infographic with wrong data

There is an infographic with wrong data for the Online Dating Industry.


That infographic is from
http://www.onlineschools.org/blog/try-online-dating/
and it was made by persons who are not experts in the Dating Industry.

Have you seen the sources in small letters at the end of that infographic? They are quite old.


The mobile data is a serious incorrect information about the mobile dating market.
They should correct that estimation to avoid false expectations.

I had contacted Juniper Research for the latest report!




Mobile Social Web 2.0 Forecasts, Challenges & Regulations 2010-2014

Here is a free WhitePaper with this image


I think mobile applications may be good for markets such as Korea and Japan, but I believe a ceiling has already been reached in North America and Europe.
Perhaps by 2014, the mobile concept will be diluted, and will disappear for online dating, with the majority of subscribers using netbooks/iPads with mobile broadband modems, or WiFi, rather than smartphones.
See for example: mobile subscriptions acounted for just 2 percent of total revenue of online dating player Meetic in 2009, down from 3 percent in 2008.

Also, actual online dating sites offering compatibility matching methods are only fueled by big marketing budgets and not by serious scientific evidence. No one (eHarmony, True, Be2, Parship, MeeticAffinity, PlentyOfFish Chemistry Predictor, Chemistry, PerfectMatch and others) can prove its matching algorithm can match prospective partners who will have more stable and satisfying relationships than couples matched by chance, astrological destiny, personal preferences, searching on one's own, or other technique as the control group in a peer_reviewed Scientific Paper.

Relationship Quality and Personality Similarity

"Relationship Quality and Personality Similarity: Differentiating Distinctiveness and Normativeness"

"Psychologists and laypeople are interested in the idea that people who are similar to each other will have relatively good relationships.

Unfortunately, many examinations of the "relationship quality and personality similarity" hypothesis suffer from two limitations that compromise previous findings:

1) defining similarity between partners in a way that confounds similarity and normativeness (or social desirability),

and

2) defining relationship quality in terms of only one measure reported by one partner.

The current study addresses both limitations.

It addresses the first by differentiating partners' distinctive similarity (the degree to which partners' share unique patterns of non-normative personality attributes) from personality normativeness (Furr, 2008).

It addresses the second limitation by having both partners describe their relationship and their relationally-based affective states along numerous dimensions (e.g., overall closeness, knowledge of each other’s goals and overall time spent alone together engaged in various activities, etc). Each member of sixty opposite-sex pairs of acquaintances provided self-reports of personality, relational attributes, and immediate affective states (both pre- and post- an interaction with their partner).

Results revealed that distinctive similarity (but not simple, unadjusted similarity) is associated with a host of positive relationship attributes and experiences, though these associations are more robust from females' perspectives than from males' perspectives. In addition, normativeness is associated with one's immediate affective state with a partner.

These results unconfound previous research by showing that it is having unique configurations of personality traits in common with one’s partner that best predicts relationship satisfaction."

Personality and speed daters

"Personality correlates of different romantic intentions in speed daters"


"Research on Sociosexuality has identified patterns of mating that reflect a range of mating preferences and strategies (Gangestad & Simpson, 2000). Previous research suggests that short-term mating behavior is associated with high extraversion, low agreeableness, and low conscientiousness for both men and women (Shackleford & Schmitt, 2008). Given the increasing prevalence of practices such as speed-dating and online dating, we searched for correlates of romantic intentions in the context of speed-dating. Prior to an experimental speed-dating session, 112 participants (55 male, 57 female; mean age= 21.97 years SD= 3.16) seeking a range of romantic interactions indicated the primary type of romantic interaction they were seeking (casual sex, dating, a relationship, or marriage) and completed self-ratings on the Big Five and other personality traits (e.g., athleticism, wealth and intelligence). Persons seeking casual sex showed high self-reported levels of wealth, narcissism and self esteem, while those seeking dating showed lower levels of intelligence and higher levels of religiosity. Additionally, persons seeking long-term relationships or marriage showed relatively high levels of intelligence and honesty. Future attention should focus on how these self views relate to impressions formed by others as well as actual behavior of the daters."

Recommendation Engines

paper: "Recommender System for Online Dating Service"



"User-User and Item-Item collaborative filtering recommenders significantly outperform global algorithms that are currently used by dating sites [offering only Browsing / Searching Options, Powerful Searching Engine but not Compatibility Matching Algorithms]."
"A blind experiment with real users [at a proprietary site named ColFi - exclusively designed for the experiment - where 111 users rated 150 photo-profiles, then two recommendation lists of top 10 profiles were generated] also confirmed that users prefer collaborative filtering based recommendations to global popularity recommendations [of 2 Czech online dating sites: ChceteMe (no longer exists now) and LibimSeTi]."
"Recommendations can be further improved by hybrid algorithms. These algorithms are combining the collaborative filtering approach with content information. Another problem specific to dating is that A_likes_B does not imply B_likes_A. Therefore each user should be probably presented with recommendations of such users, who are also interested in him/her. There is a need for reciprocal matching algorithms."
"User interface may introduce bias in the sense that users instead of providing their personal preference try to guess the global preference. This reduces the usefulness of ratings provided."


By my own experience I know that the proprietary Bidirectional Recommendation Engine (Matching based on Self-Reported Data by personal preferences & likes and dislikes) actually in use at Match ("the Daily5"at USA site) is in the range of 3 to 4 persons recommended per 1,000 persons screened, in other words any member receives on average 3 or 4 prospective mates as recommended for dating purposes per 1,000 (one thousand) members screened in Match’s big database
and
Many online dating sites had been using Behavioural Bidirectional Recommendation Engines for years, like PlentyOfFish, and they could not outperform compatibility Matching Methods based on personality profiling.

Recommendation Engines do not take into account the new discovery uncovered by Eastwick and Finkel 2008; also Kurzban and Weeden, 2007; Todd, Penke, Fasolo, and Lenton, 2007 who found that people often report partner preferences that are not compatible with their choices in real life.

cortisol, stress and men mating preferences

From the milestone paper:

"Effects of stress on human mating preferences: stressed individuals prefer dissimilar mates"

Lass-Hennemann J, Deuter CE, Kuehl LK, Schulz A, Blumenthal TD, Schachinger H. Institute of Psychobiology, University of Trier, , Trier, Germany.

"Our findings show that stress affects human mating preferences: unstressed individuals showed the expected preference for similar mates, but stressed individuals seem to prefer dissimilar mates."
"Overall, experimental evidence indicates a preference for self-resembling mates, even though there is one study that showed a preference for dissimilar mates specifically for short-term relationships (DeBruine 2005)."
"Participants were 50 male heterosexual students at the University of Trier, Germany, who responded to notices offering 25Euros for taking part in two different experiments. Participation was limited to heterosexual Caucasian students without beards, piercings or tattoos in the facial region. Furthermore, only participants with normal or corrected to normal vision and no history of hearing problems were included in the study. Participation was also limited to healthy non-smokers with body mass index in the normal range of between 20 and 25."
"Life-history theory predicts that the optimal reproductive strategy for individuals in stressful environments is to maximize current reproduction to minimize the chances of lineage extinction (Stearns 1992). A way to maximize current reproduction is to have short term relationships instead of long-term relationships, and it has been shown that individuals who experienced psychosocial stress have more short-term relationships than individuals without a history of psychosocial stress (Koehler & Chisholm 2009). Therefore, it seems likely that, in our study, stress altered men’s mating preference by making positive features of possible short-term mates (dissimilarity) more attractive than positive features of possible long-term mates (trustworthiness)."

More info about other poster/paper at eHarmonyLabs

"Stress and support: How your partner affects your hormones"

Matchmatrix debunked

Dr. James Houran had written at OnlineDatingMagazine last Jan 04, 2010 "MatchMatrix method applied to our research sample predicted the quality of a relationship rather well for couples in relatively new relationships. Yet, it didn't predict the quality of a relationship well when couples had been together two years or more. "

In other words, MatchMatrix is a hoax.

Here is the full report, written by Drs. Houran and Lange.

REPORT

http://www.onlinepersonalswatch.com/files/lange-and-houran-2.pdf

I remember I tested MatchMatrix during last July 2009 and I suspect "Friends" and "Lovers" outputs are combinations of a "modified" Biorhythms comparison! The first thing I noticed is when you maintain a fixed Birth Date in an input and slowly varies the other input, the outputs resembles sinusoidal functions.

Obsolescence of Dating Sites offering Compatibility Matching Methods

eHarmony founded: year 2000
The brains behind Eharmony are Dr. Neil Clark Warren, Dr. Galen Buckwalter and Dr. Steven Carter (Psychologists)

Cybersuitors / Matchology founded:2000
The brains behind Cybersuitors / Matchology are Dr. Glenn D. Wilson and Dr. Jon Cousins (Psychologists)

Parship founded:2001
The brain behind Parship is Dr. Hugo Schmale (Psychologist)

MatchWise founded:2003
The brain behind MatchWise is Dr. Kevin Leman (Psychologist)

True founded: 2003
The brains behind True were Dr. James Houran and Dr. Ilona Jerabek (Psychologists).

PerfectMatch founded: 2003
The brain behind Perfectmatch is Dr. Pepper Schwartz (Sociologist)

Be2 founded: 2004
The brain behind Be2 is Dr. Robert Wuttke (Sociologist)

Chemistry founded: 2005
The brain behind Chemistry is Dr. Helen Fisher (Anthropologist)

Meetic Affinity founded: 2005
The brain behind Ulteem (Meetic Affinity) is Dr. David Bernard (Psychologist)

PlentyOfFish Chemistry Predictor live since May 15 2007
The brains behind PlentyOfFish Chemistry Predictor are Dr. James Houran (Psychologist) and his team.


MyType founded: 2009
The brain behind MyType is Dr. Monica Whitty (Psychologist)



No one of them can prove its matching algorithm can match prospective partners who will have more stable and satisfying relationships than couples matched by chance, astrological destiny, personal preferences, searching on one's own, or other technique as the control group in a peer_reviewed Scientific Paper.


All of them have a low effectiveness/efficiency level of their matching algorithms (less than 10%). The majority, over 90% of its members are not going to achieve a long term relationship with commitment (or marriage)


All of them are like placebo, because
* Actual online dating sites offering compatibility matching methods, when calculating compatibility between prospective mates, have less or at least the same precision as searching on one's own. [in the range of 3 or 4 persons compatible per 1,000 persons screened]
* That is because they use:
a) simplified versions of personality traits, instead of the 16PF5 or similar with the complete inventory (16 variables)
b) inadequate quantitative methods to calculate compatibility between prospective mates

An exercise of similarity.

Which geometric figure is the most similar to the ellipse?


















The triangle? The circle? The square?

It depends of what "similar" means!

The area of the red triangle is more similar to the area of the dark blue ellipse than the area of the yellow circle and the area of the light blue square.
The shape of the yellow circle is more similar to the shape of the dark blue ellipse than the shape of the red triangle and the shape of the light blue square.
The color of the light blue square is more similar to the color of the dark blue ellipse than the color of the red triangle and the color of the yellow circle.


Using LIFEPROJECT METHOD equation, the red triangle is the most similar to the dark blue ellipse.

Another example with the PlentyOfFish Chemistry Predictor.










http://www.plentyoffish.com/personality_faq.aspx

Using LIFEPROJECT METHOD equation, it will predict different from those examples.

The "close, but dissimilar profile" will be "seen" as very similar although the trend to score of 3 of the 5 variables are in different directions.

The "similar profile, but far apart", will be "seen" as quite dissimilar.

REAL VALUES using LIFEPROJECT METHOD main matching equation

The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4 (person1)

is 88.38926174% +/- 0.00000001%

similar to

5.6.4.7.7.5.6.6.7.6.3.4.7.6.2.3 (person2)

The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4 (person1)

is 87.58389262% +/- 0.00000001%

similar to

7.8.6.9.9.7.8.8.9.8.5.6.9.8.4.5 (person3)

The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4 (person1)

is 74.79865772% +/- 0.00000001%

similar to

5.7.4.8.7.4.5.6.4.6.8.9.6.8.4.4 (person4)

The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4 (person1)

is 92.55033557% +/- 0.00000001%

similar to

7.7.6.8.8.7.6.5.8.7.4.5.7.7.3.4 (person5)

The pattern 6.7.6.7.6.7.6.7.6.7.6.7.6.7.6.7 (personaF1)

is 63.75838900% +/- 0.00000001%

similar to

4.5.4.5.4.5.4.5.4.5.4.5.4.5.4.5 (personaF2)

The pattern 6.7.6.7.6.7.6.7.6.7.6.7.6.7.6.7 (personaF1)

is 41.61073800% +/- 0.00000001%

similar to

3.4.3.4.3.4.3.4.3.4.3.4.3.4.3.4 (personaF3)

How LIFEPROJECT METHOD calculates similarity

Here is how LIFEPROJECT METHOD calculates similarity between quantized patterns.

From the paper "METHODOLOGICAL AND DATA ANALYTIC ADVANCES IN THE STUDY OF INTERPERSONAL RELATIONSHIPS: INTRODUCTION TO THE SPECIAL ISSUE"
http://www.blackwell-synergy.com/doi/abs/10.1111/j.1475-6811.1999.tb00200.x

At page 413 says: "It is vital for the study of personal relationships, as for any scientific discipline, to develop methodologies that are specifically designed to address the questions posed by the discipline. The articles in this special issue represent an effort in that direction. Perhaps equally important is the need for individuals who are involved in relationships study to learn these new techniques and to apply them in their research. It is also important for investigators to challenge statisticians to create new analytic techniques when existing ones are inadequate. These tasks are left to you, the reader."


That is because I had invented a new quantitative method to assess similarity.
Here is explained but without divulging proprietary information.

In compatibility matching methods there are 2 steps:
1) to measure personality traits or other variables.
2) to calculate compatibility between prospective mates.


The output of the 16PF5 test are 16 independent variables STens (Standard Tens) taking integer values from 1 to 10. STens divide the score scale into ten units.
STens have the advantage that they enable results to be thought of in terms of bands of scores, rather than absolute raw scores. These bands are narrow enough to distinguish statistically significant differences between candidates, but wide enough not to over emphasize minor differences between candidates.

Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.


I calculate similarity in personality patterns with (a proprietary) pattern recognition by correlation method. It takes into account the score and the trend to score of any pattern.


Dyadic comparison between person #X and person #Y is given from the following formula, derived / adapted from an advanced math equation


The BRA (#X/ means client #X's 16PF5 Report
The KET /#Y) means client #Y's 16PF5 Report



/CQ/ means Comparison Operator

(#X/CQ/#Y) means the Comparison between client #X and client #Y

(#X/CQ/#Y) == K01(AX/CQ/AY) + K02(BX/CQ/BY) + K03(CX/CQ/CY) + K04(EX/CQ/EY) + K05(FX/CQ/FY) + K06(GX/CQ/GY) + K07(HX/CQ/HY) + K08(IX/CQ/IY) + K09(LX/CQ/LY) + K10(MX/CQ/MY) + K11(NX/CQ/NY) + K12(OX/CQ/OY) + K13(Q1X/CQ/Q1Y) + K14(Q2X/CQ/Q2Y) + K15(Q3X/CQ/Q3Y) + K16(Q4X/CQ/Q4Y) == PROBABILITY OF BEING COMPATIBLE


(A) Warmth; (B) Reasoning; (C) Emotional Stability; (E) Dominance, (F) Liveliness; (G) RuleConsciousness; (H) Social Boldness; (I) Sensitivity; (L) Vigilance; (M) Abstractedness; (N) Privateness (O) Apprehension; (Q1) Openness to Change; (Q2) SelfReliance; (Q3) Perfectionism; (Q4) Tension. 16 independent variables that take integer values from 1 to 10

With K01 + K02 + K03 + K04 + K05 + K06 + K07 + K08 + K09 + K10 + K11 + K12 + K13 + K14 + K15 + K16 == 1 or 100%


K01 diff from K02 diff from K03 diff from K04 diff from K05 diff from K06 diff from K07 diff from K08 diff from K09 diff from K10 diff from K11 diff from K12 diff from K13 diff from K14 diff from K15 diff from K16 means not necessarily all the same


(A/CQ/B) == (A/CQ/C) == (A/CQ/E) == ..... == (A/CQ/Q4) == 0
(B/CQ/A) == (B/CQ/C) == (B/CQ/E) == ..... == (B/CQ/Q4) == 0
……………………………………………………………………………………………………
(Q4/CQ/A) == (Q4/CQ/B) == (Q4/CQ/C) == ..... == (Q4/CQ/Q3) == 0

and

(1/CQ/1)
(1/CQ/2) == (2/CQ/1)
(1/CQ/3) == (3/CQ/1)
(1/CQ/4) == (4/CQ/1)
(1/CQ/5) == (5/CQ/1)
(1/CQ/6) == (6/CQ/1)
(1/CQ/7) == (7/CQ/1)
(1/CQ/8) == (8/CQ/1)
(1/CQ/9) == (9/CQ/1)
(1/CQ/10) == (10/CQ/1)

(2/CQ/1) == (1/CQ/2)
(2/CQ/2)
(2/CQ/3) == (3/CQ/2)
(2/CQ/4) == (4/CQ/2)
(2/CQ/5) == (5/CQ/2)
(2/CQ/6) == (6/CQ/2)
(2/CQ/7) == (7/CQ/2)
(2/CQ/8) == (8/CQ/2)
(2/CQ/9) == (9/CQ/2)
(2/CQ/10) == (10/CQ/2)
………………………………………………
………………………………………………

(10/CQ/1) == (1/CQ/10)
(10/CQ/2) == (2/CQ/10)
(10/CQ/3) == (3/CQ/10)
(10/CQ/4) == (4/CQ/10)
(10/CQ/5) == (5/CQ/10)
(10/CQ/6) == (6/CQ/10)
(10/CQ/7) == (7/CQ/10)
(10/CQ/8) == (8/CQ/10)
(10/CQ/9) == (9/CQ/10)
(10/CQ/10)

(all real values of the complete base were derived by Fernando Ardenghi)




BRA (#X/ means person #X's 16PF5 Report
KET /#Y) means person #Y's 16PF5 Report
/CQ/ means Comparison Operator

For person #X:: A:6.B:7.C:6.E:8.F:9.G:6.H:7.I:7.L:8.M:7.N:2.O:5.Q1:8.Q2:7.Q3:3.Q4:4
16 distinguishable particles in a one_dimensional box of length L and infinite outside the box with 10 quantized levels of energy (named box X)
distinguishable particle (A) Warmth at level "6"
distinguishable particle (B) Reasoning at level "7"
distinguishable particle (C) Emotional Stability at level "6"
distinguishable particle (E) Dominance at level "8"
distinguishable particle (F) Liveliness at level "9"
distinguishable particle (G) RuleConsciousness at level "6"
distinguishable particle (H) Social Boldness at level "7"
distinguishable particle (I) Sensitivity at level "7"
distinguishable particle (L) Vigilance at level "8"
distinguishable particle (M) Abstractedness at level "7"
distinguishable particle (N) Privateness at level "2"
distinguishable particle (O) Apprehension to Change at level "5"
distinguishable particle (Q1) Openness at level "8"
distinguishable particle (Q2) SelfReliance at level "7"
distinguishable particle (Q3) Perfectionism at level "3"
distinguishable particle (Q4) Tension at level "4"

And

For person #Y:: A:5.B:7.C:4.E:8.F:7.G:4.H:5.I:6.L:4.M:6.N:8.O:9.Q1:6.Q2:8.Q3:4.Q4:4
16 distinguishable particles in other one_dimensional box of length L and infinite outside the box with 10 quantized levels of energy (named box Y)
distinguishable particle (A) Warmth at level "5"
distinguishable particle (B) Reasoning at level "7"
distinguishable particle (C) Emotional Stability at level "4"
distinguishable particle (E) Dominance at level "8"
distinguishable particle (F) Liveliness at level "7"
distinguishable particle (G) RuleConsciousness at level "4"
distinguishable particle (H) Social Boldness at level "5"
distinguishable particle (I) Sensitivity at level "6"
distinguishable particle (L) Vigilance at level "4"
distinguishable particle (M) Abstractedness at level "6"
distinguishable particle (N) Privateness at level "8"
distinguishable particle (O) Apprehension to Change at level "9"
distinguishable particle (Q1) Openness at level "6"
distinguishable particle (Q2) SelfReliance at level "8"
distinguishable particle (Q3) Perfectionism at level "4"
distinguishable particle (Q4) Tension at level "4"

Each quantized level is associated with a probability density function.
(#X/CQ/#Y) is the sum of the comparisons between different states, the sum of partial probabilities.
(#X/CQ/#Y) == 74.79865772%
Read as the pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4 is 74.79865772% similar to the pattern 5.7.4.8.7.4.5.6.4.6.8.9.6.8.4.4





Here some examples

PERSONALITY PATTERN
Client #01 ---- 16PF5 Profile A:6.B:7.C:6.E:8.F:9.G:6.H:7.I:7.L:8.M:7.N:2.O:5.Q1:8.Q2:7.Q3:3.Q4:4
Client #02 ---- 16PF5 Profile A:5.B:7.C:4.E:8.F:7.G:4.H:5.I:6.L:4.M:6.N:8.O:9.Q1:6.Q2:8.Q3:4.Q4:4
Client #03 ---- 16PF5 Profile A:2.B:5.C:4.E:6.F:3.G:8.H:7.I:6.L:3.M:9.N:9.O:8.Q1:2.Q2:5.Q3:5.Q4:6
Client #04 ---- 16PF5 Profile A:7.B:7.C:6.E:8.F:8.G:7.H:6.I:5.L:8.M:7.N:4.O:5.Q1:7.Q2:7.Q3:3.Q4:4
Client #05 ---- 16PF5 Profile A:4.B:9.C:5.E:4.F:1.G:3.H:4.I:9.L:7.M:8.N:7.O:5.Q1:6.Q2:7.Q3:9.Q4:10
Client #06 ---- 16PF5 Profile A:8.B:6.C:3.E:5.F:2.G:9.H:6.I:9.L:3.M:6.N:7.O:5.Q1:5.Q2:7.Q3:7.Q4:4
Client #07 ---- 16PF5 Profile A:5.B:7.C:6.E:4.F:6.G:7.H:3.I:5.L:8.M:5.N:4.O:6.Q1:7.Q2:1.Q3:6.Q4:6
Client #08 ---- 16PF5 Profile A:9.B:8.C:5.E:7.F:5.G:6.H:8.I:2.L:6.M:4.N:8.O:7.Q1:6.Q2:5.Q3:5.Q4:9

Comparison data base for 8 clients, needs [8 * (8-1)] / 2 = 28 comparisons

(#01/CQ/#02) == K01 (6/CQ/5) + K02 (7/CQ/7) + K03 (6/CQ/4) + K04 (8/CQ/8) + K05 (9/CQ/7) + K06 (6/CQ/4) + K07 (7/CQ/5) + K08 (7/CQ/6) + K09 (8/CQ/4) + K10 (7/CQ/6) + K11 (2/CQ/8) + K12 (5/CQ/9) + K13 (8/CQ/6) + K14 (7/CQ/8) + K15 (3/CQ/4) + K16 (4/CQ/4) == 74.79865772% PROBABILITY OF BEING COMPATIBLE

(#02/CQ/#01) == (#01/CQ/#02) == 74.79865772%
and so on for the rest (27 comparisons)

(#01/CQ/#02) == #01 to #02 == 74.79865772%
// #02 to #01 == 74.79865772%
#01 to #03 == 54.09395973% // #02 to #03 == 63.59060403%
#01 to #04 == 92.55033557% // #02 to #04 == 75.26845638%
#01 to #05 == 57.71812081% // #02 to #05 == 61.00671141%
#01 to #06 == 59.73154362% // #02 to #06 == 65.90604027%
#01 to #07 == 68.99328859% // #02 to #07 == 64.49664430%
#01 to #08 == 62.75167785% // #02 to #08 == 66.34228188%

#03 to #01 == 54.09395973% // #04 to #01 == 92.55033557%
#03 to #02 == 63.59060403% // #04 to #02 == 75.26845638%
#03 to #04 == 54.89932886% // #04 to #03 == 54.89932886%
#03 to #05 == 49.49664430% // #04 to #05 == 56.54362416%
#03 to #06 == 67.34899329% // #04 to #06 == 64.42953020%
#03 to #07 == 53.99328859% // #04 to #07 == 73.32214765%
#03 to #08 == 61.20805369% // #04 to #08 == 66.54362416%

#05 to #01 == 57.71812081% // #06 to #01 == 59.73154362%
#05 to #02 == 61.00671141% // #06 to #02 == 65.90604027%
#05 to #03 == 49.49664430% // #06 to #03 == 67.34899329%
#05 to #04 == 56.54362416% // #06 to #04 == 64.42953020%
#05 to #06 == 62.18120805% // #06 to #05 == 62.18120805%
#05 to #07 == 62.98657718% // #06 to #07 == 57.85234899%
#05 to #08 == 59.02684564% // #06 to #08 == 60.43624161%

#07 to #01 == 68.99328859% // #08 to #01 == 62.75167785%
#07 to #02 == 64.49664430% // #08 to #02 == 66.34228188%
#07 to #03 == 53.99328859% // #08 to #03 == 61.20805369%
#07 to #04 == 73.32214765% // #08 to #04 == 66.54362416%
#07 to #05 == 62.98657718% // #08 to #05 == 59.02684564%
#07 to #06 == 57.85234899% // #08 to #06 == 60.43624161%
#07 to #08 == 61.87919463% // #08 to #07 == 61.87919463%




More examples:
The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4
is 74.79865772% +/- 0.00000001%
similar to
5.7.4.8.7.4.5.6.4.6.8.9.6.8.4.4

The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4
is 92.55033557% +/- 0.00000001%
similar to
7.7.6.8.8.7.6.5.8.7.4.5.7.7.3.4

The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4
is 88.38926174% +/- 0.00000001%
similar to
5.6.4.7.7.5.6.6.7.6.3.4.7.6.2.3

The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4
is 87.58389262% +/- 0.00000001%
similar to
7.8.6.9.9.7.8.8.9.8.5.6.9.8.4.5

The pattern 6.7.5.8.8.6.7.7.8.7.4.5.8.7.3.4
is 60.23489933% +/- 0.00000001%
similar to
8.9.7.10.10.8.9.9.10.9.6.7.10.9.5.6

The pattern 6.7.5.8.8.6.7.7.8.7.4.5.8.7.3.4
is 68.15436242% +/- 0.00000001%
similar to
4.3.7.8.5.4.7.8.7.7.6.8.8.5.7.6

The pattern 6.7.6.7.6.7.6.7.6.7.6.7.6.7.6.7
is 63.75838900% +/- 0.00000001%
similar to
4.5.4.5.4.5.4.5.4.5.4.5.4.5.4.5

The pattern 6.7.6.7.6.7.6.7.6.7.6.7.6.7.6.7
is 41.61073800% +/- 0.00000001%
similar to
3.4.3.4.3.4.3.4.3.4.3.4.3.4.3.4

The pattern 6.7.6.7.6.7.6.7.6.7.6.7.6.7.6.7
is 88.59060403% +/- 0.00000001%
similar to
7.8.7.8.7.8.7.8.7.8.7.8.7.8.7.8



High precision in matching algorithms is precisely the key to open the door and leave the infancy of compatibility testing.
It is all about achieving the eighth decimal!
With 8 decimals, you have more precision than any person could achieve by searching on one's own, but the only way to achieve the eighth decimal is using analysis and correlation with quantized patterns.





High Precision patterns comparison between prospects SHOULD specify:
1) the ENSEMBLE (the whole set of different valid possibilities)

2) how exactly the compatibility matching method works, specifying main matching equation/ formula (without revealing proprietary information).

3) Which is the average number of "compatible real persons" for one person over the entire database? E.g.: 3 persons in a 100,000 persons database or 12 in 1,000,000. (or the 3 most compatible in 100,000 or the 12 most compatible in 1,000,000).

4) The whole precision
E.g.: "The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4
is 92.55033557% +/- 0.00000001%
similar to the pattern 7.7.6.8.8.7.6.5.8.7.4.5.7.7.3.4"

DNA matching methods

Basisnote, GenePartner, ScientificMatch and other proposals offering DNA matching are only based on the T_shirt Experiment that only proved:
normally cycling women (not pregnant and not taking contraceptive pills) are (temporarily) attracted by the perspiration scent of clothes used by men with a Major Histocompatibility Complex MHC more dissimilar to theirs,
and not proved: women attracted by those men for long term mating with commitment.

2 Scientific Papers debunk their claims.
1) "Human oestrus" Gangestad & Thornhill (2008)

http://rspb.royalsocietypublishing.org/content/275/1638/991.full.pdf

"Only short-term but not long-term partner preferences tend to vary with the menstrual cycle"

2) "Does the contraceptive pill alter mate choice in humans?" Alvergne & Lummaa (2009)

http://www.thestranger.com/images/blogimages/2009/10/07/1254931423-tree_final_proofs.pdf

".. whereas normally cycling women express a preference for MHC (Major Histocompatibility Complex) dissimilarity in mates, pill users prefer odours of MHC-SIMILAR men, indicating that pill use might eliminate adaptive preferences for genetic dissimilarity."
................
"Recently, Roberts et al. attempted to eliminate these potential confounds by adopting a within-subject design in which women's mate preferences were assessed before and after they began taking the pill. Women starting the pill showed a significant preference shift towards MHC SIMILARITY compared with three months before the pill was taken, a shift that was not observed in the control group of normally cycling women."

Latin America market

The local culture in Latin America differs from other regions:

Latin Americans do mostly not have credit cards.

The ones who have credit cards, do mostly not use them for subscriptions.

Latin Americans hate Banks or do not trust in Banks, because Banks had a bad "historic records", they had stolen the money of their clients several times.

Latin American users mostly pay in cash or by other electronic methods like PagoFacil, Rapipago, by Post Office wire transactions or by Western Union for International transactions.

Here in Latin America, it is full of free/cheap low quality online dating proposals -Search and Recommendation engines- powered by local newspapers.

There are also many tricks to use dating sites like Match, Meetic and Be2 for free in Latin American countries.

Latin American users send more SMS and make less calls from mobile phones than USA, Canada and European citizens. The primary use of cell phones are for sending SMS (text messages). More than 70% of people who own a cell phone, are pre-paid clients. They do not receive bills, they charge credit in their cell phones by 2 methods: Acquiring pre-paid cards at kiosks/drugstores or via virtual charge at kiosks/drugstores/supermarkets or at any place with a PosNet terminal (Banelco or Link)

Latin American users need broadband on PC, Macs, notebooks and netbooks because they are very fond of sharing or downloading copyrighted material, like films/movies/music/videos, etc. using sites like Kazaa or eMule to share and sites like Rapidshare, MegaUpload, or other similar sites to download for free. They make an intensive use of Internet. This intensive use includes reading newspapers, sending emails, chatting, video calls, sharing or downloading movies, music, etc.The value they assign to that intensive use should be worth than what the fee they pay for broadband on fixed computers or mobile broadband on notebooks and netbooks.

Now are in decadence, but it used to be lots of Cybercafes where you can hire a computer with broadband for less than USD1.00 per hour.

Latin American users are very fond to obtain things for free, to avoid paying. They are very fond of Microsoft and Yahoo instant messaging and Skype to speak and make video calls. They are very fond of free email accounts like Gmail, Hotmail and Yahoo. They are very fond to read newspapers for free. If you live near any place with WiFi like hotels, bars, restaurants, drugstores, most probably you can use Internet for free to read online newspapers, check email accounts, chat or make video calls, etc, (not for secure transactions)

----------------------
MEETIC (FR 0004063097 – MEET), consolidated annual revenue for the financial year to 31st December 2009, The Group's total consolidated annual revenue came to 164.5 million euros. The Meetic Group had 920,286 subscribers at 31st December 2009.

In 2009, ParPerfeito recorded revenue of 6.6 million euros, EBITDA of 1.7 million euros and net profit of 0.8 million euros. At 31st December 2009, ParPerfeito had a subscriber base of 76,000 clients.

6.6 million euros / 164.5 million euros == 0.04012

ParPerfeito contributtes only with 4% of The Meetic Group consolidated annual revenue

76,000 subscribers / 920,286 subscribers == 0.08258

ParPerfeito contributtes only with 8.25% of The Meetic Group subscribers base.

It is definitely true: Match, Meetic, Be2 and others had been spending millions of U.S. Dollars since years and until now they do not understand the Latin American culture.

LIFEPROJECT is like 4 pieces puzzle

LIFEPROJECT is like 4 pieces puzzle.

1 is the psycho tests (Multi-language normative tests).

2 is the supercomputer (IBM, Fujitsu, Cray, Nec, Hitachi) or high speed server arrangement (like one used in Google).

3 is the algorithm I have invented (uses QUANTUM MECHANICS MATH and STATISTICAL EQUATIONS).

4 is the marketing scheme revenue by memberships USD300 new / USD30 renewal
(niche market:
* persons that have been hurt in their feelings by others in many on line dating sites. Many people complaint about an important thing: sooner or later, they want to contact compatible real persons, so they will need reliability / high precision in on line dating.
* persons that are searching for a multicultural on line dating. (e.g. a German person living in Germany and compatible with a Brazilian person who speaks Portuguese and lives in Australia)
* persons that have time to wait, perhaps as long as a whole year, or more.
* and all of them have the same reason to pay a fee: this fee will work as a barrier to avoid free users, who could hurt their feelings.

ABOUT marketing scheme:
The MUST HAVE marketing theory: Any prospective client must have almost ONE VALID reason to buy a product or pay for a service subscription. Applying this concept to Online Dating Industry:

Reason #1: PRECIOUS TIME more valuable than MONEY. Nothing is real free!!! Many persons speak/write about or promote the FREE condition of a dating site; they are only CHEAP CHANNELS for deliver ADS, i.e. infomercial-advertainment companies on the web. When you post your profile to a "FREE dating site" or when you search for compatible real persons, you are spending precious time. TIME that you are paying with your LIFE. If you "quantify" the time you spent in a "FREE dating site", suppose USD5.00/hour x 45 hours (1/2 hour x 3 months) == USD 225.00, USD 75/month!!! It is worth than many SERIOUS dating site's subscription fee!!!!

Reason #2: AVOID BEING HURT IN OWN FEELINGSA client will pay a fee to create a barrier which will avoid free users, who could hurt other clients' feelings. "If any person does not pay for the service or does not want to pay for the service, he or she is not interested in serious dating, or is not interested in investing time and effort in building a new relationship with future in mind"

Reason #3: AVOID LOW RELIABILITY/ LOW QUALITY CONTACTS
"free users" will realize/understand that spending time and effort searching low-reliable profiles in "free or cheap dating sites" (a lot of hours contacting persons with low success rate, with low satisfaction index) is more expensive THAN paying a fee (USD300-USD800 ? per year) to a quality contacts provider!


The only way I see to kill Match&Chemistry, eHarmony, Yahoo!Personals, True, Meetic, Be2, Parship and PerfectMatch is offering a high quality compatibility matching method to dissatisfied/past customers of those online dating sites, trying to steal their users; and to prospective customers of Offline Proposals.

Example for the matching algorithm I had invented

Ensemble (whole set of different valid possibilities): 1 * E16 with 16PF5

Precision: better than 0.00000001% with Self-Adjustment
- 3 most compatible persons in a 100,000 persons database,
- 12 most compatible persons in a 1,000,000 persons database,
- 48 most compatible persons in a 10,000,000 persons database,

Results are displayed with 2 integers + 8 decimals, like 92.55033557% +/- 0.00000001%

other persons had seen the phenomenon

The entire Online Dating Industry for serious daters in 1st World Countries is a HOAX, performing as a Big Online Casino, with low successful rates.

Here are some proofs/evidence:

- No actual online dating site offering a compatibility matching method [eHarmony, True, Meetic, Chemistry, PerfectMatch, Be2, Parship, MyType, RewardingLove, PlentyOfFishChemistryPredictor and others] has a credible peer reviewed Scientifc Paper by Academics (public scrutiny of findings) from different Universities showing its matching algorithm can match prospective partners who will have more stable and satisfying relationships with low divorce rates than couples matched by chance, astrological destiny, personal preferences, searching on one's own, or other technique as the control group.

eHarmony, True, Meetic, Chemistry, PerfectMatch, Be2, Parship, MyType, RewardingLove, PlentyOfFishChemistryPredictor, no one has published any credible peer reviewed Scientific Paper about the effectiveness/efficiency of their matching algorithms.

They are all like placebo, because they have less or at least the same precision as searching on one's own OR less or at least the same precision as recommendation engines [in the range of 3 to 4 persons compatible per 1,000 persons screened]

Moreover
The success rate* of Chemistry is less than 6%**.
The success rate* of eHarmony is less than 10%**.
*success rate == percentage of persons who leave the site because they found someone compatible for long term mating with commitment.
**estimated by Fernando Ardenghi using reverse engineering.

The majority, over 90% of their members are not going to achieve a long term relationship with commitment (or marriage) using those sites.

- eHarmony 2 billion served
http://www.pinoy.ca/eharmony/1880
Shows its matching method is like a machine gun shooting flowers, good for nothing.

- Helen Fisher publised the book "Why Him? Why Her?: Finding Real Love By Understanding Your Personality Type" for marketing purposes but she never published a paper for public and Academic scrutiny of her findings.

- Markus Frind is his blog post "New Research Study raises questions about the scientific validity of some matchmaking sites.", he had written "...markus Says: July 27, 2009 at 5:11 pm my test is only 20% better than chance. But its not validated and neither is any other sites test. ....."
http://plentyoffish.wordpress.com/2009/07/15/new-research-study-raises-questions-about-the-scientific-validity-of-some-matchmaking-sites/

- Complaints from dissatisfied customers in differents blogs / forums you can find using Google.

- paper "Do Online Matchmaking Tests Work? An Assessment of Preliminary Evidence for a Publicized Predictive Model of Marital Success" North American Journal of Psychology, 2004, Vol. 6, pp. 507-526, that says at page#15 "....development and validation of online compatibility testing; and disclosing those findings for public and academic scrutiny without divulging proprietary information.... " Year 2010, still waiting for eHarmony, PerfectMatch, Chemistry, Meetic, Be2, Parship, and others.

- article "Researchers Skeptical of Claims by Online Dating Sites"
http://www.physorg.com/news164292891.html

- The comic "Zack Hill's mom joins eHarmony"
Lois: Are you telling me that out of all these guys, you didn't like one?
Jan: I did not.
Lois: This is like the phone directory for a small town!
Jan: The town of LoserVille.
http://www.pinoy.ca/eharmony/1810

- The report from Catalyst Group
http://www.pinoy.ca/eharmony/1881

- Info from
http://onlinedatingparadox.com/about
although that paradox is not true. The author says "Online Dating Paradox If there are plenty of fish in the sea, why isn't anyone biting? ... online dating is much harder than traditional dating. ..." because he could not identify well the phenomenon, the Online Dating Sound Barrier.


The entire Online Dating Industry for serious daters in 1st World Countries has:
* No Legislation.
* No Quality Norms.
* Low reliable background checks.
* Divorce rates are still very, very high.

the online dating sound barrier

The entire Online Dating Industry for serious daters in 1st World Countries is a HOAX, performing as a Big Online Casino, with low successful rates.


There is a range convergence phenomenon between the 3 mains tools online dating sites can offer: searching by your own, Bidirectional Recommendation Engines and Compatibility Matching Methods.
Any member receives on average 3 to 4 prospective mates as selected / recommended / compatible for dating purposes per 1,000 (one thousand) members screened in the database.
They all 3 are performing the same for serious daters, with a high percentage of false positives, like gun machines shooting flowers.


That range convergence phenomenon is what I had called "the online dating sound barrier", in 2003, when I had discovered than problem, 7 long years ago.

I had understood FIRST and BETTER than anybody how to solve than problem:

The Online Dating Industry does not need a 10% improvement, a 50% improvement or a 100% improvement.
It does need "a 100 times better improvement"


Breaking "the online dating sound barrier" is to achieve at least:
3 most compatible persons in a 100,000 persons database.
12 most compatible persons in a 1,000,000 persons database.
48 most compatible persons in a 10,000,000 persons database.
100 times better than Compatibility Matching Algorithms used by actual online dating sites!

The only way to achieve that is:
- using the 16PF5 normative personality test, available in different languages to assess personality of members, or a proprietary test with exactly the same traits of the 16PF5. The ensemble of the 16PF5 is: 10E16, big number as All World Population is nearly 6.7 * 10E9
(WorldWide, there are over 5,000 -five thousand- online dating sites, but no one is using the 16PF5)

- expressing compatibility with eight decimals, like The pattern 6.7.6.8.9.6.7.7.8.7.2.5.8.7.3.4 is 92.55033557% +/- 0.00000001% similar to the pattern 7.7.6.8.8.7.6.5.8.7.4.5.7.7.3.4
Using a quantized pattern comparison method (part of pattern recognition by cross-correlation) to calculate similarity between prospective mates.





Since the beginning of 2003, I had been testing online dating sites who offer a compatibility matching method to their daters by creating dummy Male/Female profiles and using them as test points for reverse engineering purposes.

All the algorithms used by eHarmony, True, Chemistry, PerfectMatch, Be2, Meetic, PlentyOfFish Chemistry Predictor, Parship, RewardingLove, MyType, etc. are like placebo, because they will show, to any member, 3 to 4 persons as highly compatible per 1,000 persons screened, so in a 10,000,000 persons database, any member will see 30,000 to 40,000 members as highly compatible; 30,000 persons is the population of an average small city. Any person can achieve 3 to 4 persons as highly compatible per 1,000 persons screened, searching by his/her own or by mutual filtering methods.

Success Rates of those sites are less than 10%. The majority of their members are not going to achieve a long term relationship with commitment (or marriage).



Breaking "the online dating sound barrier" is to achieve far better precision than searching on one's own or mutual filtering.

* Matching based on Self-Reported Data / Bidirectional Recommendation Engines (Collaborative Filtering) will always be in the range of 3 or 4 persons "recommended" per 1,000 persons screened, in exactly the same range of searching on one's own.


* Actual online dating sites offering compatibility matching methods, when calculating compatibility between prospective mates, have less or at least the same precision as searching on one's own. [in the range of 3 to 4 persons compatible per 1,000 persons screened]
* That is because they use:
a) simplified versions of personality traits, instead of the 16PF5 or similar with the complete inventory (16 variables)
b) inadequate quantitative methods to calculate compatibility between prospective mates, like eHarmony which uses Dyadic Adjustment Scale or other sites which use multivariate linear / logistic regression equations o other equations.
To solve that problem I propose:

*) the 16PF5 or similar normative personality test to measure personality of normal persons over 26 years old interested in serious dating.
*) a new quantitative method to calculate compatibility between prospective mates, based on quantized pattern comparison (part of pattern recognition by correlation) named LIFEPROJECT method.

The value of my algorithm is to achieve far more precision than searching on one's own [in the range of 3 persons compatible per 100,000 persons screened]
and
try to prove if only high level on personality* similarity* between mates is the core of relationship stability and satisfaction for normal persons over 26 years old interested in serious dating.
*personality: measured with the 16PF5 normative test in different languages.
*similarity: calculated using the method I had invented, LIFEPROJECT method.

That is what is going to revolutionize the Online Dating Industry.

My effort is directed to prove that temporal patterns of relationship variables may indeed play a significant role between prospective mates -> Last stage of temporal patterns: if only high level on personality* similarity* between mates is the core of relationship stability and satisfaction == Dyadic Success for 26_and_more_years_old_persons interested in serious dating.
personality*: measured with the 16PF5 normative test in different languages (no other actual online dating site is using it!).
similarity*: calculated using quantum math equations with the quantitative method I had invented, named LIFEPROJECT METHOD, with quantized pattern comparison (a part of pattern recognition by correlation)
Example for the matching algorithm I had invented
- Ensemble (whole set of different valid possibilities): 1 * E16 with 16PF5
- Precision: better than 0.00000001% with Self-Adjustment
3 most compatible persons in a 100,000 persons database,
12 most compatible persons in a 1,000,000 persons database,
48 most compatible persons in a 10,000,000 persons database,
- Results are displayed with 2 integers + 8 decimals, like 92.55033557% +/- 0.00000001%

The World Population (WP) is nearly 6,700 millions persons == 6.7 * E9
16PF5's Ensemble == 1 * E16
WP / Ensemble == (6.7 * E9) / (1 * E16) == 6.7 * E-7 == 0.67 * E-6
i.e. All World Population is 0.67 micro part of the Ensemble!!!

papers about quantitative methods

papers about: METHODOLOGICAL AND DATA ANALYTIC ADVANCES IN THE STUDY OF INTERPERSONAL RELATIONSHIPS == QUANTITATIVE METHODS USED TO EVALUATE ATTRIBUTES AND TO COMPARE BETWEEN PERSONS. (If you plan to innovate in the OnLine Dating & Social Networking Industry, these papers are all a "must read")

------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------

"A discussion by Gable and Reis concerning the importance of studying relationship phenomena using within_person methodologies in addition to the between_person methods that are commonly employed in relationships research today. Within_person methods involve sampling observations from an individual across multiple contexts, across multiple relationship partners, and/or across time. In addition to enumerating the benefits of such research, the authors also present a thoughtful discussion of the challenges that it involves. Finally, they examine data analytic approaches appropriate to analyzing data derived from this research paradigm." http://www.blackwell-synergy.com/doi/abs/10.1111/j.1475-6811.1999.tb00201.x

"NOW AND THEN, THEM AND US, THIS AND THAT: STUDYING RELATIONSHIPS ACROSS TIME, PARTNER, CONTEXT, AND PERSON. "
Abstract: Personal relationships are frequently studied using methods and analyses that reflect an interest in relationships as between_persons phenomena. Although informative, there is much to be learned from examining relational phenomena from a within_persons perspective. The present article reviews the application of within_persons approaches to both the conceptualization and investigation of relational phenomena. The benefits of studying variation in psychologically meaningful constructs across multiple relationships, across different contexts within a relationship, and across time are outlined. Moreover, combinations of between_persons and within_persons strategies that can examine how relational, contextual, and temporal variation differs across people are discussed. Methodological and statistical considerations important to such designs are also outlined, and their limitations are discussed.

------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------

"Haslam addresses issues involved in creating taxonomies of relationships, adapting methods that have been more commonly used in the fields of psychopathology, personality psychology, and behavior genetics. These taxometric methods are techniques that test between discrete and continuous models of latent variables. Arguing that these methods have great potential for the relationships field, Haslam describes three statistical techniques used to test the usefulness of taxonomies and to create new ones. A detailed example is employed to walk readers through the process of developing and testing taxonomies."
http://www.blackwell-synergy.com/doi/abs/10.1111/j.1475-6811.1999.tb00207.x

"TAXOMETRIC AND RELATED METHODS IN RELATIONSHIPS RESEARCH. "
Abstract: Research on personal relationships inescapably uses taxonomies for classifying people, relationships, and interpersonal processes and events, and often develops new ones. However, constructing a good taxonomy is no simple matter. Many existing classification methods have serious weaknesses, and they carry the risk of drawing taxonomic distinctions that are spurious. In addition, researchers frequently make unwarranted assumptions about the nature of the taxonomic categories that they employ in their work. This article introduces a family of quantitative methods for testing and generating taxonomies. Although they have seen little use to date outside of psychopathology, personality psychology, and behavioral genetics, these methods are versatile and readily adapted to the domain of personal relationships, where they offer many research possibilities. Three of the methods are illustrated in a study of elementary forms of relationships.
At page 522 " … The two taxometric procedures to be discussed are called the MAXCOV (maximum covariance) and MAMBAC (means above minus below a cut) procedures. These are the two procedures that have been most widely used in taxometric research to date. Both procedures require the use of several 'indicators' of the conjectured latent variable. These indicators can be any measures that are associated with this variable, such as personality scales, item ratings, physiological measurements, and so on. …."
At page 523 "…. Admixture or commingling analysis (the terms are essentially interchangeable) is an alternative way to detect categories, and to test between discrete and continuous models of latent variables. …."
At page 525 "The three quantitative methods described above will be illustrated in a study of a theory of elementary forms of relationship developed by Alan Fiske (1991). The theory proposes four cognitive models in terms of which relationships are represented, comprehended, evaluated, and constructed. The Communal Sharing model organizes relationships in terms of collective belonging or solidarity. Members of an in_group are treated as equivalent elements of a bounded set, and consequently individual distinctiveness is ignored. By contrast, the Authority Ranking model organizes relationships in asymmetrical terms. Parties to relationships governed by this model are hierarchically ordered, with higher_ranked individuals authorized to command, protect, dominate, and precede, and lower ranked individuals expected to defer, obey, and show loyalty and respect. The Equality Matching model organizes relationships with reference to their degree of balance or imbalance; it is manifested most distinctly in turn_taking, reci p r ocity, distributions of equal shares, democratic voting, and tit_for_tat retaliation. The Market Pricing model, finally, organizes relationships with reference to a common scale of ratio values such as money. Emphasis is on proportions; earning a wage based on hours worked, getting a good return on an investment of effort, or efficient use of time; and social transactions are reckoned as rational calculations of cost and benefit"
At page 533 " In conclusion, taxometric and admixture procedures offer the interested researcher some accessible quantitative methods for investigating fundamental questions in the study of personal relationships. Their versatility and promise have yet to be exploited in this domain, although they are increasingly appreciated in others, and they offer relationship researchers a chance to make innovative contributions."

------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------

"Griffin, Murray, and Gonzalez discuss the common practice in relationships research of computing difference or discrepancy scores to represent SIMILARITY OR DISSIMILARITY BETWEEN INDIVIDUALS. Although difference scores and their variants have great intuitive appeal, such scores involve numerous pitfalls when they are used in correlational research. In this article, the authors review the problems associated with difference score correlations using a descriptive and graphical approach rather than relying on formulas. They also describe three data analytic techniques that can be used as alternatives to difference score correlations."

http://www.blackwell-synergy.com/doi/abs/10.1111/j.1475-6811.1999.tb00206.x

"DIFFERENCE SCORE CORRELATIONS IN RELATIONSHIP RESEARCH: A CONCEPTUAL PRIMER."
Abstract: The practice of computing correlations between difference or discrepancy scores and an outcome variable is common in many areas of social science. Relationship researchers most commonly use difference scores to index the (dis)similarity of members of two_person relationships. Using an intuitive, graphical approach and avoiding formulas and pointing fingers, we illustrate problems with using difference score correlations in relationship research, suggest ways to ensure that difference score correlations are maximally informative, and briefly review alternatives to difference score correlations in studying similarity, accuracy, and related constructs.

------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------

"Gonzalez and Griffin also focus their attention on INTERDEPENDENT DYADIC DATA. Their article spotlights two ways of modeling correlations between couple members when the DYAD MEMBERS ARE DISTINGUISHABLE. First they discuss estimation of the overall WITHIN_PARTNER correlation (which is analogous to Kenny and Cook's actor effect) and the overall CROSS_PARTNER correlation (analogous to the partner effect) using both a PAIRWISE APPROACH and a STRUCTURAL EQUATION MODELING APPROACH. They then describe how these overall correlations can be decomposed into dyad_level effects and individual_level effects. The dyad_level effects address whether dyad members are similar to one another on two variables, and whether the degree of similarity between dyad members on one variable relates to the degree of similarity between them on the second variable. The individual_level correlation addresses whether, after taking into account the dyad's standing on the two variables, an individual's score on one variable relates to that person's score on the second variable."
http://www.blackwell-synergy.com/doi/abs/10.1111/j.1475-6811.1999.tb00203.x

"THE CORRELATIONAL ANALYSIS OF DYAD_LEVEL DATA IN THE DISTINGUISHABLE CASE. "
Abstract: Many theories of interpersonal relationships distinguish between individual_level processes and dyadic or group_level processes. This suggests that two_person relationships should be studied at the level of the dyad as well as at the level of the individual. We discuss correlational methods for dyads when each dyad contains two different types of individuals (e.g., a husband and wife, a mother and child, or an expert and a novice). In such dyadic interaction designs, the dyad members are said to be distinguishable. We present a method for computing the OVERALL CORRELATION FOR DISTINGUISHABLE DYADS, and we discuss a model for separating the dyad_level and individual_level components of such a correlation. The computational techniques and their interpretation are described using data from 98 heterosexual couples.

------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------

"Kenny and Cook present a detailed discussion of partner effects in dyadic research. Partner effects are one way of conceptualizing the interdependence that exists within dyads in that they occur when the characteristics of an individual affect the outcomes of his or her relationship partner. For example, not only may a person's attachment style affect his or her own relationship satisfaction (an actor effect) but that person's attachment style may also affect his or her partner's satisfaction (a partner effect). These investigators describe FOUR MODELS IN WHICH ACTOR AND PARTNER EFFECTS MAY PLAY DIFFERING ROLES IN DYADIC RELATIONSHIPS, and they also discuss how these two effects may interact with one another. After discussing partner effects at a conceptual level, the authors present an overview of several methods that can be used to estimate partner effects in dyadic research, giving considerable attention to the use of MULTILEVEL MODELING AS AN ESTIMATION METHOD."

http://www.blackwell-synergy.com/doi/abs/10.1111/j.1475-6811.1999.tb00202.x

"PARTNER EFFECTS IN RELATIONSHIP RESEARCH: CONCEPTUAL ISSUES, ANALYTIC DIFFICULTIES, AND ILLUSTRATIONS. "
Abstract: This article discusses the conceptual meaning of partner effects, which occur when one person is affected by the behavior or characteristics of his or her partner. We show that partner effects can be used to validate the presence of a relationship and can elaborate the particular nature of that relationship. We discuss possible moderation of partner effects and show that many theoretical variables in relationship research (e.g. SIMILARITY) can be viewed as the interactions of partner effects with other variables. We present three extended examples that illustrate the importance of partner effects.

------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------ ------
"METHODOLOGICAL AND DATA ANALYTIC ADVANCES IN THE STUDY OF INTERPERSONAL RELATIONSHIPS: INTRODUCTION TO THE SPECIAL ISSUE"

http://www.blackwell-synergy.com/doi/abs/10.1111/j.1475-6811.1999.tb00200.x

At page 413 says: "It is vital for the study of personal relationships, as for any scientific discipline, to develop methodologies that are specifically designed to address the questions posed by the discipline. The articles in this special issue represent an effort in that direction. Perhaps equally important is the need for individuals who are involved in relationships study to learn these new techniques and to apply them in their research. It is also important for investigators to challenge statisticians to create new analytic techniques when existing ones are inadequate. These tasks are left to you, the reader."

Latest Research

Latest Research in Theories of Romantic Relationships Development outlines: compatibility is all about a high level on personality similarity between prospective mates for long term mating with commitment.

Chapter 11 of the Book "Strangers in a strange lab: How personality shapes our initial encounters with others" (Oxford University Press, 2009) written by Dr. William Ickes

" ... In summary, birds of a feather (couples with similar personalities) are not only more likely to flock together (that is, to select each other as marriage partners), but are also more satisfied with their relationships to the extent that they are globally similar. ... Although odd couples (those with globally mismatched personalities) may occasionally find each other and form committed relationships as well, the statistical odds of these odd couples being satisfied with each other tend to work against them. In contrast, the statistical odds for the success of committed relationships involving not-so-odd couples (those with globally similar personalities) are substantially better" page 25

" .... highly similar couples will probably always have an advantage over the odder, highly dissimilar ones. That doesn't mean that you can't win against long odds, but it does mean that it's a real gamble trying to make things work with a person you're just too different from." page 26

PAPERS

#1 Charania & Ickes (2009) paper: "Personality influences on marital satisfaction: Integrating the empirical evidence using the Actor-Partner Interdependence Model (APIM) model"

"... substantial level of inter-partner personality similarity for seven of the thirteen personality traits studied, with four of the similarity correlations exceeding 0.38 ..."

#2 Rammstedt & Schupp (2008) paper: "Only the congruent survive - Personality similarities in couples. Personality and Individual Differences"

".... Results reveal that among the Big Five dimensions, there are strong differences in spouses' congruences. While for Extraversion and Emotional Stability, congruence is close to zero, correlations averaging at 0.30 are found for Agreeableness, Conscientiousness, and Openness."

Dr. Ickes' opinion about this paper:"I think a closer look will reveal that couples involving one high and one low conscientious partner tend to be dissatisfied because the conscientious partner feels that he or she has to 'take care of' the low conscientious partner. Couples involving one partner who is open to experience and one partner who is closed to experience will also tend to be dissatisfied because their political views and leisure time preferences are likely to diverge, and because the more 'adventurous' partner is likely to find the other partner somewhat boring. In initial interactions, an agreeable partner is able to compensate for the faults of a disagreeable partner, so that the interaction proceeds reasonably well. Having to constantly compensate for a disagreeable partner over a long period of time is a different proposition, however, and I can well imagine that the agreeable partner eventually gets disaffected and dissatisfied with having to do that so much."

#3 Barelds & Dijkstra (2008) paper: "Do People Know What They Want: A Similar or Complementary Partner?"

"In The Netherlands, where this study was conducted, almost 40% of the divorcees report mismatches in personalities as the major cause of their break-up (De Graaf, 2006; Amato and Previti, 2003). .... although several studies have revealed similarities between partners in their personalities (e.g., Buss, 1984; McCrae, Martin, Hrebícková, Urbánek, Boomsma et al., 2008) only few studies have investigated the extent to which similarity in personality leads to romantic attraction (Barelds and Dijkstra, 2007). From their finding that couples across age groups show the same partner similarities (McCrae et al. 2008) conclude that mate selection, rather than convergence over time, accounts for personality similarity among partners." "Finally, the present study explored a recent issue uncovered by Eastwick and Finkel 2008; also Kurzban and Weeden, 2007; Todd, Penke, Fasolo, and Lenton, 2007 who found that people often report partner preferences that are not compatible with their choices in real life."

#4 McCrae, Martin, Hrebícková, Urbánek, Boomsma et al. (2008) paper: "Personality Trait Similarity Between Spouses in Four Cultures"

"... Most assortment effects were small, but correlations exceeding 0.40 were seen for a subset of traits, chiefly from the Openness and Agreeableness domains. ... This suggested that mate selection, rather than convergence over time, accounted for similarity"

#5 Barelds & Dijkstra (2007) paper: "Love at first sight or friends first? Ties among partner personality trait similarity, relationship onset, relationship quality, and love"

"... partner personality trait similarity was related to relationship quality as a function of both relationship onset and specific personality traits. "

#6 Gonzaga, Campos & Bradbury (2007) paper: "Similarity, convergence, and relationship satisfaction in dating and married couples."

#7 Figueredo, Sefcek & Jones (2006) paper: "The ideal romantic partner personality "

"... Individuals sought mates that were matches of themselves to some degree (a concept that we termed aspirational positive assortative mating) but also sought mates that were somewhat higher in Conscientiousness, Extraversion, Agreeableness, and Mate Value, but lower in Neuroticism than themselves."

#8 Bekkers, van Aken & Denissen (2006) paper: "Social Structure and Personality Assortment Among Married Couples"

"... Personality characteristics like agreeableness and neuroticism are good predictors of marital conflicts and ultimately of union dissolution, even across different relationships (Robins, Caspi & Moffitt, 2002). .... In sum: spouses with higher levels of neuroticism and openness, spouses with lower levels of agreeableness, and couples with more dissimilar personalities at the time of marriage are more likely to divorce."

#9 Gaunt (2006) paper:"Couple similarity and marital satisfaction: Are similar spouses happier?"

#10 Amodio & Showers (2005) paper: "Similarity breeds liking revisited: The moderating role of commitment"

While opposites attract for short term affairs, similarity is preferred for marriage.

#11 What is important in attracting people to one another may not be important in making couples happy, as stated in the Klohnen & Luo 2005 paper "ASSORTATIVE MATING AND MARITAL QUALITY IN NEWLYWEDS: A COUPLE CENTERED APPROACH", February 2005 at "Journal of Personality and Social Psychology"

"........People may be attracted to those who have similar attitudes, values, and beliefs and even marry them (at least in part) on the basis of this similarity. However, once individuals are in a committed relationship, IT MAY BE PRIMARILY PERSONALITY SIMILARITY THAT INFLUENCES MARITAL HAPPINESS. ...."

Although none of the above papers use the 16PF normative personality test (they mostly use different versions of the normative Big5 personality test instead) and linear or logistic multivariate regression equations to calculate similarity, they clearly show a connection between personality similarity and marital happiness / dyadic success (stability and satisfaction) for some persons.

*Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.

Three words in compatibility matching methods.

Three words with different meanings for different persons or companies!

Compatibility Personality Similarity

Sometimes the word compatibility means a high degree of similarity between several variables (religion, education, income, personality, likes and dislikes, etc.) of prospective mates; sometimes compatibility means a mix of similarity and complementarity between variables; sometimes when a dating site says compatibility or even chemistry, nobody really knows exactly what it means!

Some online dating sites offering compatibility matching methods use the word similarity as: "a proprietary Dyadic Adjustment Scale", others mean: "a proprietary multivariate linear regression equation", some say a mix of similarity and complementarity meaning: "a proprietary multivariate logistic regression equation", still others mix similarity and complementarity meaning: "a proprietary equation to calculate compatibility between prospective mates!"

Personality could be assessed by different methods.
No actual online dating site offering compatibility matching methods uses the 16PF5 normative test available in different languages, the 5th version actualized after Census 2000.

Guide to review

Guide to review online dating sites offering compatibility matching methods :

-----A) TEST

A.1) Brain behind the test.

A.2) test? proprietary or commercial / ipsative or normative / validation / reliability, etc



-----B) MATCHING ALGORITHM

B.1) Brain behind matching algorithm.

B.2) the ENSEMBLE (the whole set of different valid possibilities)

B.3) About compatibility.
If compatibility means a high degree of similarity between several variables (religion, education, income, personality, personal preferences, likes and dislikes, etc.) between prospective matesORif compatibility means a mix of similarity and complementarity between variablesORWhat does exactly compatibility mean?

B.4) What does exactly similarity mean? and What does exactly complementarity mean?

B.5) How exactly the compatibility matching method works, specifying main matching equation/ formula (without revealing proprietary information).
E.g.:
"a proprietary Dyadic Adjustment Scale"
"a proprietary multivariate linear regression equation"
"a proprietary multivariate logistic regression equation"
"an adapted quantum mechanics math equation"

B.6) How compatibility results are displayed
E.g.:
* only a number: like 110 (Cybersuitors), 96% (PlentyofFish Chemistry Predictor), 65 (Parship), 92.55033557% +/- 0.00000001% (LPM), etc.
* only a graphic system: like a set of up to five empty/half_full/full hearts icon; a set of up to ten empty/half_full/full squares, a set of semaphores, etc.
* a written report like ThomasKnowsPeople.

B.7) Average number of "compatible real persons" for one person over the entire database.
E.g.:
* 3 or 4 persons high compatible per 1,000 persons
* 3 most compatible persons in a 100,000 persons database,


-----C) DIVORCE RATES
C.1) "Divorce rates" of the couples matched by the compatibility matching method after 1 year, 2 years, 5 years, 10 years.


-----D) peer_reviewed Scientifc Paper
Peer_reviewed Scientifc Paper showing the compatibility matching method matches persons who will have more stable and satisfying relationships than couples matched by chance, astrological destiny, personal preferences, searching on one's own, or other typical type of compatibility test (like Wilson & Cousins) as the control group; with low 'divorce rates' (e.g. after 2, 5, 10 years of 'marriage').