Looking for Love in London?

Great post Dr. Houran!!!!
I had read your new article and also I agree with your previous paper “Do Online Matchmaking Tests Work? An Assessment of Preliminary Evidence for a Publicized -Predictive Model of Marital Success-” 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…. ” although I think Rasch scaling methodologies could be the correct way to MEASURE but not the correct way to COMPARE results.
Serious OnLine Dating Sites and their Big Databases are NEW sources for scientific research. New Knowledge is waiting to be discovered inside these Big Databases!!! Sooner I will research in a collaborative environment and try to prove these possible FUTURE TRENDS / NEW DISCOVERIES on Theories of Romantic Relationships Development.
• Homophily dominates human attraction but “It seems that what is important in attracting people to one another may not be important in making couples happy.” Also conclusions from scientific papers obtained using small samples (small scale of researching) seems to not be valid with real world (large scale of researching), e.g. Big Databases of (actual and future/to_be_launched_soon) Serious OnLine Dating Sites == big samples == more than 100,000 persons involved.
• Temporal patterns of relationship variables: combination of physique, personality, intelligence, social background, attitudes, habits and leisure preferences may indeed play a significant role between mates / prospective mates:
Early stage of temporal patterns: a combination of high level of infatuation, fantasy, passion, physical attraction between prospective mates.
Middle stage of temporal patterns: a considerable degree of similarity on social background, attitudes, habits and leisure preferences between mates.
Last stage of temporal patterns: If only high level on personality similarity between mates / couples could be the core of relationship stability and satisfaction == Dyadic Success.
• Complex mental processes (successful relationships based on a mental set arrangement) could be only exceptions for “couples by convenience” and not for “romantic couples” i.e. old rich man with young pretty lady.
• Longitudinal approach will be “a must” in any research, and cross-sectional research must be discarded because does not take into account temporal patterns of relationship variables.
• Big-5 (like N, E, O, A, C; Costa & McCrae) will not be enough any more to evaluate Couple Similarity between prospective mates; and the complete inventory, 16PF5 test or similar like IPIP-NEO, must be used.
————————————————————
The concept of COMPATIBILITY does not make sense by itself, but the concept: PROBABILITY OF BEING COMPATIBLE could be measured with high precision using well-known personality tests, and applied in a predictive model of Dyadic Success: Stability and Satisfaction.
DYADIC COMPARISON using the method I had invented.
Dyadic comparison between person #X and person #Y is given from the following formula, derived from an advanced math equation:
/ #X | means client #X’s 16PF5 Report
| #Y \ means client #Y’s 16PF5 Report
| CQ | means Comparison Operator
/#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) 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, K02, K03, K04, K05, K06, K07, K08, K09, K10, K11, K12, K13, K14, K15, K16 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 are proprietary information)
Here an example
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%
What is Dyadic Success?
Stability and Satisfaction; i.e. perhaps PROBABILITY OF BEING COMPATIBLE over 90.00000000%
I applied the method to 16PF5 test in first instance, but the method does not depend only on 16PF5 tests’ results, could be used also with the IPIP-NEO test.
Kindest Regards,
Fernando Ardenghi.
Buenos Aires.
Argentina.
ardenghifer@gmail.com

2 thoughts on “Looking for Love in London?”

James Houran says:

January 27, 2006 at 2:50 pm

Hmmm… seems that SnogLondon is attempting a form of pseudo “compatibility testing” with this approach. I imagine customers find it fun and perhaps even addictive!
However, these types of questions and quizzes should not be confused with evidence-based compatibility tests. Please see my new article on this at:
http://www.onlinedatingmagazine.com/features/compatibilitytesting.html
Thanks,
James Houran, PhD
Research Psychologist

Fernando Ardenghi says:

January 28, 2006 at 2:34 am

Great post Dr. Houran!!!!
I had read your new article and also I agree with your previous paper “Do Online Matchmaking Tests Work? An Assessment of Preliminary Evidence for a Publicized -Predictive Model of Marital Success-” 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…. ” although I think Rasch scaling methodologies could be the correct way to MEASURE but not the correct way to COMPARE results.
Serious OnLine Dating Sites and their Big Databases are NEW sources for scientific research. New Knowledge is waiting to be discovered inside these Big Databases!!! Sooner I will research in a collaborative environment and try to prove these possible FUTURE TRENDS / NEW DISCOVERIES on Theories of Romantic Relationships Development.
• Homophily dominates human attraction but “It seems that what is important in attracting people to one another may not be important in making couples happy.” Also conclusions from scientific papers obtained using small samples (small scale of researching) seems to not be valid with real world (large scale of researching), e.g. Big Databases of (actual and future/to_be_launched_soon) Serious OnLine Dating Sites == big samples == more than 100,000 persons involved.
• Temporal patterns of relationship variables: combination of physique, personality, intelligence, social background, attitudes, habits and leisure preferences may indeed play a significant role between mates / prospective mates:
Early stage of temporal patterns: a combination of high level of infatuation, fantasy, passion, physical attraction between prospective mates.
Middle stage of temporal patterns: a considerable degree of similarity on social background, attitudes, habits and leisure preferences between mates.
Last stage of temporal patterns: If only high level on personality similarity between mates / couples could be the core of relationship stability and satisfaction == Dyadic Success.
• Complex mental processes (successful relationships based on a mental set arrangement) could be only exceptions for “couples by convenience” and not for “romantic couples” i.e. old rich man with young pretty lady.
• Longitudinal approach will be “a must” in any research, and cross-sectional research must be discarded because does not take into account temporal patterns of relationship variables.
• Big-5 (like N, E, O, A, C; Costa & McCrae) will not be enough any more to evaluate Couple Similarity between prospective mates; and the complete inventory, 16PF5 test or similar like IPIP-NEO, must be used.
————————————————————
The concept of COMPATIBILITY does not make sense by itself, but the concept: PROBABILITY OF BEING COMPATIBLE could be measured with high precision using well-known personality tests, and applied in a predictive model of Dyadic Success: Stability and Satisfaction.
DYADIC COMPARISON using the method I had invented.
Dyadic comparison between person #X and person #Y is given from the following formula, derived from an advanced math equation:
/ #X | means client #X’s 16PF5 Report
| #Y \ means client #Y’s 16PF5 Report
| CQ | means Comparison Operator
/#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) 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, K02, K03, K04, K05, K06, K07, K08, K09, K10, K11, K12, K13, K14, K15, K16 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 are proprietary information)
Here an example
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%
What is Dyadic Success?
Stability and Satisfaction; i.e. perhaps PROBABILITY OF BEING COMPATIBLE over 90.00000000%
I applied the method to 16PF5 test in first instance, but the method does not depend only on 16PF5 tests’ results, could be used also with the IPIP-NEO test.
Kindest Regards,
Fernando Ardenghi.
Buenos Aires.
Argentina.
ardenghifer@gmail.com

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