Gender-specific preference in online dating

EPJ Data Science

Table 2 Logistic regression results for female users sending messages to male users

Variables	Model 1		Model 2		Model 3
Variables	b	SE	b	SE	b	SE
Intercept	−5.322^∗∗∗	0.014	−5.548^∗∗∗	0.016	−5.640^∗∗∗	0.017
MobileF	−0.092^∗∗∗	0.014			−0.090^∗∗∗	0.014
HouseF	0.061^∗∗∗	0.014			0.038^∗∗	0.014
AutoF	−0.118^∗∗∗	0.016			−0.116^∗∗∗	0.016
LevelF	−0.059^∗∗∗	0.014			−0.072^∗∗∗	0.014
Pop1F	−0.162^∗∗∗	0.018			−0.167^∗∗∗	0.018
Pop2F	0.016	0.014			0.012	0.014
Pop3F	−0.110^∗∗∗	0.021			−0.121^∗∗∗	0.021
OutdegreeF	0.209^∗∗∗	0.005			0.211^∗∗∗	0.006
MobileM			0.015	0.014	0.025	0.014
HouseM			0.238^∗∗∗	0.015	0.243^∗∗∗	0.015
AutoM			0.153^∗∗∗	0.013	0.157^∗∗∗	0.013
LevelM			0.016	0.013	0.029^∗	0.013
Pop1M			0.393^∗∗∗	0.007	0.390^∗∗∗	0.007
Pop2M			0.053^∗∗∗	0.004	0.051^∗∗∗	0.004
Pop3M			0.142^∗∗∗	0.006	0.146^∗∗∗	0.006
OutdegreeM			0.028^∗∗	0.011	0.029^∗∗	0.011
CompatFM					0.057^∗∗∗	0.014
CompatMF					0.061^∗∗∗	0.014
AIC	72,160		67,462		65,958
N	1,115,363		1,115,363		1,115,363