Gender-specific preference in online dating

EPJ Data Science

Table 3 Logistic regression results for male users sending messages to female users

Variables	Model 1		Model 2		Model 3
Variables	b	SE	b	SE	b	SE
Intercept	−4.800^∗∗∗	0.008	−4.732^∗∗∗	0.008	−4.973^∗∗∗	0.009
MobileF	0.007	0.007			0.022^∗∗	0.007
HouseF	−0.021^∗∗	0.007			−0.015^∗	0.007
AutoF	0.037^∗∗∗	0.006			0.038^∗∗∗	0.006
LevelF	−0.013	0.007			0.012	0.007
Pop1F	0.468^∗∗∗	0.004			0.462^∗∗∗	0.004
Pop2F	0.023^∗∗∗	0.003			0.022^∗∗∗	0.003
Pop3F	0.126^∗∗∗	0.003			0.141^∗∗∗	0.003
OutdegreeF	−0.004	0.008			0.000	0.008
MobileM			−0.146^∗∗∗	0.007	−0.147^∗∗∗	0.007
HouseM			−0.062^∗∗∗	0.008	−0.071^∗∗∗	0.008
AutoM			−0.100^∗∗∗	0.008	−0.107^∗∗∗	0.008
LevelM			−0.195^∗∗∗	0.009	−0.197^∗∗∗	0.009
Pop1M			−0.036^∗∗∗	0.009	−0.044^∗∗∗	0.009
Pop2M			−0.026^∗	0.012	−0.026^∗	0.012
Pop3M			−0.196^∗∗∗	0.013	−0.215^∗∗∗	0.014
OutdegreeM			0.338^∗∗∗	0.003	0.335^∗∗∗	0.004
CompatFM					−0.013	0.007
CompatMF					0.062^∗∗∗	0.008
AIC	219,384		227,215		210,184
N	2,066,668		2,066,668		2,066,668