Personal resources, family factors, and remarriage: an analysis based on CFPS2010 data

The Journal of Chinese Sociology

Table 2 The ML estimation of interaction coefficient in personal resources and gender (N = 1033)

Variable	Model 3	Model 4	Model 5	Model 6
Gender^a	−.29** (.11)	−.53** (.22)	−1.25*** (.23)	−.51*** (.14)
Work^b.	.20* (.10)	.16** (.08)	.16** (.08)	.16** (.08)
Log income	−.00 (.01)	−.01⁺ (.00)	−.00 (.01)	−.00 (.00)
Housing conditions	.06* (.03)	.06* (.03)	−.06* (.03)	.06* (.03)
Compulsory education^c	−.16* (.09)	−.15 (.09)	−.12 (.09)	−.20 (.12)
Secondary education	−.24* (.13)	−.24** (.03)	−.21⁺ (.03)	−.47** (.17)
Higher education	−.32* (.17)	−.29** (.17)	−.25 (.17)	−.82** (.26)
Gender × work	−.08 (.14)
Gender × income		.03 (.03)
Gender × compulsory education				.11 (.17)
Gender × secondary education				.46** (.23)
Gender × higher education				.95** (.32)
Gender × housing condition			.22*** (.05)
Log likelihood	−3539	−3539	−3532	−3535
Chi-square statistic	320.2	319.6	333.9	333.7

Due to space limitations, only variables involved in the analysis of interactions are listed in the table. Other variables include registered permanent residence, region, nationality, age, family size, whether or not respondent’s parents are still alive, size of social network of relatives, whether or not the respondent belongs to a clan, and whether or not they have minor children
⁺Means p < 0.1, *means p < 0.05, **means p < 0.01, ***means p < 0.001(two-tailed test)
^aFemales as the reference category. ^bNonagricultural jobs as the reference category. ^cNo formal education as the reference category