6 | 187 Acknowledgements (Dankwoord) Table C2 The effects of (starting to) work on the number of sports and sport frequency; Complete results MAJOR LIFE EVENTSd Educational domain Not in full-time education vs. in full-time educatione Leaving full-time educationf Employment domain Working vs. not working (>32 hours a week)e Beginning work (>32 hours a week)f Relationship domain In a relationship vs. singlee Entering an intimate relationshipf Civil/marital domain Cohabiting/married vs. not cohabiting/not marriede Starting to cohabit/getting marriedf Parental domain Parent vs. non-parente Becoming a parentf CONTROLS Female Immigrant Age Age: Being oldere Aging: Getting olderf Interceptg Log likelihood Wald chi-square 0.599 0.891 0.758 0.871 0.996 0.997 4.072 -8143.681 406.830 0.000*** 0.049* 0.000*** 0.000*** 0.060+ 0.494 0.000*** - 0.000*** Exp(B) Number of sportsa sig.c 0.550 0.819 0.780 0.843 0.998 1.010 7.723 -11873.624 221.690 0.000*** 0.003** 0.000*** 0.000*** 0.501 0.066+ 0.000*** - 0.000*** Exp(B) Sport frequencyb sig.c Source: NELLS wave 1 (2009) and wave 2 (2013); N=2317 aMixed-effects Poisson regression analyses bMixed-effects negative binomial regression analyses c+p<0.10; *p<0.05; **p<0.01; ***p<0.001 (two-tailed) dWe examined the influence of each event in a separate analysis (see tables C1 to C5), in which we controlled for gender, migration background, age (between-person differences), and aging (withinperson changes). We present the merged results from these separate analyses regarding the effects of the life events in chapter 4; see table 4.2) eBetween variable: Exp(B) = estimate of the between-person effect of the event, thus reflecting interpersonal differences fWithin variable: Exp(B) = estimate of the within-person effect of the event, thus reflecting changes within individuals gPresented estimates for the intercepts are B’s instead of Exp(B)’s. Appendix