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472 A. Reichel, J. Brandl and W. Mayrhofer<br />

Table 3<br />

Hierarchical linear regression<br />

Model 1 Model 2 Model 3 Model 4<br />

Intercept 1.31 (.050)*** 1.10 (.067)*** 1.14 (.092)*** 1.38 (.720)<br />

Control variables and functional attributes<br />

Company size .000 (.000) .000 (.000) .000 (.000)<br />

Relative size of HR department .083 (.355) –.096 (.361) –.040 (.375)<br />

Proportion of women in workforce .000 (.001) .000 (.001) .000 (.001)<br />

Difference between proportion of women in HR department and in company –.002 (.001)** –.001 (.0005)+ –.001 (.001)+<br />

Experience .009 (.002)*** .008 (.002)*** .009 (.002)***<br />

Education .213 (.033)*** .208 (.033)*** .212 (.035)***<br />

Gender composition<br />

Sex of HR director –.069 (.038)+ –.097 (.042)*<br />

Proportion of women in HR department –.001 (.001) –.001 (.001)<br />

Country effects<br />

Enabling social policies .354 (.089)**<br />

Proportion of female workforce in HRM –.007 (.012)<br />

Proportion of HR departments led by women –.001 (.006)<br />

Deviance 5559.473 3879.103 3854.915 3205.406<br />

AIC 5565.473<br />

3897.103 3876.915 3233.406<br />

Difference in deviance 1680.370*** (df = 6) 24.188*** (df = 2) 649.509*** (df = 3)<br />

ICC .139<br />

.147 .147 .044<br />

Variability between companies .422 (.011) .396 (.013) .394 (.013) .400 (.014)<br />

Variability between countries .068 (.020) .068 (.020) .068 (.020) .018 (.009)<br />

Note: + p < .10, * p < .05, ** p < .01, *** p < .001.

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