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Full entry and stepwise regression analyses were computed.
Table 5 shows the results of forced entry and stepwise multivariate linear regression analysis of the participants' characteristics and mental health status.
One finding from these final models of stepwise regression analysis was that female gender was associated with reporting higher scores on the HSCL-37A in both forced entry and stepwise models.
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Significantly correlated variables (p < 0.05) including maternal leptin measured in early and late pregnancy (which may have influenced cord leptin levels) were subsequently analysed by simple linear regression, with each anthropometric measure as the dependent variable, and then imputed into multiple linear regression models using a combination of forced entry and backwards stepwise procedures.
In model 1, the FIM + FAM total admission score, and NIS physical and cognitive scores on admission all met the criteria for entry and were entered stepwise into the prediction model.
Only variables with significant P-values from the univariate analyses were entered into the multivariate analysis, using the Cox proportional hazards model (backward stepwise, probability for stepwise entry, and removal set at 0.05 and 0.10).
A gradual and stepwise entry or comeback into the labour market would therefore be more realistic for many in this group.
All significant variables from the univariate analyses were entered into the multivariate analyses in a backward stepwise Cox regression analysis with a probability for stepwise entry and removal at 0.05 and 0.10, respectively.
Probability for stepwise entry and removal was set at 0.05 and 0.10, respectively.
Probability for stepwise entry and removal were 0.2 and 0.4.
Probability for stepwise entry and removal was set at.05 and.10, respectively.
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