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Therefore the models' variables, assumptions and the underlying data sources are described.
Table 4 HLM results of the fixed and random effects of the final models Variables Indonesia Malaysia Thailand Coef.
In all models, variables representing more extreme intervention and/or removal of the victim and/or perpetrator from the home (foster care or criminal court involvement) were negatively associated with the risk of becoming a case.
Correlations between regional brain volume changes, histology and motor behaviour across time were evaluated for all subjects (both saline controls and lactacystin-lesioned animals) using linear multiple regression models (variables entered) or a Pearson's correlation, as appropriate.
Backward elimination with a p-value set to 0.1 was used to determine which variables were included in the multivariate model.In the multivariate logistic regression models, variables that were significantly (p<0.05) or moderately significantly (p<0.1) associated with HIV status were reported by presenting adjusted odds ratios (aOR) with 95% confidence intervals.
In the logistic regression models, variables were aggregated.
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Table 1 Description of modeling variables.
Further exploration of model variables is warranted.
Table 2 provides descriptive statistics for model variables.
The constraints below are binary requirements for the model variables.
The last three constraints determine model variables signs.
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