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We intended to evaluate the variety of candidate determinants used in models of self-reported health (SRH) and to examine the methodological problems encountered in multivariate models used in recent studies in this field.
Multivariate models used the backward selection technique and an alpha of 0.50 [18].
Multivariate models used multiple logistic regression.
Residual diagnostics were performed for the multilevel multivariate models used in the analysis via plots of residual values for both the fixed and random effects.
All differences in baseline characteristics between the cohorts were accounted for in the multivariate models used to compare adherence and persistence as measured by the PDC.
Table 3 gives the results of the adjusted (multivariate) models used to describe the blood levels of DDE, total PCBs, and dieldrin in the Washington County study population.
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Predictive variables with some association with vaccination (p<0.05) were tested in multivariate models using forward stepwise multivariable logistic regression and the likelihood ratio method.
We report results from the multivariate models using odds ratios, OR (95% confidence intervals, 95% CI).
All non-binary variables were added to multivariate models using indicator variables.
The results presented are predicted values based on multivariate models using all measured metabolites.
Three multivariate models using different covariates to describe access to facilities were explored.
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