GZ managed the DHS datasets, ran the econometric models for unconditional quantile regressions and counterfactual decompositions and contributed to the interpretation of results.
The fixed-effects regression model for the unconditional lagged relation is given by begin{aligned} tilde{R}_{i,t}=sum _{k=1}^K beta _k^u tilde{I}_{i,t-k}+tilde{epsilon }_{i,t}^u, end{aligned} (6 with analogous definitions.
The regression model for the unconditional relation is given by begin{aligned} tilde{R}_{i,t}=sum _{k=1}^K beta _k^u tilde{I}_{i,t-k}+ sum _{k=1}^K gamma _k^{lu} tilde{S}_{i,t-k}+ sum _{k=1}^K delta _k^{lu} tilde{S}_{i,t-k} cdot tilde{I}_{i,t-k}+ tilde{epsilon }_{i,t}^{u}, end{aligned} (11 with analogous definitions.
The best fitting unconditional model for alcohol use included a fixed quadratic time effect, and a random linear intercept and slope with heteroscedastic residual error variance (Table 2).
We generalized this procedure by fitting an unconditional growth model for each of the Emotion Awareness scales and extracting the slopes for each child.
For each regression model, the unconditional relations of the independent variables with research use were tested using one-way Anova.
Therefore, we employed the negative binomial model for the LOS variable because the unconditional variances of this variable were larger than the unconditional means.
The association between each genetic variant and disease risk was estimated by the odds ratio (OR) and 95% confidence interval (CI) per allele, assuming a log-additive genetic model using unconditional logistic regression adjusting for age at recruitment and study design (CIS vs. invasive carcinoma) in 961 cervical cancer patients and 1725 controls.
Using the selected covariates, we constructed a multivariate unconditional logistic regression model for risk of TB.
