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We used multivariable generalized linear model (GLM) regression analysis with a log link to estimate the adjusted RR of the independent variables on perinatal mortality.
Multivariable generalized linear regression models were used to derive estimates of relative risks (RRs) and 95% CIs.
The effect of surgical diagnosis group on EQ-us/EQ-VAS was assessed by multivariable generalized linear regression analysis.
We did account for priority group and admitting hospital in our multivariable, generalized linear mixed-effect models.
Explanatory variables with a significant effect on treatment delay were entered into a multivariable generalized linear model.
Variables with a significant association with treatment delay in univariate models were added to a multivariable generalized linear model.
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Multivariable general linear models were performed for data analyses.
This was tested using a multivariable, general linear model (multivariable GLM).
Univariate and multivariable regression analyses (generalized linear models) were used, with detectable HIV RNA at delivery as dependent variable.
Descriptive and multivariable analysis using generalized linear mixed models (GLMM) were used to examine the patterns of dental procedures provided to children.
Then for all observations, we examined the relationship in age-adjusted models and multivariable models using generalized linear mixed models (with logit link) for dichotomized biomarkers (as described below) and with mixed-effects models for continuous biomarkers.
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