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Multilevel mixed effects linear regression will be used to evaluate change on the outcome measures.
Multilevel mixed effects regression models will be applied to test for intervention effects.
Multilevel mixed effects multiple linear regression models were used to quantify the effect of incentive withdrawal.
Multilevel mixed effects regression models will be applied to test the effect of the intervention.
Multilevel mixed effects models provide a natural decomposition of observed variance into within- and between-subject variance and noise variance.
Multilevel mixed effects logistic regression models were constructed to account for the within-subject correlation between four time points.
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Multilevel mixed-effects models were used to analyse the rate of CD4+ T-cell decline.
A multilevel, mixed-effects linear regression model with state as a fixed effect and nested random effects for LGA and ward was then constructed.
We use a multilevel mixed-effects logistic regression model to estimate the effect of job accessibility on the likelihood of being informally employed, controlling for individual and other area characteristics.
Change over time was analysed using a multilevel mixed-effects model for both linear and logistic regressions.
Statistical tests were conducted by generating a generalized multilevel mixed-effects model of raw data, according to a Bernoulli distribution, in R (www.r-project.org).org
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