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The use of multilevel models corrects this by modelling the correlation between the control sets.
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Given the small number of higher-order units (seven countries or 13 cities), we refrain from estimating multilevel models, but correct for intragroup correlations at the country level by using robust standard errors.
Multilevel models also corrected for biases in parameter estimates and standard errors by adjusting intra-group correlations due to within-division clustering of the data (Guo and Zhao 2000; Rabe-Hesketh and Skrondal 2008).
A multilevel model (to correct for correlation between measurements) with a link function (as cost-data will not be normally distributed) is used to obtain parameter estimates, likelihood and p-values for the costs and effects.
15 The second reason to use a multilevel model is to correct the sample size due to matched cohort design.
Therefore, a random intercept was added to the multilevel models with group (depressed or non-depressed) as the central determinant to correct for clustering of patients within GPs.
brms: an R Package for Bayesian Multilevel Models Using Stan.
brms: an R package for Bayesian multilevel models Using Stan.
brms: an R package for Bayesian multilevel models using Stan.
Data were analyzed with linear multilevel models.
Kenny, D. A., Korchmaros, J. D. & Bolger, N. Lower level mediation in multilevel models.
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