Thursday, 10 August 2017

Comparisons of Modeling Approaches for Evaluating the Longitudinal Association in a Clustered Healthcare Intervention Study


biostatistics open access journals
This paper addresses methodology issues related to evidence-based healthcare research, specifically when evaluating and analyzing the hospital practice environments (HPE) impacts on the patient health outcomes are conducted in longitudinal intervention survey studies. HPE include the spatially clustered hospital characteristics, including practice environment scale (PES) measures, hospital facilities, nursing staffing and nursing attributes. The longitudinal associations between HPE and patient smoking cessation counseling (SCC) activities, and patient heart failure (HF) outcomes are examined. Various longitudinal and hierarchical modeling are compared including linear mixed models with restricted maximum likelihood estimation, generalized estimating equations with quasi-likelihood estimation, hierarchical linear regression models with nonparametric generalized least squares estimations, and repeated ANOVA.


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