TY - JOUR
T1 - Handling intra-cluster correlation when analyzing the effects of decision support on health care process measures
AU - Peek, Niels
AU - Goud, Rick
AU - de Keizer, Nicolette
PY - 2013
Y1 - 2013
N2 - The clinical worksite constitutes a naturally clustered environment, posing challenges in the statistical analysis of quality improvement interventions such as computerized decision support. Ignoring clustering in the analysis may lead to biased effect estimates, underestimating the variance and hence type I errors. This paper presents a secondary analysis on data from a previously published, cluster randomized trial in cardiac rehabilitation. We compared six different statistical analysis methods (weighted and unweighted t-test; adjusted χ2 test; normal and multilevel logistic regression analysis; and generalized estimation equations). There were considerable differences in both point estimates and p-values derived by the methods, and differences were larger with increasing intracluster correlation
AB - The clinical worksite constitutes a naturally clustered environment, posing challenges in the statistical analysis of quality improvement interventions such as computerized decision support. Ignoring clustering in the analysis may lead to biased effect estimates, underestimating the variance and hence type I errors. This paper presents a secondary analysis on data from a previously published, cluster randomized trial in cardiac rehabilitation. We compared six different statistical analysis methods (weighted and unweighted t-test; adjusted χ2 test; normal and multilevel logistic regression analysis; and generalized estimation equations). There were considerable differences in both point estimates and p-values derived by the methods, and differences were larger with increasing intracluster correlation
M3 - Article
C2 - 23542960
SN - 0926-9630
VL - 186
SP - 22
EP - 27
JO - Studies in health technology and informatics
JF - Studies in health technology and informatics
ER -