However, as explained in Chap.
In these cases, specialized techniques must be applied in order to produce the appropriate estimates and their standard errors. Clustered data are frequently encountered in fields such as health services, public health, epidemiology, and education research.
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- By Uncategorized Multinomial logistic regression is the multivariate extension of a chi-square analysis of three of more dependent categorical outcomes.
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Data may consist of patients clustered within primary care practices or hospitals, or households clustered within neighborhoods, or students clustered within schools.
Subjects nested within the same cluster often exhibit a greater degree of similarity, or homogeneity, of outcomes compared to randomly selected subjects from different clusters Multilevel analysis: an introduction to basic and advanced multilevel modeling, Thousand Oaks, CA; Hierarchical linear models: applications and data analysis methods, Thousand Oaks, CA; Introduction to multilevel modeling, Thousand Oaks, CA; Multilevel statistical models, London; Canadian Journal of Public Health —, Due to the possible lack of independence of subjects within the same cluster, traditional statistical methods may not be appropriate for the analysis of clustered data.
While Chap. The logistic regression model on the analysis of survey data takes into account the properties of the survey sample design, including stratification, clustering, and unequal weighting.
Chi-square tests for overdispersion with multiparameter estimates. Wilson, J.
Approximate distribution and test of fit for the clustering effect in Dirichlet multinomial model. Communications in Statistics A, 15 4— Koehler, K.
Chi-square tests for comparing vectors of proportions for several cluster samples. Communications in Statistics A, 15 10—