Texas Department of Health organizational structure changes: A reflection of public health policy and agency expansion, September 1, 1946--June 30, 1994

The premise of this study is that changes in the agency's organizational structure reflect changes in government public health policy. Based on this premise, this study tracks the changes in the organizational structure and the overall expansion of the Texas Department of Health to understand the evolution of changing public health priorities in state policy from September 1, 1946 through June 30, 1994, a period of growth and new responsibilities. It includes thirty-seven observations of organizational structure as depicted by organizational charts of the agency and/or adapted from public documents. ^ The major questions answered are, what are the changes in the organizational structure, why did they occur and, what are the policy priorities reflected in these changes in and across the various time periods. ^ The analysis of the study included a thorough review of the organizational structure of the agency for the time-span of the study, the formulation of the criteria to be used in ascertaining the changes, the delineation of the changes in the organizational structure and comparison of the observations sequentially to characterize the change, the discovery of reasons for the structural changes (financial, statutory - federal and state, social and political factors), and the determination of policy priorities for each time period and their relation to the expansion and evolution of the agency. ^ The premise that the organizational structure of the agency and the changes over time reflect government public health policy and agency expansion was found to be true. ^

A Bayesian approach to estimating the intraclass correlation coefficient

A Bayesian approach to estimating the intraclass correlation coefficient was used for this research project. The background of the intraclass correlation coefficient, a summary of its standard estimators, and a review of basic Bayesian terminology and methodology were presented. The conditional posterior density of the intraclass correlation coefficient was then derived and estimation procedures related to this derivation were shown in detail. Three examples of applications of the conditional posterior density to specific data sets were also included. Two sets of simulation experiments were performed to compare the mean and mode of the conditional posterior density of the intraclass correlation coefficient to more traditional estimators. Non-Bayesian methods of estimation used were: the methods of analysis of variance and maximum likelihood for balanced data; and the methods of MIVQUE (Minimum Variance Quadratic Unbiased Estimation) and maximum likelihood for unbalanced data. The overall conclusion of this research project was that Bayesian estimates of the intraclass correlation coefficient can be appropriate, useful and practical alternatives to traditional methods of estimation. ^