Physical Sciences and Mathematics Commons^™

Who Enrolled In A State Program For The Uninsured: Was There Adverse Selection?, Paula Diehr

Paula Diehr

Managed care plans may hesitate to participate in programs for uninsured persons because they fear adverse selection, whereby only the sickest people or highest users would choose to join the program. We studied this issue in Washington State's Basic Health Plan, a demonstration program that provides subsidized health insurance for families earning less than 200% of the poverty level. We interviewed people in three counties who enrolled in the program, and compared them to people in the same counties who were eligible but did not enroll. There were substantial differences between enrollees and eligibles in education, age, income, employment, race, …

Do Communities Differ In Health Behaviors?, Paula Diehr

Paula Diehr

Communities differ in the prevalence of various health behaviors, but it is not known to what extent these differences are due to "different types" of people living in them. We used data from the evaluation of the Henry J Kaiser Family Foundation Community Health Promotion Grant Program to study individual-level and community-level variation in health behaviors for 15 communities. Our results show (1) there was significant variation among these communities in prevalences of smoking, consumption of alcohol and dietary fat, and use of seatbelts; (2) these differences persisted after control for demographic, health status, and other health behavioral characteristics of …

Small Area Variation Analysis. Methods For Comparing Several Diagnosis-Related Groups., Paula Diehr

Paula Diehr

In small-area variation analysis, the variation of health care utilization rates, e.g., admission rates, among small areas is calculated. Frequently, the variation of one diagnosis, diagnosis-related group (DRG), or procedure is compared with the variation of another. Unfortunately, the methods generally used to make these comparisons are not consistent. They differ on whether they 1) adjust for the prevalence of the DRGs, 2) distinguish between variation among areas and variation within areas, 3) weight all areas equally, and 4) adjust for multiple admissions per person. None has an associated confidence interval. These discrepancies occur in part because there is no …

Generalized Linear Models: Software Implementation And The Structure Of A General Power-Link Based Glm Algorithm, Joseph Hilbe

Joseph M Hilbe

Generalized linear modeling (GLM) is currently undergoing a renaissance. The number of software packages offering GLM capability grows each year and as a partial consequence one finds an increased number of research endeavors being modeled using GLM methodology. On the other hand, there have likewise been an increasing number of requests to vendors by users of statistical packages to include GLM facilities amid other offerings. The overall effect has been a near 300 percent increase in GLM programs over the past four years.

I shall discuss the nature of generalized linear models followed by an examination of how they have …

Special Review: Evaluation Of The Exploratory Factor Analysis Programs Provided In Spssx And Spss/Pc+, Gregory J. Boyle

Gregory J. Boyle

Given the frequent use of SPSSX and SPSS/PC+ exploratory factor analysis in analyzing multivariate psychometric data, it is germane to examine the limitations of the Factor program as it currently exists. Over recent years, the routines in these packages generally have been developed and expanded considerably. In particular, the exploratory factor analysis procedures have been greatly extended and enhanced with inclusion of additional estimation methods such as minimum likelihood, unweighted least squares, generalized least squares, and so on. Like­ wise, availability of a Scree plot of the latent roots against factor number has facilitated determination of the appropriate factor-extraction number. …