Nonparametric statistical procedures for the changepoint problem

Let X₁,…,X_r?1,X_r,X_r+1,…,X_n be independent, continuous random variables such that X_i, i = 1,…,r, has distribution function F(x), and X_i, i = r+1,…,n, has distribution function F(x?Δ), with -∞ <Δ< ∞. When the integer r is unknown, this is refered to as a change point problem with at most one change. The unknown parameter Δ represents the magnitude of the change and r is called the changepoint. In this paper we present a general review discussion of several nonparametric approaches for making inferences about r and Δ.     

THE CULTURAL GENOGRAM: KEY TO TRAINING CULTURALLY COMPETENT FAMILY THERAPISTS

Training programs committed to the development of culturally competent family therapists must discover ways to raise cultural awareness and increase cultural sensitivity. While awareness involves gaining knowledge of various cultural groups, sensitivity involves having experiences that challenge individuals to explore their personal cultural issues. This article outlines how the cultural genogram can be used as an effective training tool to promote both cultural awareness and sensitivity.     

Medcamp's Effect on Junior High School Students' Medical Career Self-Efficacy

Medcamp, a 3-day problem-based career intervention for students entering the 9th grade, implemented each of the 4 antecedents for self-efficacy. Ten boys and 35 girls participated in Medcamp; of these, 35 completed and returned the Medical Career Self-Efficacy Scales (developed by the authors for their study) both at the beginning and at the end of the program. Three scales measured specific self-efficacy (tasks students had performed during Medcamp), related self-efficacy (other tasks students would complete by the second year of medical school), and general self-efficacy (included lifestyle variables and study habits). Results demonstrated significant increases in self-efficacy on all 3 scales.     

Entropy Measures of Inequality*

Although sociologists have long been interested in the analysis of inequality, there have been relatively few systematic attempts to measure it. Most measurement has utilized popular existing measures such as the Gini coefficient, which unfortunately is relatively difficult to compute and interpret. This article presents a new measure of inequality (B) that is based upon the concept of entropy. The B measure is used for categorical data and complements Theil's (T) entropy measure for continuous data. The B measure is illustrated for both income and wealth data and successfully meets several criteria for evaluating measures of inequality. These include the criteria of scale invariance, sensitivity to transfers, and adequate upper bounds. A further advantage of sociological entropy measures of inequality is that they facilitate interdisciplinary comparison of work on inequality between sociology and other disciplines (such as economics) which use entropy measures of inequality.     

Planning for innovation in health care: A breakthrough in blood banking

A solution for preserving red blood cells (adenine) will make it possible to extend the life of blood from 21 to 35 days. Adenine supplementation may bring dramatic changes in blood outdating and the supply of blood to hospital blood banks. Substantial improvements, however, can be realized only if blood administrators are able to estimate the potential effects of adenine supplementation and set goals based on these projections. Appropriate action could then be taken to reduce blood collection and increase the supply of blood to hospitals. This paper offers a method for blood administrators to estimate the full effects of adenine supplementation and set reasonably attainable goals. Experiences with setting goals for a midwestern U.S. blood region are then discussed.     

Efficient Estimation of Nested Logit models

This article examines the sequential, full information maximum likelihood (FIML), and linearized maximum likelihood (LML) estimators for a nested logit model of time-of-day choice for work trips. These estimators are compared using a Monte Carlo study based on specification and data from a previously published empirical study. The sequential estimator is found to be much less efficient than LML or FIML, and its uncorrected second-stage standard-error estimates are strongly downward biased. LML is only slightly less efficient than FIML, but it is often easier to compute. There are cases in which the sequential and LML estimators do not exist, but FIML still performs well.     

On Measuring Segregation in Samples With Small Units

Standard indexes of segregation measure a sample's distance from evenness, which occurs when each sample unit (e.g., an occupation) has the population share of both the minority and majority groups. We show that random allocation of individuals to units generates substantial unevenness among small units and hence that standard segregation indexes reflect random allocation as well as systematic group segregation. We then modify two popular indexes so that they measure deviations from random allocation rather than deviations from evenness. An empirical example suggests that these modified indexes provide improved measures of the systematic component of group segregation.