A NOTE ON A SEQUENTIAL GROUP t-TEST

A sequential probability ratio test (SPET) of the mean of a normal distribution with unknown variance, based on an independent sequence of groups of observations, is investigated and its efficiency compared with that of the WAGE sequential t-test, which is based on an invariantly sufficient sequence of test statistics.     

Biotechnology: will it break the health care bank?

Pharmaceuticals traditionally have been viewed as a cost-effective component in medicine's technological armamentarium. The use of pharmaceuticals has been estimated to account for 6-8 percent of the nation's total expenditures on health care. The first wave of pharmaceuticals/biologicals that has been produced by the biotechnology industry has offered therapies that can provide much benefit to patients, but it has also raised concern about the cost of these new recombinant drugs. In addition to pricing, methods of promotion and modifications in the FDA approval process have raised concerns.     

Suicide Attempts by Adolescent Latinas: An Exploratory Study of Individual and Family Correlates

Epidemiological data show high rates of suicide attempts among adolescent Latinas. Few studies have addressed the psychosocial, cultural and family correlates of suicide attempts among this age group of a rapidly growing population. The authors studied 31 adolescent Hispanic females who were receiving mental health services; 14 girls had attempted suicide in the previous five years and 17 had never attempted suicide. The two groups of girls did not differ significantly with respect to demographic profiles, levels of depression, family type, acculturation, or self-esteem. However, as hypothesized, the mutuality between girls and their mothers was lower among suicide attempters. Maladaptive coping skills of withdrawal and wishful thinking were more commonly used by attempters, and non-attempters used emotional regulation and problem-solving more frequently. Findings are discussed within the context of the empirical and theoretical literature and implications for practice are considered.     

MEANINGFUL REGRESSION AND ASSOCIATION MODELS FOR CLUSTERED ORDINAL DATA

Many proposed methods for analyzing clustered ordinal data focus on the regression model and consider the association structure within a cluster as a nuisance. However, the association structure is often of equal interest—for example, temporal association in longitudinal studies and association between responses to similar questions in a survey. We discuss the use, appropriateness, and interpretability of various latent variable and Markov models for the association structure and propose a new structure that exploits the ordinality of the response. The models are illustrated with a study concerning opinions regarding government spending and an analysis of stability and change in teenage marijuana use over time, where we reveal different behavioral patterns for boys and girls through a comprehensive investigation of individual response profiles.     

Mood in Daily Contexts: Relationship With Risk in Early Adolescence

Disturbances in affect have been linked to problem behavior in adolescence and future psychopathology, but little is known about how such disturbances manifest themselves in everyday contexts. This study investigated daily mood in Dutch 7th graders, aged 11–14. Cluster analysis of problem measures distinguished high-risk (n=25) and low-risk (n=106) subgroups. Participants completed experience-sampling reports of mood, social context, and location nine times daily for 5 days. Multilevel regression analyses of four mood measures confirmed higher anxiety and depressed mood in the high-risk group. Moods varied by location and social context, with significant differences between groups in two specific social contexts. First, when with family, low-risk adolescents felt less depressed than when alone, whereas high-risk adolescents felt more depressed. Second, high-risk adolescents showed more pronounced anxiety in social situations outside the network of family and friends. These findings point to everyday social contexts in which young adolescents with emotional and behavioral problems appear to be particularly vulnerable.     

Rural Income-Generating Programs and Fertility Limitation: Evidence from a Microdemographic Study in Nepal1

Abstract Participation in rural development programs that organize members into local cooperative groups can alter the decision-making environment facing couples to reflect some of the negative consequences of childbearing. This study uses data from Nepal, collected through a combination of ethnographic and survey methods, to test the effects of participation in such a development program on fertility behavior. Results demonstrate that program participants are much more likely to use contraceptives to limit their fertility than are non-participants. The study provides empirical support for theories linking this type of institutional change to fertility and indicates a policy option that can allow some negative consequences of childbearing to affect couples' fertility decisions.     

Boosting with Bayesian stumps

Boosting is a new, powerful method for classification. It is an iterative procedure which successively classifies a weighted version of the sample, and then reweights this sample dependent on how successful the classification was. In this paper we review some of the commonly used methods for performing boosting and show how they can be fit into a Bayesian setup at each iteration of the algorithm. We demonstrate how this formulation gives rise to a new splitting criterion when using a domain-partitioning classification method such as a decision tree. Further we can improve the predictive performance of simple decision trees, known as stumps, by using a posterior weighted average of them to classify at each step of the algorithm, rather than just a single stump. The main advantage of this approach is to reduce the number of boosting iterations required to produce a good classifier with only a minimal increase in the computational complexity of the algorithm.     

Robust confidence interval for a residual standard deviation

The residual standard deviation of a general linear model provides information about predictive accuracy that is not revealed by the multiple correlation or regression coefficients. The classic confidence interval for a residual standard deviation is hypersensitive to minor violations of the normality assumption and its robustness does not improve with increasing sample size. An approximate confidence interval for the residual standard deviation is proposed and shown to be robust to moderate violations of the normality assumption with robustness to extreme non-normality that improves with increasing sample size.     

Determinants of Perceived Interfirm Dependence in Industrial Supplier Relations

Studies of industrial buyer-supplier relations mostly focus on structural characteristics of the transactions between parties, and assume a direct relation between these factors and characteristics of the relationships. This paper focuses on the psychological dimension of transaction relations, reflected in perceptions of dependence, from the perspective of an industrial supplier. In the first step of the analysis, three groups of structural determinants of perceived supplier dependence are explored: factors related to goal mediation, factors related to relation-specific assets, and factors related to network embeddedness. After that, the influence of these structural factors and of perceived supplier dependence on the ordering of buyer-supplier relations is investigated. Data come from a study of the micro-electronics assembly industry in the Netherlands. The findings show that sales to a particular buyer as a percentage of the total sales of the supplier and the growth of sales to a particular buyer (two forms of goal mediation) are important determinants of perceived supplier dependence. Human asset specificity is also related to perceived supplier dependence. Network embeddedness variables play only a minor role in explaining perceived supplier and buyer dependence in this study. The data further show that perceived dependence has an effect on the degree of ordering in the relationship, next to structural factors like the extendedness of the relationship beyond the focal transaction and physical asset specificity. The effects of human asset specificity and dedicated assets on ordering are contrary to what was expected on the basis of the literature.