TESTING SPHERICITY UNDER A MIXTURE MODEL

The robustness of Mauchly's sphericity test criterion when sampling from a mixture of two multivariate normal distributions is studied. The distribution of the sphericity test criterion when the sample covariance matrix has a non-central Wishart density of rank one is derived in terms of Meijer's G-functions; its distribution under the mixture model is then deduced. The robustness is studied by computing actual significance levels of the test under the mixture model using the critical values under the usual normal model.     

DRUG POLICY IN THE TIME OF AIDS:

In 1985, the National Institute on Drug Abuse (NIDA) funded an ethnographic research project in San Francisco to study the needle sharing behavior of injection drug users (IDUs). The goal of the research was to develop a strategy to slow the spread of HIV among this hidden and hard to reach population of drug users and their sexual partners. This small-scale project grew into a model intervention in which bleach, condoms, and street-based education by outreach workers were employed to inform IDUs of the risk of AIDS and of methods for protecting themselves. The "reach and teach bleach" model was adopted by NIDA and implemented in a number of American cities. This study describes the development of the model intervention, the adoption of the model by NIDA as part of its National AIDS Demonstration Research (NADR) project, and the political circumstances under which the city of San Francisco applied for the NADR grant. Drawing on Social Worlds/Arena theory, and based on extensive interviews and participant observation, a sociohistorical analysis examines the initial development, implementation, and disintegration of the model outreach project and the impact of the program on drug policy in the city of San Francisco.     

Children's gender- and age-based categorization in similarity and induction tasks

The present studies examined children's and adults' preferences for gender- or age-based categorization using similarity and inductive inference tasks. Four-year-olds, 6-year-olds, and adults looked at pictures of people and decided which of two was more like a target (similarity condition) or which shared a novel age- or gender-related property with the target (inference condition). Age or gender-based matches were possible. The results are consistent with previous findings that gender-based classification decreases with age. However, they also demonstrate that children use gender more for judging similarity than for making inferences about novel properties. Distinct patterns emerge from the two tasks: 6-year-olds and adults in both conditions categorize more by age than gender; 4-year-olds categorize by gender more than age in the similarity task, but by age more in the induction task. Only adults differentiated by property in the inference condition. These findings suggest that the salience of gender categories cannot entirely be attributed to their inductive potential. Gender has a salience beyond what would be predicted by its power for directing novel generalizations.     

Estimation of noncentrality parameters

We propose some estimators of noncentrality parameters which improve upon usual unbiased estimators under quadratic loss. The distributions we consider are the noncentral chi-square and the noncentral F. However, we give more general results for the family of elliptically contoured distributions and propose a robust dominating estimator.     

Erroneous perceptions and arousal among regular and occasional video poker players

This study investigated the relationship between the level of arousal (Heart Rate) and the number of erroneous perceptions among video poker players. Twelve regular and twelve occasional gamblers participated in a gambling session conducted in a natural environment. It was hypothesised that 1) a significant positive correlation would be observed between arousal and the number of erroneous verbalizations, 2) regular players would show a higher level of arousal than occasional players, and 3) they would emit more erroneous verbalizations. Results showed that hypotheses one and three were confirmed. Theoretical and practical implications of these results for the psychology of gambling are discussed.This study was supported by a grant from Loto-Québec.     

The Micro System of Deviance in Intimate Relationships*

Deviance in intimate relationships may lie as much within the micro system of such relationships as it does within the personalities of the actors involved. Using a Parsonsian framework, it is argued that the strain of systemically disequilibrated relationships can produce deviant personality adaptations which, in turn, intensify conflict and deviance in those relationships. It is also proposed that a reciprocal quality exists to such maladaptations, with each member of the dyad contributing to the amplification of a stable system of deviant behavior patterns within the relationship. Because the patterns of maladaptive dyads spill over into parent-child relationships, they have implications for understanding intergenerational transmission of deviance between intimates.     

ANOTHER LOOK AT THE STRATIFICATION OF EDUCATIONAL TRANSITIONS: THE LOGISTIC RESPONSE MODEL WITH PARTIAL PROPORTIONALITY CONSTRAINTS

In this paper we reanalyze Robert D. Mare's highly influential work on educational transitions among American men born in the first half of the 20th century. Contrary to previous belief, Mare found that the effects of socioeconomic background variables decline regularly across educational transitions in conditional logistic regression analyses. We have reconfirmed Mare's findings and tested them by introducing a modified logistic response model that constrains selected social background effects to vary proportionally across educational transitions. We refer to our preferred model as the logistic response model with partial proportionality constraints (LRPPC). The model can easily be estimated in Stata or using other standard statistical software. Partial proportionality constraints may also prove useful in interpopulation comparisons based on other linear models.     

Effects of Medicaid managed care policies on mental health service use among a national probability sample of children in the child welfare system

Children in the child welfare system are dependent upon Medicaid to finance services for their considerable mental health needs. This study examines the effects of Medicaid policies on mental health service use among a national probability sample of children in the child welfare system. Data for this study came from the National Survey of Child and Adolescent Well-Being, the Caring for Children in Child Welfare study, and the Area Resource File. Weighted multivariate logistic regression analyses were conducted to estimate effects of policy variables on children's use of mental health services, controlling for child-level covariates and county-level health resources. Children in counties with behavioral carve-outs under Medicaid managed care had lower odds of inpatient mental health service use. Medicaid managed care enrollment and variations in type of provider reimbursement did not affect use of mental health services. Older age, greater need for mental health services, and higher levels of caregiver education were associated with increased odds of service use. Restrictions on use of inpatient mental healthcare caused by behavioral carve-outs may disproportionately affect children in the child welfare system who have high rates of such use. Careful adoption of carve-outs is necessary to assure appropriate care for these children.     

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature.