A Factor-Adjusted Multiple Testing Procedure With Application to Mutual Fund Selection

In this article, we propose a factor-adjusted multiple testing (FAT) procedure based on factor-adjusted p-values in a linear factor model involving some observable and unobservable factors, for the purpose of selecting skilled funds in empirical finance. The factor-adjusted p-values were obtained after extracting the latent common factors by the principal component method. Under some mild conditions, the false discovery proportion can be consistently estimated even if the idiosyncratic errors are allowed to be weakly correlated across units. Furthermore, by appropriately setting a sequence of threshold values approaching zero, the proposed FAT procedure enjoys model selection consistency. Extensive simulation studies and a real data analysis for selecting skilled funds in the U.S. financial market are presented to illustrate the practical utility of the proposed method. Supplementary materials for this article are available online.     

Elementary School-age Children's Attitudes Toward Children in Same-Sex Parent Families

As numbers of families with same-sex parents increase in the United States, children are more likely to encounter diverse family structures. Given that young children can demonstrate in-group bias, prejudicial attitudes, and social exclusion, it is important to understand how children perceive their peers in diverse families. To our knowledge, no studies have assessed elementary-school-age children's attitudes about same-sex parent families. Here, 131 elementary school students (M_age = 7.79 years; 61 girls) viewed images of same-sex (female and male) and other-sex couples with a child and then were asked about their perceptions of these families, particularly the children. Results indicated participants' preferences toward children with other-sex versus same-sex parents. Developmental and practical implications about children's attitudes toward sexual minority parent families are discussed.     

Measuring the health patterns of the ‘mixed/multiple’ ethnic group in Britain: data quality problems,reporting issues,and implications for policy

The ‘mixed’ group, officially recognised in the 2001 Census, is one of the most rapidly growing ethnic groups in Britain. Although ‘mixed’ categorisation was added to ethnic coding in NHS datasets, our knowledge of health patterns for this population is meagre. Data quality problems remain a key obstacle, including poor reproducibility of the data and constraints on reporting due to sparse data bias. The consequent minimal and indicative evidence base has focused mainly on risky health behaviours, mental health and generic measures of self-rated health, as it has in the U.S.A. and Canada. There is negligible information on the main underlying causes of death, such as neoplasms, heart disease and stroke. Consideration should be given to pooling data across multiple years of health and general purpose surveys to enable reporting for the four ‘mixed’ categories and adjustment for mediating factors and relevant confounders, such as measures of socio-economic status.     

Estimates of subgroup treatment effects in overall nonsignificant trials: To what extent should we believe in them?

In drug development, it sometimes occurs that a new drug does not demonstrate effectiveness for the full study population but appears to be beneficial in a relevant subgroup. In case the subgroup of interest was not part of a confirmatory testing strategy, the inflation of the overall type I error is substantial and therefore such a subgroup analysis finding can only be seen as exploratory at best. To support such exploratory findings, an appropriate replication of the subgroup finding should be undertaken in a new trial. We should, however, be reasonably confident in the observed treatment effect size to be able to use this estimate in a replication trial in the subpopulation of interest. We were therefore interested in evaluating the bias of the estimate of the subgroup treatment effect, after selection based on significance for the subgroup in an overall “failed” trial. Different scenarios, involving continuous as well as dichotomous outcomes, were investigated via simulation studies. It is shown that the bias associated with subgroup findings in overall nonsignificant clinical trials is on average large and varies substantially across plausible scenarios. This renders the subgroup treatment estimate from the original trial of limited value to design the replication trial. An empirical Bayesian shrinkage method is suggested to minimize this overestimation. The proposed estimator appears to offer either a good or a conservative correction to the observed subgroup treatment effect hence provides a more reliable subgroup treatment effect estimate for adequate planning of future studies.     

Sexual orientation differences in HIV testing motivation among college men

Objective: To investigate sexual orientation differences in college men's motivations for HIV testing. Participants: 665 male college students in the Southeastern United States from 2006 to 2014. Methods: Students completed a survey on HIV risk factors and testing motivations. Logistic regressions were conducted to determine the differences between heterosexual men (HM) and sexual minority men (SMM). Results: SMM were more motivated to get tested by concern over past condomless sex, while HM were more often cited supporting the testing program “on principle” and wanting a free t-shirt. SMM and HM differed in behaviors that impact HIV risk and other demographics. However, differences in testing motivation by concern over past condomless sex or wanting a free t-shirt persisted when controlling for these demographic and behavioral differences. Conclusions: Appropriately designed HIV prevention interventions on college campuses should target SMM's distinct concern over past condomless sex as a testing motivation.     

Employee communication,job engagement,and organizational commitment: A study of members of the Millennial Generation

The purpose of this study was to explore the relationship between job engagement and two key components of employee-organization relationships (EOR). Findings from a survey of members of the Millennial Generation (N = 539) in the United States indicate that job engagement mediates the relationship between employee communication and organizational commitment. It is concluded that when employees are engaged in their work, their commitment to the organization is strengthened and the likelihood of them leaving the organization decreases. Furthermore, an argument is made in light of the study’s findings that engagement and commitment work in concert to strengthen EORs overall. To foster engagement, organizations should remove obstacles to internal information flow and provide ongoing feedback to employees about individual and organizational issues.     

Inappropriate Comparisons: The LGB Population's Missing Reference Group

ABSTRACT

Given that many professional organizations emphasize the need for comparing assessment results to appropriate reference groups in their codes of ethics, we consider this practice through an ecological perspective as it applies to the lesbian, gay, and bisexual (LGB) population. The purpose of norming and types of assessment bias is discussed with respect to LGB population, which frequently lack specific norming data. The authors discuss whether the LGB population has characteristics similar to other commonly normed for groups and explore how group-shared constructs such as minority stress and internalized homophobia may introduce bias and affect the validity of assessments. A social anxiety assessment as well as a personality disorder inventory are examined for bias as case examples explaining how these assessments may exhibit bias when used with the LGB population. Increases in validity and effects on treatment planning are discussed as benefits of providing LGB-specific norms. Risks of providing these norms, such as minimizing subgroup differences and possibly increasing the risk of discrimination are also addressed before providing clinicians with recommendations as to how they may minimize the risk of bias in their assessment process.