Is the Gene-Environment Interaction Paradigm Relevant to Genome-Wide Studies? The Case of Education and Body Mass Index

This study uses data from the Framingham Heart Study to examine the relevance of the gene-environment interaction paradigm for genome-wide association studies (GWAS). We use completed college education as our environmental measure and estimate the interactive effect of genotype and education on body mass index (BMI) using 260,402 single-nucleotide polymorphisms (SNPs). Our results highlight the sensitivity of parameter estimates obtained from GWAS models and the difficulty of framing genome-wide results using the existing gene-environment interaction typology. We argue that SNP-environment interactions across the human genome are not likely to provide consistent evidence regarding genetic influences on health that differ by environment. Nevertheless, genome-wide data contain rich information about individual respondents, and we demonstrate the utility of this type of data. We highlight the fact that GWAS is just one use of genome-wide data, and we encourage demographers to develop methods that incorporate this vast amount of information from respondents into their analyses.     

Black,Queer, and Looking for a Job: An Exploratory Study of Career Decision Making Among Self-Identified Sexual Minorities at an Urban Historically Black College/University

This thematically analyzed study seeks to explore the career decision perceptions of sexual minority college students at an urban historically black college/university (HBCU). This qualitative focus group study delved into how sexual minorities feel their visible variables of race, gender expression, and degree of disclosure influence their career thought process. Theories relative to the study included Krumboltz’s social learning theory of career decision-making, gender role theory, racial socialization, Cass’s homosexual identity model, and impression management. Though participants initially proclaimed they did not allow their sexual minority identity to affect their career decisions, their overall responses indicated otherwise.     

Optimal One-Way Random Effects Designs for the Intraclass Correlation Based on Confidence Intervals

ABSTRACT

Confidence intervals for the intraclass correlation coefficient (ρ) are used to determine the optimal allocation of experimental material in one-way random effects models. Designs that produce narrow intervals are preferred since they provide greater precision to estimate ρ. Assuming the total cost and the relative cost of the two stages of sampling are fixed, the authors investigate the number of classes and the number of individuals per class required to minimize the expected length of confidence intervals. We obtain results using asymptotic theory and compare these results to those obtained using exact calculations. The best design depends on the unknown value of ρ. Minimizing the maximum expected length of confidence intervals guards against worst-case scenarios. A good overall recommendation based on asymptotic results is to choose a design having classes of size 2 + √4 + 3r, where r is the relative cost of sampling at the class-level compared to the individual-level. If r = 0, then the overall cost is the sample size and the recommendation reduces to a design having classes of size 4.     

Biostatistics:a difficult road ahead

We are now well into the nineteen-eighties and looking back over the last ten years one of the most striking, perhaps the most striking, aspect of biostatistics and statistical epidemiology is sheer volume of literature that has emerged. Any historian of our subject is bound to ask two major and not unrelated questions! how much of this was necessary and how much of it was of direct use to clinical science in the sense of giving real aid to progress in medicine?.     

Hiding Customer Complaints: Studying the Motivations and Forms of Service Employees' Complaint Concealment Behaviours

This study aims to explore both how and why customer service employees conceal the complaints made by customers. Using an exploratory qualitative approach, data were gathered through the in‐depth interviewing of 25 managers, 25 supervisors and 57 front‐line employees of UK general retailers/supermarkets. Data analysis reveals that the concealment of customer complaints by store employees of all hierarchical levels is common. Front‐line, customer‐contact employees were found to conceal complaints in four ways: through (1) misleading customers, (2) complaint resolution without logging, (3) concealing recorded complaints and (4) falsification of recorded complaints. Store‐level supervisory and managerial employees were also found to conceal complaints in four ways: through (1) complaint resolution without logging, (2) concealing recorded complaints, (3) the non‐recording of complaints and (4) the disregarding of ‘minor’ complaints. The motives for complaint concealment differed between managerial/supervisory and front‐line employees but included reasons of (1) personal protection, (2) perceived customer unpleasantness, (3) serial complaint avoidance, (4) alienation, (5) friends or family protection, (6) instrumental gain, (7) avoidance of additional work, (8) perceived unfairness and (9) limited time. These findings suggest that theorists and practitioners need to acknowledge the existence and prevalence of these motives and behaviours and incorporate them into their conceptualizations and practices.     

Testing for Unit Roots in Dynamic Panels in the Presence of a Deterministic Trend: Re-examining the Unit Root Hypothesis for Real Stock Prices and Dividends

In this paper, we suggest a similar unit root test statistic for dynamic panel data with fixed effects. The test is based on the LM, or score, principle and is derived under the assumption that the time dimension of the panel is fixed, which is typical in many panel data studies. It is shown that the limiting distribution of the test statistic is standard normal. The similarity of the test with respect to both the initial conditions of the panel and the fixed effects is achieved by allowing for a trend in the model using a parameterisation that has the same interpretation under both the null and alternative hypotheses. This parameterisation can be expected to increase the power of the test statistic. Simulation evidence suggests that the proposed test has empirical size that is very close to the nominal level and considerably more power than other panel unit root tests that assume that the time dimension of the panel is large. As an application of the test, we re-examine the stationarity of real stock prices and dividends using disaggregated panel data over a relatively short period of time. Our results suggest that while real stock prices contain a unit root, real dividends are trend stationary.