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.     

Influence of Female Genital Cutting on Sexual Experience in Southern Ethiopia

Female genital cutting (FGC) is a persistent social norm in the Liben district of southern Ethiopia. This study explores whether the sexual experiences of married men and women differ by women's FGC status. Qualitative in-depth interviews were conducted with 28 women with different types of FGC (or no FGC) and 21 husbands. Compared to others, women with more severe FGC reported traumatic sexual experiences and decreased sexual desire. Nonetheless, participants largely endorsed FGC for daughters, revealing pressure to maintain the practice. Opportunities for change exist, as women and men recognized the sexual pleasure and healthy birth experiences of uncut women.     

The Impact of HIV Pre-exposure Prophylaxis (PrEP) Use on the Sexual Health of Men Who Have Sex with Men: A Qualitative Study in Seattle,WA

This study explores the impacts of HIV pre-exposure prophylaxis (PrEP) use on the sexual health of men who have sex with men (MSM). The authors conducted in-depth interviews with MSM who use PrEP (n = 14). Data was analyzed using interpretative phenomenological analysis. PrEP use reduced fear and shame associated with sex and facilitated greater sexual satisfaction and intimacy. Although participants generally viewed PrEP as empowering and beneficial, they also experienced PrEP-related stigma. The authors’ analysis emphasizes the importance of understanding the reasons MSM use PrEP and highlights opportunities for reducing harm and fostering sexual health among MSM who are using or considering PrEP.     

Seemingly unrelated systems of econometric equations

A generalization of Zellner's SUR model is derived for sets of seemingly unrelated systems of econometric equations. The resulting structural form – worked out for a set of Cowles Commission-type simultaneous equations systems – is general enough to include any SUR-type or panel-type specification of systems of econometric equations with contemporaneously correlated errors. Maximum estimation efficiency is obtained by treating all the individual subsystems at once rather than in a subsystem-by-subsystem fashion.     

Spatio‐temporal Ornstein–Uhlenbeck Processes: Theory,Simulation and Statistical Inference

Spatio‐temporal modelling is an increasingly popular topic in Statistics. Our paper contributes to this line of research by developing the theory, simulation and inference for a spatio‐temporal Ornstein–Uhlenbeck process. We conduct detailed simulation studies and demonstrate the practical relevance of these processes in an empirical study of radiation anomaly data. Finally, we describe how predictions can be carried out in the Gaussian setting.     

Marginal models for the association structure of hierarchical binary responses

Clustered binary responses are often found in ecological studies. Data analysis may include modeling the marginal probability response. However, when the association is the main scientific focus, modeling the correlation structure between pairs of responses is the key part of the analysis. Second-order generalized estimating equations (GEE) are established in the literature. Some of them are more efficient in computational terms, especially facing large clusters. Alternating logistic regression (ALR) and orthogonalized residual (ORTH) GEE methods are presented and compared in this paper. Simulation results show a slightly superiority of ALR over ORTH. Marginal probabilities and odds ratios are also estimated and compared in a real ecological study involving a three-level hierarchical clustering. ALR and ORTH models are useful for modeling complex association structure with large cluster sizes.     

Generalized correlation and kernel causality with applications in development economics

New generalized correlation measures of 2012, GMC(Y|X), use Kernel regressions to overcome the linearity of Pearson's correlation coefficients. A new matrix of generalized correlation coefficients is such that when |r*_ij| > |r*_ji|, it is more likely that the column variable X_j is what Granger called the “instantaneous cause” or what we call “kernel cause” of the row variable X_i. New partial correlations ameliorate confounding. Various examples and simulations support robustness of new causality. We include bootstrap inference, robustness checks based on the dependence between regressor and error, and on the out-of-sample forecasts. Data for 198 countries on nine development variables support growth policy over redistribution and Deaton's criticism of foreign aid. Potential applications include Big Data, since our R code is available in the online supplementary material.     

Correlated gamma frailty models for bivariate survival data

Frailty models are used in the survival analysis to account for the unobserved heterogeneity in individual risks to disease and death. To analyze the bivariate data on related survival times (e.g., matched pairs experiments, twin or family data) the shared frailty models were suggested. Shared frailty models are used despite their limitations. To overcome their disadvantages correlated frailty models may be used. In this article, we introduce the gamma correlated frailty models with two different baseline distributions namely, the generalized log logistic, and the generalized Weibull. We introduce the Bayesian estimation procedure using Markov chain Monte Carlo (MCMC) technique to estimate the parameters involved in these models. We present a simulation study to compare the true values of the parameters with the estimated values. Also we apply these models to a real life bivariate survival dataset related to the kidney infection data and a better model is suggested for the data.     

A general long-term aging model with different underlying activation mechanisms: Modeling,Bayesian estimation,and case influence diagnostics

In this paper we propose a general cure rate aging model. Our approach enables different underlying activation mechanisms which lead to the event of interest. The number of competing causes of the event of interest is assumed to follow a logarithmic distribution. The model is parameterized in terms of the cured fraction which is then linked to covariates. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis for the proposed model. Moreover, some discussions on the model selection to compare the fitted models are given, as well as case deletion influence diagnostics are developed for the joint posterior distribution based on the ψ-divergence, which has several divergence measures as particular cases, such as the Kullback–Leibler (K-L), J-distance, L₁ norm, and χ²-square divergence measures. Simulation studies are performed and experimental results are illustrated based on a real malignant melanoma data.