Comparison of Two Psycho-Educational Interventions Aimed at Preventing HIV and Promoting Sexual Health Among Portuguese Women

This study compares the efficacy of 2 psychoeducational interventions—ACCENT skills-based and didactic information only—to prevent HIV among Portuguese women. At posttest and follow-up, participants in both intervention groups (n = 127) were more knowledgeable about HIV than at baseline. Although both intervention groups showed an increase in self-reported condom use over time, differences were marginally stronger in the ACCENT group. Both intervention groups showed more positive results than the non-intervention control group (n = 33). The study suggests that HIV prevention interventions can produce significant changes when they target a set of knowledge, social, and cognitive variables relevant to sexual behavior change.     

Sexuality in Older Adults (65+)—An Overview of the Literature,Part 1: Sexual Function and its Difficulties

Objectives: The aim of the current article was to provide an overview of literature on sexual function and sexual difficulties in older adults. Method: The authors conducted a narrative review of papers published in English between January 2005 and July 2015 based on an extensive search in PsycINFO. Results: The review showed that although common biological changes may adversely affect sexual function in old age, sexual experience seems to also be affected by psychological and interpersonal factors. Conclusions: Greater life expectancy and better medical care will result in older individuals with chronic diseases living longer. The need for help to cope with changes in sexual health is likely to increase in older adults, as sexuality may be negatively affected through several pathways.     

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.     

All Data are Wrong,but Some are Useful? Advocating the Need for Data Auditing

In a recent article from the Annals of Applied Statistics, Cox discussed the main phases of applied statistical research ranging from clarifying study objectives to final data analysis and interpreting results. As an incidental remark to these main phases, we advocate that beyond cleaning and preprocessing the data, it is a good practice to audit the data to determine if they can be trusted at all. A case study based on Ghanaian Official Fishery Statistics is used to illustrate this need, with Benford's law being the tool used to carrying out the data audit. Supplementary materials for this article are available online.     

Permuting incomplete paired data: a novel exact and asymptotic correct randomization test

Various statistical tests have been developed for testing the equality of means in matched pairs with missing values. However, most existing methods are commonly based on certain distributional assumptions such as normality, 0-symmetry or homoscedasticity of the data. The aim of this paper is to develop a statistical test that is robust against deviations from such assumptions and also leads to valid inference in case of heteroscedasticity or skewed distributions. This is achieved by applying a clever randomization approach to handle missing data. The resulting test procedure is not only shown to be asymptotically correct but is also finitely exact if the distribution of the data is invariant with respect to the considered randomization group. Its small sample performance is further studied in an extensive simulation study and compared to existing methods. Finally, an illustrative data example is analysed.     

Estimation of P{X < Y} for geometric—exponential model based on complete and censored samples

This article deals with the estimation of R = P{X < Y}, where X and Y are independent random variables from geometric and exponential distribution, respectively. For complete samples, the MLE of R, its asymptotic distribution, and confidence interval based on it are obtained. The procedure for deriving bootstrap-p confidence interval is presented. The UMVUE of R and UMVUE of its variance are derived. The Bayes estimator of R is investigated and its Lindley's approximation is obtained. A simulation study is performed in order to compare these estimators. Finally, all point estimators for right censored sample from the exponential distribution, are obtained.     

Minimum variance unbiased estimation of stress–strength reliability under bivariate normal and its comparisons

In many industrial and natural phenomena, we need the probability that a component is smaller than the other component. Under a stress–strength model, this is reliability of an item. Under independent setup, there are different approaches for the estimation of such reliability. Here, estimation is considered under the dependent case. Under bi-variate setup uniformly minimum variance unbiased estimator is obtained. Also comparison with available estimator based on Maximum Likelihood Estimate (MLE) is done through Mean Square Error (MSE) and bias. Also these are compared by computing L₁ distance between their distribution functions. From this idea and numerical computations, UMVUE appears to be good.     

On some aspects of a generalized alternative zero-inflated logarithmic series distribution

Here, we consider a generalized form of the alternative zero-inflated logarithmic series distribution of Kumar and Riyaz (J. Statist. Comp. Simul., 2015) and study some of its important aspects. The parameters of the distribution are estimated by the method of maximum likelihood and some test procedures are developed for testing the significance of the additional parameter of the model. All these estimation and testing procedures are illustrated with the help of certain real life datasets. A simulation study is also carried out for assessing the performance of the estimators.     

On the performance of Turing's formula: A simulation study

Turing's formula is an amazing result that allows one to estimate the probability of observing something that has not been observed before. After a brief review of the literature, we perform a simulation study to better understand how well this formula works in a variety of situations. We also compare the performance of Turing's formula with several modifications that have appeared in the literature. We find that these modifications tend to outperform Turing's formula, but usually not by very much. We further find that Turing's formula and its modifications tend to work better for heavy-tailed distributions than for light-tailed ones.