Increased prevalence of premature ejaculation in men with metabolic syndrome

This prospective study aimed to investigate the relationship between metabolic syndrome (Met S) and premature ejaculation (PE) among men. The study included 300 consecutive male patients (53.6 y?±?8.7) who attended the urology clinic (December 2013–September 2014), mostly complaining of renal/ureteric calculi. A diagnostic approach was undertaken to include demographics, clinical features and laboratory investigations of the study subjects. Both erectile function and PE were evaluated using the International Index of Erectile Function (abridged form, IIEF-5) and Premature Ejaculation Diagnostic Tool (PEDT) questionnaires, respectively. Results identified 182 (60.7%) men had Met S. Prevalence of PE was significantly higher in the subjects with Met S than the controls (35.2% vs 7.6%, p?< 0.001). Patients with Met S and PE had significantly higher PEDT scores (15.4 vs 6.7), smaller waist circumference (108.3?cm vs 111.5?cm) and higher fasting blood sugar (187?mg% vs 161?mg%) than those with no PE (p?p?=?0.047 and <0.001, respectively) with PE in Met S. In conclusion, PE has a high prevalence in Met S. Patients with Met S should be questioned about PE. Both ED and systolic hypertension may be associated with PE. Prevention of Met S should be considered, and this may be of help to decrease the prevalence of PE.     

On the Nearness of Records to Population Quantiles with Respect to Order Statistics in the Sense of Pitman Closeness

In this paper, Pitman closeness criterion is used to compare the nearness of record values and order statistics from two independent samples to a specific population quantile of the parent distribution while the underlying distributions are the same. General expressions for the associated Pitman closeness probability are obtained when the support of the parent distribution is bounded and also unbounded. Some distribution-free results are achieved for symmetric distributions. The exponential and uniform distributions are considered for illustrative proposes and exact expressions are obtained in each case.     

Estimation of the parameter of a dynamically selected population for two subclasses of the exponential family

We introduce the problem of estimation of the parameters of a dynamically selected population in an infinite sequence of random variables and provide its application in the statistical inference based on record values from a non stationary scheme. We develop unbiased estimation of the parameters of the dynamically selected population and evaluate the risk of the estimators. We provide comparisons with natural estimators and obtain asymptotic results. Finally, we illustrate the applicability of the results using real data.     

Semiparametric Estimation of a Change-point for Recurrent Events Data

One particular recurrent events data scenario involves patients experiencing events according to a common intensity rate, and then a treatment may be applied. The treatment might be effective for a limited amount of time, so that the intensity rate would be expected to change abruptly when the effect of the treatment wears out. In particular, we allow models for the intensity rate, post-treatment, to be at first decreasing and then change to increasing (and vice versa). Two estimators of the location of this change are proposed.     

Paving the Way for A Normal Life: A Qualitative Study of Coping Strategies Among Iranian Divorced Women

Regarding the devastating aftermath of divorce among Iranian divorced women, which is mainly affected by sociocultural factors, this qualitative study was conducted to explore their applied strategies in reorganizing their lives. Data collection started through deep unstructured interviews followed by semistructured interviews with 18 divorced women who were chosen by purposive sampling from mental health clinics, social work centers, or available cases. Gathered data were analyzed using the qualitative content analysis method. Two main themes—behaviors of self-preservation and abstinence and struggling for balance—emerged. Subcategories were concealing the divorce, feminine self-restriction, avoidance behaviors, replacement of losses, seeking support, role development, handling the tensions, and defending oneself against the divorce failure. This study provides comprehensive knowledge of how Iranian divorced women reregulate their lives and also highlights their unique and culture-based coping strategies. Therefore, it provides specialists with a context-specific foundation for mental health care and enables them to intervene more effectively.     

Bayesian prediction of order statistics with fixed and random sample sizes based on k-record values from Pareto distribution

In this paper, the two-parameter Pareto distribution is considered and the problem of prediction of order statistics from a future sample and that of its geometric mean are discussed. The Bayesian approach is applied to construct predictors based on observed k-record values for the cases when the future sample size is fixed and when it is random. Several Bayesian prediction intervals are derived. Finally, the results of a simulation study and a numerical example are presented for illustrating all the inferential procedures developed here.     

Comparison of preliminary test estimators based on generalized order statistics from proportional hazard family using Pitman measure of closeness

In this article, based on generalized order statistics from a family of proportional hazard rate model, we use a statistical test to generate a class of preliminary test estimators and shrinkage preliminary test estimators for the proportionality parameter. These estimators are compared under Pitman measure of closeness (PMC) as well as MSE criteria. Although the PMC suffers from non transitivity, in the first class of estimators, it has the transitivity property and we obtain the Pitman-closest estimator. Analytical and graphical methods are used to show the range of parameter in which preliminary test and shrinkage preliminary test estimators perform better than their competitor estimators. Results reveal that when the prior information is not too far from its real value, the proposed estimators are superior based on both mentioned criteria.     

Competing risks model for clustered data based on the subdistribution hazards with spatial random effects

In some applications, the clustered survival data are arranged spatially such as clinical centers or geographical regions. Incorporating spatial variation in these data not only can improve the accuracy and efficiency of the parameter estimation, but it also investigates the spatial patterns of survivorship for identifying high-risk areas. Competing risks in survival data concern a situation where there is more than one cause of failure, but only the occurrence of the first one is observable. In this paper, we considered Bayesian subdistribution hazard regression models with spatial random effects for the clustered HIV/AIDS data. An intrinsic conditional autoregressive (ICAR) distribution was employed to model the areal spatial random effects. Comparison among competing models was performed by the deviance information criterion. We illustrated the gains of our model through application to the HIV/AIDS data and the simulation studies.KEYWORDS: Competing risks, subdistribution hazard, cumulative incidence function, spatial random effect, Markov chain Monte Carlo     

Confidence and prediction intervals based on interpolated records

In several statistical problems, nonparametric confidence intervals for population quantiles can be constructed and their coverage probabilities can be computed exactly, but cannot in general be rendered equal to a pre-determined level. The same difficulty arises for coverage probabilities of nonparametric prediction intervals for future observations. One solution to this difficulty is to interpolate between intervals which have the closest coverage probability from above and below to the pre-determined level. In this paper, confidence intervals for population quantiles are constructed based on interpolated upper and lower records. Subsequently, prediction intervals are obtained for future upper records based on interpolated upper records. Additionally, we derive upper bounds for the coverage error of these confidence and prediction intervals. Finally, our results are applied to some real data sets. Also, a comparison via a simulation study is done with similar classical intervals obtained before.     

Point estimation of lower quantiles based on two-sampling scheme

ABSTRACT

Consider a two-sampling scheme in which an initial sample is first taken from the underlying population and then by assuming a suitable restriction on this sample, some more data points are observed as a new restricted sample. This sampling scheme is used to do inference about the lower quantiles of the underlying distribution. The results are compared with those of simple random sampling in view of mean squared error and Pitman’s measure of closeness criteria for exponential and uniform distributions. It will be shown that the proposed sampling scheme would improve the performance of the point estimators of the lower quantiles of the population.