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.     

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.     

Maximum likelihood estimation,from doubly censored samples,of the mean of a normal distribution with known coeffucient of variation

Let x be a random variable having the normal distribution with mean μ and variance c²μ², where c is a known constant. The maximum likelihood estimation of μ when the lowest r₁ and the highest r₂ sample values censored have been given the asymptotic variance of the maximum likelihood estimator is obtained.     

Testing for linearity and convexity of potency curve

Let P(t) be the probability that a subject dies at dose level t or a unit fails at stress level t,then the Bayesian methodology is used to test (i) P(t) is straight line and (ii) P(t) is convex function (concave function).     

On the Optimal Parameters for Reconstruction and Forecasting in Singular Spectrum Analysis

There are two main parameters in Singular Spectrum Analysis (SSA). The aim of this study is to determine whether the optimal values of these parameters are different for reconstruction and forecasting stages, and if those are worth the extra computational effort and time which they require. Here, we evaluate these issues using simulation study.     

A Feasibility Study of Implementing the Policies on Increasing Birth Rate with an Emphasis on Socio-economic Status: A Case Study of Kermanshah Metropolis,Western Iran

Population and development have a mutual relationship, and more to the point, lack of sufficient knowledge on population development and fertility can lead to the presentation of inappropriate population plans in such a way that they may turn out to be useless and ineffective even in the event of implementation. So, the present study aimed to delve into the feasibility of implementing the new governmental policies on increasing birth rate with an emphasis on the socioeconomic status in Kermanshah Metropolis, Iran. To evaluate poverty and fertility in Kermanshah Metropolis, the present cross-sectional study used the latest statistics obtained from the Statistical Center of Iran (2011), and as for the data analysis, such tests in Arc/GIS and SPSS 20 software. The results of the present study showed that the spatial patterns of poverty and fertility were formed in clusters across the city, and the results of variance analysis of the relationship between the variables of fertility and poverty demonstrated that there was a significant difference between the selected neighborhoods in terms of the variables of poverty and total fertility (P < 0.001). Furthermore, the spatial autocorrelations of fertility and poverty in Kermanshah were positive and showed that the spatial means and standard distances of poverty and fertility were overlapping. Not all districts and urban neighborhoods were equal in the total fertility rate. So, given the societal classes’ different socioeconomic and cultural status across different neighborhoods, the government’s new approaches to increasing birthrate cannot be applied to all classes throughout Kermanshah Metropolis.

     

Prediction Regions for Bivariate Extreme Events

This paper suggests using a mixture of parametric and non‐parametric methods to construct prediction regions in bivariate extreme‐value problems. The non‐parametric part of the technique is used to estimate the dependence function, or copula, and the parametric part is employed to estimate the marginal distributions. A bootstrap calibration argument is suggested for reducing coverage error. This combined approach is compared with a more parametric one, relative to which it has the advantages of being more flexible and simpler to implement. It also enjoys these features relative to predictive likelihood methods. The paper shows how to construct both compact and semi‐infinite bivariate prediction regions, and it treats the problem of predicting the value of one component conditional on the other. The methods are illustrated by application to Australian annual maximum temperature data.     

Testing for bivariate gumbel against bivariate new better than used in expectation

It is shown that a bivariate survival function is both New Better than Used in Expectation (NBUE) and New Worse than Used in Expectation (NWUE) if and only if it is a bivariate Gumbel distribution. Statistical procedures are then presented to test whether that, within the class of bi-variate NBUE survival functions, a survival function is a Gumbel's bivariate exponential.     

A parametric approach to theory of competing risks when the time of death from each cause follows a change-point hazard rate model

The paper a t tempts t o make i n f e r e n c e about the component parameters, based on data from a series system, when the components each follow a different changepoint hazard r a t e model.The paper extends the result of Nattbews and Farewell (1982) to the competing risk framework.