Visceral adiposity index is associated with premature ejaculation inversely: a cross-sectional study

Objective: Visceral adiposity index (VAI) is a novel indicator for the assessment of visceral obesity. In this study, we aimed to evaluate the relationship between VAI and premature ejaculation (PE).

Materials and method: A total of 300 men were included in the study. Hundred and fifty men with PE and 150 men without PE (control). All men were evaluated for PE by premature ejaculation diagnostic tool (PEDT). VAI levels were calculated using body mass index (BMI), high density lipoprotein and triglyceride (TG) levels.

Results: Mean age of the study groups was 34.3?±?5.2 (30–60) years and the mean age of the controls were 35.9?±?5.3 (30–60) years. The men with PE had lower BMI, TG levels, waist circumference (WC) and higher high-density lipoprotein-cholesterol (HDL-C) levels. Mean VAI level was 4.13?±?0.7 in study group and 5.72?±?1.6 in control group, respectively. VAI levels were statistically higher in men without PE (p?Discussion: Our cross-sectional study demonstrated a negative correlation between VAI and PE. VAI is superior index for the evaluation and calculation the relationship between obesity and PE.     

Externaliser la défense : la politique américaine

This analysis of the thoroughgoing change effected in the US defense industry shows that the Pentagon’s traditional partners are taking a back seat behind private, for-profit service providers. These firms, which provide military services and the “information technology” necessary for modern warfare, now play a key role in the American national security system. Among the factors accounting for this unprecedented sharing of a classical government prerogative with private firms are the redefinition of the government’s role, the technological revolution and the strategic environment related to the global war against terrorism. This role-sharing brings new forces into play. The Defense Department is externalizing strategic activities without all the legislative and institutional means for regulating them, whence the risk of a crisis in the military establishment. The mixed systems coming out of this change are a driving force in altering the civilian and military capability to project power and intervene in the world.     

Small sample distribution of the likelihood ratio test in the random effects model

In this paper we examine the small sample distribution of the likelihood ratio test in the random effects model which is often recommended for meta-analyses. We find that this distribution depends strongly on the true value of the heterogeneity parameter (between-study variance) of the model, and that the correct p-value may be quite different from its large sample approximation. We recommend that the dependence of the heterogeneity parameter be examined for the data at hand and suggest a (simulation) method for this. Our setup allows for explanatory variables on the study level (meta-regression) and we discuss other possible applications, too. Two data sets are analyzed and two simulation studies are performed for illustration.     

Optimal Designs for Binary Logistic Regression with a Qualitative Classifier with Independent Levels

Dose response studies arise in many medical applications. Often, such studies are considered within the framework of binary-response experiments such as success-failure. In such cases, popular choices for modeling the probability of response are logistic or probit models. Design optimality has been well studied for the logistic model with a continuous covariate. A natural extension of the logistic model is to consider the presence of a qualitative classifier. In this work, we explore D-, A-, and E-optimal designs in a two-parameter, binary logistic regression model after introducing a binary, qualitative classifier with independent levels.     

Functional logistic regression: a comparison of three methods

Functional logistic regression is becoming more popular as there are many situations where we are interested in the relation between functional covariates (as input) and a binary response (as output). Several approaches have been advocated, and this paper goes into detail about three of them: dimension reduction via functional principal component analysis, penalized functional regression, and wavelet expansions in combination with Least Absolute Shrinking and Selection Operator penalization. We discuss the performance of the three methods on simulated data and also apply the methods to data regarding lameness detection for horses. Emphasis is on classification performance, but we also discuss estimation of the unknown parameter function.     

Christ vs. Communism: Communism as a Religious Social Problem in Finland's Proto‐Fascist Lapua Movement in the 1930s

This article traces the emergence of religious anti‐communist discourse in Finland's proto‐fascist Lapua Movement in the 1930s. Applying constructionist social problems theory, it discusses the constructions of communism as a religious social problem, Christian piety as a solution to the problem of godless communism, and the religious legitimation of violence. The article argues that by identifying Christianity with the Finnish nation the construction of communism as a religious problem—itself an outcome of the influence of revivalist Lutheran ministers in the leadership of the movement—resonated with the broader audience, but that this indigenous religious nationalism lost support with the increasing belligerence of the movement.