Estimating the Pólya process

Traditionally, a Pólya process is approached from a probability point of view. No prior inference work has been done on them. In this study, we approach the continuous-time Pólya process from an estimation point of view. We construct efficient estimators for the replacement matrix of certain classes of Pólya processes.     

Is there a protective role of testosterone against high-grade prostate cancer? Incidence and severity of prostate cancer in 553 patients who underwent prostate biopsy: a prospective data register

This study investigated the role of testosterone replacement therapy (TRT) in prostate safety and cancer progression. A cohort of 553 patients, 42 treated and 162 untreated hypogonadal men, and 349 eugonadal men were included. Pathological analysis of prostate biopsies examining the incidence and severity of PCa revealed that: 16.7% of treated hypogonadal men had a positive biopsy, a Gleason score of ≤6 in 71.4% and >6 in 28.6% of men, a predominant score of 3 and tumour staging of II in 85.7% men; 51.9% of untreated hypogonadal men had a positive biopsy, a Gleason score of ≤6 in 40.5% and >6 in 59.5% men, a predominant score of 3 (77.4%) and tumour staging of II (41.7%) or III (40.5%); 37.8% of eugonadal men had a positive biopsy, a Gleason score of ≤6 in 42.4% and >6 in 57.6% of men, a predominant score of 3 (82.6%) and tumour staging of II (44.7%) or III (47.7%). The incidence of positive prostate biopsies was lowest in hypogonadal men receiving TRT, with significantly lower severity of PCa in terms of staging and grading in the same group. These results suggest that TRT might have a protective effect against high-grade PCa.     

Preventing diseases of the prostate in the elderly using hormones and nutriceuticals

The prostate has only one function, namely to secrete fluid containing substances that are needed for reproduction. This requires an extremely high concentration of androgens in the tissues. Benign prostatic hypertrophy (BPH) seems to be related to the long-term exposure of the prostate to the strong androgen 5α-dihydrotestosterone (DHT) and, possibly, to estrogens. The relation between prostate cancer and androgens is suggested to be U-shaped, with both extremes of androgen concentrations being associated with increased risk of invasive cancer.

In the treatment of patients with BPH, the lipidic liposterolic extracts of Serenoa repens were as effective as the pharmaceutical inhibitors of the 5α-reductase enzyme or α₁-adrenergic blockers in relieving urinary symptoms. In addition to moderately inhibiting the 5α-reductase activity, Serenoa seems to exert anti-inflammatory and complementary cellular actions with beneficial effects on the prostate. Unlike the pharmaceutical 5α-reductase inhibitors, finasteride and dutasteride, Serenoa does not suppress serum PSA, facilitating the follow-up and the early detection of prostate cancer.

We suggest a strategy to prevent prostate cancer that aims at providing men with partial androgen deficiency correct testosterone substitution with a sustained release buccal bio-adhesive tablet. In addition, food supplementation with extracts of Serenoa repens and a combination of the antioxidants selenium, (cis)-lycopene and natural vitamin E, together with fish oil rich in long-chain polyunsaturated essential fatty acids of the omega-3 group seems warranted. Clearly, a holistic approach including careful clinical and biological monitoring of the aging man and his prostate remains mandatory.     

Doppelganger: Twins' Disruption of the Assumptions of Constancy and Uniqueness of Self in Everyday Life

The ubiquitous presence of the assumptions of constancy and uniqueness of self in everyday life renders them virtually undetectable. A radical disruption of these assumptions through an experiment involving identical twins lays bare the varieties of “extrinsic” and “intrinsic” rationalizations and convictions concerning the performer and the audience that protect the above dual assumptions of social cognition and communication.     

Testing fuzzy hypotheses based on vague observations: a <Emphasis Type="Italic">p</Emphasis>-value approach

This paper deals with the problem of testing statistical hypotheses when both the hypotheses and data are fuzzy. To this end, we first introduce the concept of fuzzy p-value and then develop an approach for testing fuzzy hypotheses by comparing a fuzzy p-value and a fuzzy significance level. Numerical examples are provided to illustrate the approach for different cases.     

On generalized order statistics from linear exponential distribution and its characterization

In this paper, recurrence relations for single and product moments of generalized order statistics (gOSs) from linear exponential distribution (LE) are derived and characterizations of this distribution based on the conditional moments of the gOSs are given.     

Likelihood Inference for Spatial Generalized Linear Mixed Models

Spatial modeling is widely used in environmental sciences, biology, and epidemiology. Generalized linear mixed models are employed to account for spatial variations of point-referenced data called spatial generalized linear mixed models (SGLMMs). Frequentist analysis of these type of data is computationally difficult. On the other hand, the advent of the Markov chain Monte Carlo algorithm has made the Bayesian analysis of SGLMM computationally convenient. Recent introduction of the method of data cloning, which leads to maximum likelihood estimate, has made frequentist analysis of mixed models also equally computationally convenient. Recently, the data cloning was employed to estimate model parameters in SGLMMs, however, the prediction of spatial random effects and kriging are also very important. In this article, we propose a frequentist approach based on data cloning to predict (and provide prediction intervals) spatial random effects and kriging. We illustrate this approach using a real dataset and also by a simulation study.     

Semi‐parametric small‐area estimation by combining time‐series and cross‐sectional data methods

In survey sampling, policymaking regarding the allocation of resources to subgroups (called small areas) or the determination of subgroups with specific properties in a population should be based on reliable estimates. Information, however, is often collected at a different scale than that of these subgroups; hence, the estimation can only be obtained on finer scale data. Parametric mixed models are commonly used in small‐area estimation. The relationship between predictors and response, however, may not be linear in some real situations. Recently, small‐area estimation using a generalised linear mixed model (GLMM) with a penalised spline (P‐spline) regression model, for the fixed part of the model, has been proposed to analyse cross‐sectional responses, both normal and non‐normal. However, there are many situations in which the responses in small areas are serially dependent over time. Such a situation is exemplified by a data set on the annual number of visits to physicians by patients seeking treatment for asthma, in different areas of Manitoba, Canada. In cases where covariates that can possibly predict physician visits by asthma patients (e.g. age and genetic and environmental factors) may not have a linear relationship with the response, new models for analysing such data sets are required. In the current work, using both time‐series and cross‐sectional data methods, we propose P‐spline regression models for small‐area estimation under GLMMs. Our proposed model covers both normal and non‐normal responses. In particular, the empirical best predictors of small‐area parameters and their corresponding prediction intervals are studied with the maximum likelihood estimation approach being used to estimate the model parameters. The performance of the proposed approach is evaluated using some simulations and also by analysing two real data sets (precipitation and asthma).