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Many authors have reported that Prostate Cancer (PC) and Cardiovascular Disease (CVD) are strongly associated, while it is not yet well established. The current report examines this fundamental query by examining the associations of a PC biomarker known as serum Prostatic Acid Phosphatase (PAP) with CVD risk factors such as Diastolic Blood Pressure (DBP), Systolic Blood Pressure (SBP), along with CVD history, and classified CVD patients based on Electrocardiogram (EKG) status, and conversely. It is derived herein that PAP has no association with SBP and DBP, while the mean PAP level is significantly higher for non-CVD subjects (P=0.0179), than for CVD patients. The variance of PAP level is significantly more scattered for CVD patients (P=0.0190) than normal, and also it is significantly more scattered for normal subjects based on EKG (P=0.0249), than the others. On the other hand, the mean and variance of DBP have no relation with PAP. Only the variance of DBP is significantly more scattered for normal subjects (P=0.0004) than PC patients, and it is significantly more scattered for PC patients with bone metastases (BM) (P=0.0021) than normal. Again, mean SBP decreases (P=0.0621) if PAP rises, while it increases as the primary tumor size (P=0.0054) increases. A similar association is observed for the variance of SBP with PAP, that is SBP variance is negatively associated with PAP (P=0.0045). It can be concluded that the association between PC and CVD exists, which should be considered for the medical treatment process. [ABSTRACT FROM AUTHOR]

Ridge regression techniques have been extensively used to solve the multicollinearity problem for both linear and non-linear regression models since its inception. This paper studied different ridge regression t-type tests of the individual coefficients of a linear regression model. A simulation study has been conducted to evaluate the performance of the proposed tests with respect to their sizes and powers under different settings of the linear regression model. Our simulation results demonstrated that most of the proposed tests have sizes close to the 5% nominal level and all tests except tAKS, tkM2 and tkM9 have considerable gain in powers over the ordinary OLS t-type test. It is also observed that some of the proposed test statistics are performing better than the HK and HKB tests which are proposed some authors. [ABSTRACT FROM AUTHOR]

This paper proposes three alternative confidence intervals namely, AADM-t, MAAD-t and MADM-t, which are simple adjustments to the Student-t confidence interval for estimating the population mean of a positively skewed distribution. The proposed methods are very easy to calculate and are not overly computer-intensive. The performance of these confidence intervals was compared through a simulation study using the following criterion: (a) coverage probability (b) average width and (c) coefficient of variation of width. Simulation studies indicate that for small sample sizes and moderate/highly positively skewed distributions, the proposed AADM-t confidence interval performs the best and it is as good as the Student-t confidence interval. Some real-life data are analyzed which support the findings of this paper to some extent. [ABSTRACT FROM AUTHOR]