Continuous data arise in most areas of medicine. Familiar clinical examples include blood pressure, ejection fraction, forced expiratory volume in 1 second (FEV1), serum cholesterol, and anthropometric measurements. Methods for analysing continuous data fall into two classes, distinguished by whether or not they make assumptions about the distribution of the data. Theoretical distributions are ...

this paper examines the accuracy of valuation models in providing reasonable estimation of the market values of listed companies in tehran stock exchange (tse). six valuation models including gordon growth model, two stage dividend discount model, adjusted present value, price to earning ratio and residual income were examined in this study. in addition, three proxies represent the market value...

Methods Patients diagnosed of Juvenile dermatomyositis in La Fe Hospital (Valencia, Spain) since June 1992 to March 2013. Dates are shown in median and interquartile range for non-parametric variables, and for parametric variables is given as mean and standard deviation. To assess response to treatment, we used Wilcoxon test for paired measures of non-parametric variables and t-student for para...

Asymptotic Relative Efficiency ] was pleased to read "Promise in Nonparametrics" by Royeen and Seaver (March, ] 986). As the authors state, analysis of data by non parametric methods when the strong assumptions for parametric counterparts cannot be met provides the researcher with effective statistical procedures that may be more realistic and valid in a given situation. It is also interesting ...

the objective of this study was to compare non-parametric stability procedures, and to apply different non-parametric tests for genotype × environment interaction (g×e) on seed yield data of 17 chickpea genotypes grown during 2004-05 growing seasons in 10 rainfed environments in iran. the non-parametric measures used for g × e interaction were highly significant (p