These notes descibe various simple models and methods for analysis of longitudinal data and show how the analyses can be carried out using SAS. The descriptions require some knowledge of analysis of variance, also with random eeects as in split-plot experiments, in particular. Knowledge of multivariate analysis is not required, and the plain multivariate analysis of variance , treating each ser...

Statistical data are frequently not precise numbers but more or less non-precise, also called fuzzy. Measurements of continuous variables are always fuzzy to a certain degree. Therefore histograms and generalized classical statistical inference methods for univariate fuzzy data have to be considered. Moreover Bayesian inference methods in the situation of fuzzy a-priori information and fuzzy da...

The GS-distribution is a family of distributions that provide an accurate representation of any unimodal univariate continuous distribution. In this contribution we explore the utility of this family as a general model in survival analysis. We show that the survival function based on the GS-distribution is able to provide a model for univariate survival data and that appropriate estimates can b...

The study of extreme phenomena in hydrology generally involves frequency analysis and a time series analysis. In this article we provide enough mathematics to enable researchers apply wide range probability distributions analyses hydrological drought. presents drought methodology for the determination minimum annual flows, durations deficit volumes exceedance probabilities common water manageme...

background: based on some estimation more than two million peoples in iran are affected by type 2 diabetes. the present study was designed to evaluate the status of diabetes control among type 2 diabetes patients in kurdistan, west of iran and its associated factors. methods: in our cross sectional study conducted in 2010, 411 type 2 diabetes patients were randomly recruited from sanandaj, capi...