Statistical data contains noise. Smoothing is used to smooth out these noises and present the data as a meaningful one. Kernel methods are nonparametric smoothing tools that can reveal structural features in the data which may not be possible with a parametric approach. This paper applies Epanechnikov kernel method of data smoothing to smooth out the dropout rates of the children with disabilit...

In this paper we study the importance of possible non-random attrition on variations in psychiatric morbidity using data from the first eight waves of the British Household Panel Study. To study attrition we use the model of Hausman and Wise (1979) which applies to continuous longitudinal data with nonignorable or informative dropout. The model combines a multivariate linear model for the under...

CONTEXT Dropout rates in randomized clinical trials of antipsychotic drugs have consistently been reported to be high, and the use of a placebo-controlled design is hypothesized to be one of the reasons for this. OBJECTIVE To investigate this hypothesis in a meta-analysis of available data from pertinent clinical trials. DATA SOURCES Comprehensive search of PubMed- and MEDLINE-listed journa...

<span lang="EN-US">Implementation of data mining, machine learning, and statistical from educational department commonly known as mining. Most school systems require a teacher to teach number students at one time. Exam are regularly being use method measure student’s achievement, which is difficult understand because examination cannot be done easily. The other hand, programming classes m...