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High-dimensional data: This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21st century\ such data sets are collected in number of areas, such as, text/web data mining and bioinformatics. The job of extracting meaningful statistical and biological information from such data sets present many challenges for which a number of recent methodological developments, for instance, sure screening methods, lasso, and Dantzig selector, might be quite helpful.
Confidence profile method : A Bayesian approach to meta-analysis in which the information in each piece of the evidence is captured in the likelihood function which is then used al
Lancaster models : The means of representing the joint distribution of the set of variables in terms of the marginal distributions, supposing all the interactions higher than a par
Atomistic fallacy : A fallacy which arises because of the association between two variables at the individual level might vary from the association between the same two variables m
Projection pursuit is a procedure for attaning a low-dimensional (usually two-dimensional) representation of the multivariate data, which will be particularly useful in revealing
It is an informal method of assessing the effect of the publication bias, generally in the context of the meta-analysis. The effect measures from each of the reported study are plo
The linear component ηi, de?ned just in the traditional way: η i = x' 1 A monotone differentiable link function g that describes how E(Yi) = µi is related to the linear compon
McNemar's test is the test for comparing proportions in data involving the paired samples. The test statistic can be given by it is most useful when the data have a symmetri
Component bar chart : A bar chart which shows the component parts of the aggregate represented by the whole length of the bar. The component parts are shown as the sectors of bar w
Complier average causal effect (CACE): The treatment effect amid true compliers in the clinical trial. For the suitable response variable, the CACE is given by the difference in o
Please help with following problem: : Let’s consider the logistic regression model, which we will refer to as Model 1, given by log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.
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