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Greenhouse geissercorrection is the method of adjusting the degrees of freedom of the within- subject F-tests in the analysis of the variance of longitudinal data so as to allow the possible departures of the variance-covariance matrix of the measurements from the suppositions of sphericity. If this condition holds for data then the correction factor is one and the easy F-tests are valid. Departures from the sphericity result in the estimated correction factor less than one, hence reducing the degrees of freedom of the appropriate F-tests.
how to constuct design matrix
Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of
Hazard function : The risk which an individual experiences an event in a small time interval, given that the individual has survived up to the starting of the interval. It is th
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
A mixture of benzene, toluene, and xylene enters a two-stage distillation process where some of the componentsare recovered. The distillation process operates at steady-state condi
a researcher is interested in whether students who attend privte high schools have higher average SAT Scores than students in the general population. a random sample of 90 student
Hello, I have a solution for a Survey Design (proposal) assignment and looking for an expert that can look at it and correct it in case if it is wrong. Do you have this kind of ser
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
Marginal matching is the matching of the treatment groups in terms of means or other summary characteristics of matching variables. This has been shown to be almost as efficient a
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
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