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Clinical vs. statistical significance: The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. With large samples, for instance, very small differences which have little or no clinical importance may turn out to be the statistically signi?cant products. The practical implications of any ?nding in the medical investigation should be judged on the clinical as well as the statistical grounds.
Cohort study : An investigation in which the group of individuals (or the cohort) is identi?ed and followed prospectively, possibly for many years, and their subsequent medical his
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
Zero sumgame is a game played by the number of persons in which the winner takes all stakes given by the losers so that the algebraic sum of gains at any stage is zero. Number of
The division of a sample of observations into several classes, together with the number of observations in each of them. It acts as a useful summary of the main features of the da
Non linear mapping (NLM ) is a technique for obtaining a low-dimensional representation of the set of multivariate data, which operates by minimizing a function of the differences
The diagnostic tools or devices used to approach the closeness to the linearity of the non-linear model. They calculate the deviation of so-called expectation surface from the plan
Correlation matrix : A square, symmetric matrix with the rows and columns corresponding to the variables, in which the non diagonal elements are correlations between the pairs of t
Multivariate analysis of variance is the procedure for testing equality of the mean vectors of more than two populations for the multivariate response variable. The method is dire
Nuisance parameter : The parameter of the model in which there is no scienti?c interest but whose values are generally required (but in usual are unknown) to make inferences about
An approach of using the likelihood as the basis of estimation without the requirement to specify a parametric family for data. Empirical likelihood can be viewed as the example of
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