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Poisson regression
In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regression is used when the response to model is counts which typically follow a Poisson distribution. Examples include colony counts for bacteria or viruses, accidents, equipment failures, insurance claims, incidence of disease. Interest often lies in estimating a rate of incidence and determining its relationship to a set of explanatory variables. Again, an IRLS procedure is used to ?nd the MLE estimators of the β coeffcients. When we can not assume φ = 1, (this is the case of over- or under- dispersion discussed in McCullagh and Nelder (1989)), the iterative procedure is changed to so called "quasi-likelihood estimation". Finally in this section, we shall also mention shortly the extension of GLM to GAM.
Missing values : The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the stud
Longitudinal data : The data arising when each of the number of subjects or patients give rise to the vector of measurements representing same variable observed at the number of di
Procrustes analysis is a technique of comparing the alternative geometrical representations of a group of multivariate data or of the proximity matrix, for instance, two competing
Half-normal plot is a plot for diagnosing the model inadequacy or revealing the presence of outliers, in which the absolute values of, for instance, the residuals from the multipl
A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how t
Multicentre study : The clinical trial conducted simultaneously in the number of participating hospitals, with all centres following an agreed-upon study of the protocol and with
Balanced incomplete repeated measures design (BIRMD): An arrangement of the N randomly selected experimental units and k treatments in which each and every unit receives k1 treatm
Continual reassessment method: An approach which applies Bayesian inference for determining the maximum tolerated dose in a phase I trial. The method starts by assuming a logistic
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A subject who withdraws from the study for whatever reason, adverse side effects, noncompliance, moving away from the district, etc. In number of cases the reason may not be known.
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