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Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probability 1 p a random variable with the Poisson distribution is observed. For instance, when manufacturing equipment is properly aligned, defects might be almost impossible. But when it is misaligned, defects might happen according to a Poisson distribution. Both probability p of the perfect zero defect state and the mean number of defects λ in the imperfect state might depend on covariates. The parameters in this type of models can be estimated using maximum likelihood estimation.
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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The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult
This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p
Hello-goodbye effect : The phenomenon initially described in psychotherapy research, but one which might arise whenever a subject is assessed on two occasions, with some interventi
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
The term used for the estimation of the misclassification rate in the discriminant analysis. Number of techniques has been proposed for two-group situation, but the multiple-group
The studies conducted in the pharmaceutical industry to calculate the degradation of the new drug product or an old drug formulated or packaged in the new manner. The main study ob
Matching is the method of making a study group and a comparison group comparable with respect to the extraneous factors. Generally used in the retrospective studies when selecting
Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing
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