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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.
The interplay of the genes and environment on, for instance, the risk of disease. The term represents the step away from the argument as to whether the nature or nurture is the pre
Clinical vs. statistical significance : The distinction among results in terms of their possible clinical importance rather than simply in terms of their statistical importance. Wi
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It is the technique used in the clinical trials when it is possible to make an acceptable place before an active treatment but not to make the two active treatments identical. In t
Regression line drawn as y= c+ 1075x ,when x was2, and y was 239,given that y intercept was 11. Calculate the residual ?
Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the
Mention the characteristics of Statistics. Explain any two applications of Statistics.
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
Designs which permits two or more questions to be addressed in the investigation. The easiest factorial design is one in which each of the two treatments or interventions are p
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