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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.
calculate absorbance value from concentration
Comparative exposure rate : A measure of alliance for use in a matched case-control study, de?ned as the ratio of the number of case-control pairs, where the case has greater expos
The plot of the number of cases of the disease against the time period. A large and sudden increase corresponds to an epidemic. The example of this is shown in the figure drawn bel
Chebyshev's inequality: A statement about the proportion of the observations which fall within some number of the standard deviations of the mean for any of the probability distri
An unusual aggregation of the health events, real or perceived. The events might be grouped in the particular region or in some short period of time, or they might happen among the
The tabulation of a sample of observations in terms of numbers falling below particular values. The empirical equivalent of the growing probability distribution. An example of such
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 regre
The Null Hypothesis - H0: There is no first order autocorrelation The Alternative Hypothesis - H1: There is first order autocorrelation Durbin-Watson statistic = 1.98307
Non-identified response is a term used to signify censored observations in survival data, which are not independent of the endpoint of the interest. Such observations can happen f
What is the EM?
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