Over dispersion, Advanced Statistics

Over dispersion is the phenomenon which occurs when empirical variance in the data exceeds the nominal variance under some supposed model. Most often encountered when the modeling data which occurs in the form of proportions or counts, where it is frequently observed that there is more variation than, for instance, an assumed binomial distribution can accommodate.

There might be a variety of relatively easy reasons of the amplified variation, ranging from the presence of one or more outliers, to the mis-specification of model being applied to the data. If none of these explanations could explain the phenomenon then it is likely that it is due to the variation between the response probabilities or correlation between the binary responses, in which case particular modelling procedures might be required. 


Posted Date: 7/30/2012 7:48:50 AM | Location : United States

Related Discussions:- Over dispersion, Assignment Help, Ask Question on Over dispersion, Get Answer, Expert's Help, Over dispersion Discussions

Write discussion on Over dispersion
Your posts are moderated
Related Questions
Response surface methodology (RSM): The collection of the statistical and mathematical methods useful for improving, developing, and optimizing processes with significant applicat

Please help with following problem: : Let’s consider the logistic regression model, which we will refer to as Model 1, given by log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.

Back-projection: A term most often applied to the procedure for reconstructing plausible HIV incidence curves from the AIDS incidence data. The method or technique assumes that th

Independent component analysis (ICA) is the technique for analyzing the complex measured quantities thought to be mixtures of other more fundamental quantities, into their fundamen

The Current status data arise in the survival analysis if the observations are limited to the indicators of whether or not the event of interest has happened at the time the sample

Classification matrix: A term many times used in discriminant analysis for the matrix summarizing the results and outputs obtained from the derived classi?cation rule, and obtaine

The theorem relating structure of the likelihood to the concept of the sufficient statistic. Officially the necessary and sufficient condition which a statistic S be sufficient for

Residual plots are the plots of some type of residual which might be helpful in assessing the assumption made by the fitted model. In regression analysis there are various method

Mosaic displays  is the graphical display of the standardized residuals from the fitting a log-linear model to a contingency table in which the colour and outline of the mosaic's '