Generalized Linear Models
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Generalized Linear Models: with Applications in Engineering and the Sciences
By Douglas C. Montgomery, G. Geoffrey Vining, Raymond H. Myers31 proc logistic data=sentence descending; title3 ' Example For Pearson Chi-Square and Deviance ' ; model prison=ibus iprior / aggregate scale=N ; weight count; output out=home . good ...
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Generalized Linear Models: A Unified Approach
By Jeff Gill, Michelle TorresPearson residuals are an attempt to provide some sense of scale to the response residual by dividing by the standard error of the prediction. The name comes from the fact that the sum of the Pearson residuals for a Poisson generalized ...
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Generalized Linear Models: A Unified Approach
By Jeff GillThe author explains the theoretical underpinnings of generalized linear models so that researchers can decide how to select the best way to adapt their data for this type of analysis.
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Generalized Linear Models
By P. McCullaghThe success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data.
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Generalized Linear Models: A Unified Approach
By Jeff GillThe author explains the theoretical underpinnings of generalized linear models so that researchers can decide how to select the best way to adapt their data for this type of analysis.
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Generalized Linear Models: A Bayesian Perspective
By Bani K. Mallick, SUJIT K. GHOSH, Dipak K. DeyThis volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation.
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Generalized Linear Models
By P. McCullaghThe success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data.
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Generalized Linear Models: An Applied Approach
By John Patrick HoffmannThis brief and economical text shows students with relatively little mathematical background how to understand and apply sophisticated linear regression models in their research areas within the social, behavioral, and...
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Generalized Linear Models: A Unified Approach
By Jeff Gill, Michelle TorresOften the best way to understand generalized linear models with interaction effects is by using first differences. As described in Chapter 5, the principle of first differences is to select two levels of interest for a given explanatory ...
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Generalized Linear Models: A Unified Approach
By Jeff Gill, Michelle Torres, Professor Jefferson M Gill... Regression: A Mathematical Introduction Gujarati Propensity Score Methods and Applications Bai/Clark Multilevel ... Effects in Logistic Regression Jaccard Missing Data Allison Spline Regression Models Marsh/Cormier Logit and Probit ...
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Generalized Linear Models
By Jeff Gill, Michelle TorresAlthough these specifications are unnecessarily treated as distinct and particular, they are all part of the generalized linear models (GLMs), a class of regression models that share a common theoretical basis and structure.
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Generalized Linear Models
By John A. Nelder, P. McCullaghGeneralized Linear Models