... sandwich estimate of variance of Newey–West type with Anderson quadratic weights for the first two lags. . glm die anterior hcabg kk2 kk3 kk4 age2-age4, > nwest(anderson 2) nolog Generalized linear models family(bin cases) l(loglog) ...
For example, model diagnostics may be calculated and interpreted similarly regardless of the assumed distribution. This text thoroughly covers GLMs, both theoretically and computationally, with an emphasis on Stata.
Generalized Linear Models and Extensions
This book presents a thorough examination of generalized linear model (GLM) estimation methods as well as the derivation of all major GLM families.
For the logistic regression model, m, = logs/ti/(1 – sti)], so that onl/07t; = 1/[st;(1 – st;)]. Thus, w; = not (1 – sti), and for large samples, ... For example, to test Ho: s', = 0, the Wald chi-squared (df = 1) uses (ff.
... USA Statistical Theory: A Concise Introduction F. Abramovich and Y. Ritov Practical Multivariate Analysis, ... Ideas and Data Analysis: An Introduction for Scientists and Statisticians R. Christensen, W. Johnson, A. Branscum, ...
The 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.
This book provides a well-stocked toolbox of methodologies, and with its unique presentation of these very modern statistical techniques, holds the potential to break new ground in the way graduate-level courses in this area are taught.
The 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.
Pearson 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 ...