Office of Academic Resources
Chulalongkorn University
Chulalongkorn University

Home / Help

AuthorLindsey, James K. author
TitleApplying Generalized Linear Models [electronic resource] / by James K. Lindsey
ImprintNew York, NY : Springer New York, 1997
Connect to
Descript XIV, 256 p. online resource


Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liรจge, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books


Generalized Linear Modelling: Statistical Modelling -- Exponential Dispersion Models -- Linear Structure -- Three Components of a GLM -- Possible Models -- Inference -- Exercises. Discrete Data: Log Linear Models -- Models of Change -- Overdispersion -- Exercises. Fitting and Comparing Probability Distributions: Fitting Distributions -- Setting Up the Model -- Special Cases -- Exercises. Growth Curves: Exponential Growth Curves -- Logistic Growth Curve -- Gomperz Growth Curve -- More Complex Models -- Exercises. Time Series: Poisson Processes -- Markov Processes -- Repeated Measurements -- Exercises. Survival Data: General Concepts -- 'Nonparametric' Estimation -- Parametric Models -- 'Semiparametric' Models -- Exercises. Event Histories: Event Histories and Survival Distributions -- Counting processes -- Modelling Event Histories -- Generalizations -- Exercises. Spatial data: Spatial Interaction -- Spatial Patterns -- Exercises. Normal Models: Linear Regression -- Analysis of Variance -- Nonlinear Regression -- Exercises. Dynamic Models: Dynamic Generalized Linear Models -- Normal Models -- Count Data -- Positive Response Data -- Continuous Time Nonlinear Models. Appendices: Inference -- Diagnostics -- References -- Index

Mathematics Probabilities Statistics Mathematics Probability Theory and Stochastic Processes Statistical Theory and Methods Statistics for Life Sciences Medicine Health Sciences


Office of Academic Resources, Chulalongkorn University, Phayathai Rd. Pathumwan Bangkok 10330 Thailand

Contact Us

Tel. 0-2218-2929,
0-2218-2927 (Library Service)
0-2218-2903 (Administrative Division)
Fax. 0-2215-3617, 0-2218-2907

Social Network


facebook   instragram