rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Applying Generalized Linear Models
  name:
    name part: Lindsey, James K.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 1997
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIV, 256 p. online resource.
  abstract: 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 Liège, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books.
  table of contents: 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.
  note: by James K. Lindsey.
  subject:
    topic: Mathematics
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Texts in Statistics
  identifier: 9780387227306
  identifier: http://dx.doi.org/10.1007/b98856
  record info:
    record creation date: 100301
    record change date: 20151204164821.0
    record identifier: 978-0-387-22730-6