Modeling experimental and observational data


Modeling experimental and observational data

Clifford E. Lunneborg

Duxbury Press, c1994

大学図書館所蔵 件 / 3



Includes bibliographical references and index



This book shows readers how modelling is a useful and powerful tool in the applied sciences. Lunneborg's approach emphasizes understanding regression analysis of variance concepts by way of example and explanation rather than rote computation.


  • Models for experimental and observational data
  • The measured response variable
  • Simple linear regression: an introduction
  • Simple linear regression: estimation
  • Simple linear regression: inference about models
  • Categorical explanatory variables: one way ANOVA
  • Several explanatory variables: multiple regression
  • Comparing fuller with less full models
  • Assessing a model's adequacy: individual observations
  • Assessing a model's adequacy: checking assumptions
  • Categorical explanatory variables: ANOVA models
  • Auxiliary variable models: enhancing model sensitivity
  • Auxiliary variable models: moderating the influence of an explanatory variable
  • Introduction to modelling: repeated observations
  • The categorical response variable: characteristics
  • Logistic regression: modelling the properties of success
  • Grouped logistic regression and multiple explanatory variable models
  • Logistic regression for multiple response categories
  • Poisson regression for counted responses in time series.

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