Applied Linear Statistical Models (Paperback, 5th Edition)

Part1 Simple Linear Regression 1 Linear Regression with One Predictor Variable 2 Inferences in Regression Analysis 3 Diagnostics and Remedial Measures 4 Simultaneous Inferences and Other topics in Regression Analysis 5 Matrix Approach to Simple Linear Regression Analysis Part 2 Multiple Linear Regression 6 Multiple Regression I 7 Multiple Regression II 8 Regression Models for Quantitative and Qualitative Predictors 9 Building the Regression Model I: Model Selection and Validation 10Building the Regression Model II: Diagnostics 11Building the Regression Model III: Remedial Measures 12Autocorrelation in Time Series Data Part 3NonLinear Regression 13Introduction to NonLinear Regression and Neural Networks 14Logistic Regression, Poisson Regression, and Generalized Linear Models Part 4 Single Factor Studies 15Introduction to the Design of Experiments 16Analysis of Single-Factor Studies 17Analysis of Factor Level Effects in Single Factor Studies 18ANOVA Diagnostics and Remedial Measures Part 5 Two -Factor Studies and Blocking 19Two -Factor Studies- Equal Sample Sizes 20 Two -Factor Studies-One Case per Cell 21 Randomized Complete Block Designs and the Analysis of Covariance 22Two -Factor Studies-Unequal Sample Sizes and Unequal Treatment Importance Part 6 Multifactor Studies 23 Multifactor Studies 24Random and Mixed-Effects Models 25Nested Designs, Subsampling, and Partially Nested Designs 26Repeated Measures and Related Designs 27Latin Square, Balanced Incomplete Block, and Related Designs 28Exploratory Experiments-Two-Level Factorial and Fractional Factorial Designs 29Response Surface Experiments