TY  - BOOK
AU  - Hodges,James S.
TI  - Richly parameterized linear models: additive, time series, and spatial models using random effects 
T2  - Chapman & Hall/CRC texts in statistical science series
SN  - 9781439866832 (hbk. : alk. paper)
U1  - 000SA.062 23
PY  - 2014///
CY  - Boca Raton
PB  - CRC Press
KW  - Regression analysis
KW  - Linear models (Statistics)
KW  - MATHEMATICS / Probability & Statistics / General
N1  - Includes bibliographical references (pages 413-424) and indexes; I. Mixed Linear Models: Syntax, Theory, and Methods

1. An Opinionated Survey of Methods for Mixed Linear Models--
2. Two More Tools: Alternative Formulation, Measures of Complexity--

II Richly Parameterized Models as Mixed Linear Models--
3. Penalized Splines as Mixed Linear Models--
4. Additive Models and Models with Interactions--
5. Spatial Models as Mixed Linear Models--
6. Time-Series Models as Mixed Linear Models--
7. Two Other Syntaxes for Richly Parameterized Models--

III Form Linear Models to Richly Parameterized Models: Mean Structure--
8. Adapting Diagnostics from Linear Models--
9. Puzzles from Analyzing Real Datasets--
10. A Random Effect Competing with a Fixed Effect--
11. Differential Shrinkage--
12. Competition between Random Effects--
13. Random Effects Old and New--
Exercises--

N2  - "This book covers a wide range of statistical models, including hierarchical, hierarchical generalized linear, linear mixed, dynamic linear, smoothing, spatial, and longitudinal. It presents a framework for expressing these richly parameterized models together as well as tools for exploring and interpreting the results of fitting the models to data. It extends the standard theory of linear models and illustrates the advantages and disadvantages of various theories. The book also examines surprising or undesirable results arising in the use of the models to analyze real data sets from collaborative research"--
ER  -