TY  - BOOK
AU  - Gelman,Andrew
AU  - Hill,Jennifer
TI  - Data analysis using regression and multilevel/hierarchical models
T2  - Analytical methods for social research
SN  - 9780521867061 (hbk.) :
AV  - HA31.3 .G45 2006
U1  - 519.536 GEL 
PY  - 2007///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Regression analysis
KW  - Multilevel models (Statistics)
KW  - Mathematics
KW  - ukslc
KW  - Social research & statistics
KW  - thema
KW  - Psychological testing & measurement
KW  - Probability & statistics
KW  - Calculus & mathematical analysis
N1  - Includes bibliographical references; 1.Why? -- 2.Concepts and methods from basic probability and statistics -- Part 1A: Single-level regression -- 3.Linear regression: the basics -- 4.Linear regression: before and after fitting the model -- 5.Logistic regression -- 6.Generalized linear models  -- Part 1B: Working with regression inferences -- 7.Simulation of probability models and statistical inferences -- 8.Simulation for checking statistical procedures and model fits  -- 9.Casual inference using regression on the treatment variable -- 10.Casual inference using mode advanced models -- Part 2.Multivlevel structures -- 12.Multilevel linear models: the basics -- 13.Multilevel linear models: varying slops, non-rest models and other complexities -- 14. Multilevel logistic regression -- 15.Multilevel generalized linear models - Part 2B: Fitting multilevel models -- 16.Multilevel modeling in Bugs and R: the basics -- 17.Fitting multilevel linear and generalized linear models in Bugs and R -- 18.Likelihood and Bayesian inference and computation 19.Debugging and speeding convergence -- Part 3: From data collection to model understanding to model checking -- 20.Sample size and power calculations -- 21.Understanding and summarizing the fitted models -- 22.Analysis of variance -- 23.Casual inference using multilelvel models -- 24.Model checking and comparison --25.Missing-data imputation
N2  - No further information has been provided for this title
ER  -