| University Libraries
Software-independent -- For those who need to do multiple or other multivariate regression, especially those doing clinical research or biostatistics. It also includes chapters on Propensity scores and Correlated observations:
Multivariable Analysis by
Now in its third edition, this highly successful text has been fully revised and updated with expanded sections on cutting-edge techniques including Poisson regression, negative binomial regression, multinomial logistic regression and proportional odds regression. As before, it focuses on easy-to-follow explanations of complicated multivariable techniques. It is the perfect introduction for all clinical researchers. It describes how to perform and interpret multivariable analysis, using plain language rather than complex derivations and mathematical formulae. It focuses on the nuts and bolts of performing research, and prepares the reader to set up, perform and interpret multivariable models. Numerous tables, graphs and tips help to demystify the process of performing multivariable analysis. The text is illustrated with many up-to-date examples from the medical literature on how to use multivariable analysis in clinical practice and in research.
A Question-and-Answer format helps make this book a great reference for all your Regression questions. Written for clinical research and biostatistics, but globally useful.
Software-inclusive -- For those using any software and doing multi-level or mixed models:
Multilevel Modeling: Applications in STATA, SPSS, SAS, R & HLM by
Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R & HLM(tm) provides a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences. Author G. David Garson's step-by-step instructions for software walk readers through each package. The instructions for the different platforms allow students to get a running start using the package with which they are most familiar while the instructor can start teaching the concepts of multilevel modeling right away. Instructors will find this text serves as both a comprehensive resource for their students and a foundation for their teaching alike.
A practically-focused book covering a basic multi-level model, through generalized linear mixed models, with a comparison of and then complete example for each software.
These have code in R, and others as specified:
LEMMA: Learning Environment for Multilevel Methods and Applications - See course topics
Free (requires registration) course from the basics through multiple regression, then multiple types of multi-level models. Has exercises in MLwiN, Stata, and R. Assumes some prior knowledge, but has a pre-test and reviews much.
Statistics for Linguists: An Introduction Using R by