description: Mixed model methods are useful in a variety of applications, including medicine, biostatistics, and agriculture. Mixed Models for Data Analysts balances theory and practice to illustrate and demonstrate mixed model methodology. The authors, all highly regarded researchers in the field, demonstrate the strength of the mixed model approach through numerous examples using S-PLUS and other computer packages. Integration of theory with "how to do it," interesting, real data sets from wide-ranging applications, and computer code available on the Internet make this a valuable guide for researchers and practitioners interested in using linear mixed models.
language: English
title: Mixed Models for Data Analysts
titlecomplete: Mixed Models for Data Analysts (Interdisciplinary Statistics)
publisher: Chapman & Hall/CRC