This work describes several statistical techniques for studying repeated measures data, presenting growth curve methods applicable to biomedical, social, animal, agricultural and business research. It details the multivariate development of growth science and repeated measures experiments, covering time-moving covariates, exchangable errors, bioassay results, missing data procedures and nonparametric and Bayesian methods.
For professionals and graduate students in statistics, and experimental scientists interested in analyzing correlated data, describes several statistical techniques for studying repeated measures data, and presents growth curve methods applicable to biomedical, social, animal, agricultural, and business research. Among the models described are the multidimensional, the sum of profiles and time moving, Potthoff-Roy, and nonparametric. Includes three case studies involving the eyes of dogs, the diet of quarter horses, and suctioning in intensive care. Annotation copyright Book News, Inc. Portland, Or.