منابع مشابه
Multivariate Analysis of Repeated Measures Data
ABSTRACT In this paper, we have used SAS software for the multivariate analysis of repeated measures data due to Grizzel and Allen (1969). We have applied four multivariate methods viz MANOVA, Profile Analysis, non-parametric multisample rank sum test and non-parametric multisample median test to analyse two sets of data. The findings of the study reveal that profile analysis gives similar resu...
متن کاملStatistical analysis of repeated measures data using SAS procedures.
Mixed linear models were developed by animal breeders to evaluate genetic potential of bulls. Application of mixed models has recently spread to all areas of research, spurred by availability of advanced computer software. Previously, mixed model analyses were implemented by adapting fixed-effect methods to models with random effects. This imposed limitations on applicability because the covari...
متن کاملAnalysis of repeated measures data with clumping at zero.
Longitudinal or repeated measures data with clumping at zero occur in many applications in biometrics, including health policy research, epidemiology, nutrition, and meteorology. These data exhibit correlation because they are measured on the same subject over time or because subjects may be considered repeated measures within a larger unit such as a family. They present special challenges beca...
متن کاملDiscriminant Analysis for Repeated Measures Data: A Review
Discriminant analysis (DA) encompasses procedures for classifying observations into groups (i.e., predictive discriminative analysis) and describing the relative importance of variables for distinguishing amongst groups (i.e., descriptive discriminative analysis). In recent years, a number of developments have occurred in DA procedures for the analysis of data from repeated measures designs. Sp...
متن کاملRobust descriptive discriminant analysis for repeated measures data
Robust repeated measures discriminant analysis (RMDA) procedures based on parsimonious covariance structures were developed using trimmed estimators. The e ects of non-normality, covariance structure, and mean con guration on bias and root mean square error (RMSE) of RMDA coe cients were studied using Monte Carlo techniques. The bias and RMSE values of robust RMDA coe cients were at least 10% a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Conference on Applied Statistics in Agriculture
سال: 1990
ISSN: 2475-7772
DOI: 10.4148/2475-7772.1427