Abstract
The objectives of some experiments are to compare the variances of two or more treatments, products, or techniques. If the investigator is more concerned about within-unit variances rather than between-unit variances, then a repeated measurement design is needed. We invoke a random effects model with heterogeneous within-unit variances for certain repeated measurements designs. We do not impose any distributional assumptions for the random effects, whereas we assume either a normal or multivariate t distribution for the random errors. We propose a partial likelihood analysis for population-based inference and individual-based inference. We illustrate the methodology with an example from a trial comparing serum cholesterol measurements from a routine laboratory analyzer to those of a standardized method.
Original language | English (US) |
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Pages (from-to) | 205-216 |
Number of pages | 12 |
Journal | Biometrics |
Volume | 51 |
Issue number | 1 |
DOIs | |
State | Published - 1995 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- General Biochemistry, Genetics and Molecular Biology
- General Immunology and Microbiology
- General Agricultural and Biological Sciences
- Applied Mathematics