Repeated Measures Data
Jump to navigation
Jump to search
See: Longitudinal Study, Longitudinal Data, Transfer Learning, Mixed Effects Models.
References
2006
- (Statistics.com, 2006) ⇒ http://www2.statistics.com/resources/glossary/r/repmeas.php
- QUOTE: Repeated measures (or repeated measurements) data are usually obtained from multiple measurements of a response variable. Such multiple measurements are carried out for each experimental unit over time (as in a longitudinal study ) or under multiple conditions.
An essential statistical peculiarity of such data is dependence of the response on the experimental unit itself. This often makes variability of response between units significantly higher than variability between different conditions or time points for the same unit.
- QUOTE: Repeated measures (or repeated measurements) data are usually obtained from multiple measurements of a response variable. Such multiple measurements are carried out for each experimental unit over time (as in a longitudinal study ) or under multiple conditions.
1990
- (Lindstrom & Bates, 1990) ⇒ Mary J. Lindstrom, and Douglas M. Bates. (1990). “Nonlinear Mixed Effects Models for Repeated Measures Data.” In: Biometrics, 46(3).
- QUOTE: There has been a great deal of recent interest in mixed effects models for repeated measures data. By “repeated measures data” we mean data generated by observing a number of individuals repeatedly under differing experimental conditions where the individuals are assumed to constitute a random sample from a population of interest. For the reader familiar with split-plot designs, each individual can be thought of as a whole plot and each observation as a subplot.