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Generalizability theory acknowledges and allows for variability in assessment conditions that may affect measurements. The advantage of G theory lies in the fact that researchers can estimate what proportion of the total variance in the results is due to the individual factors that often vary in assessment, such as setting, time, items, and raters.
However, if one's goal is to understand generalizability across subpopulations that differ in situational or personal background factors, these remedies do not have the efficacy in increasing external validity that is commonly ascribed to them. If background factor X treatment interactions exist of which the researcher is unaware (as seems ...
For instance, consider a scenario with three factors, each having two levels, and an experiment that tests every possible combination of these levels (a full factorial design). One complete replication of this design would comprise 8 runs (2^3). The design can be executed once or with several replicates. [2]
However, the very methods used to increase internal validity may also limit the generalizability or external validity of the findings. For example, studying the behavior of animals in a zoo may make it easier to draw valid causal inferences within that context, but these inferences may not generalize to the behavior of animals in the wild.
Regularization can be motivated as a technique to improve the generalizability of a learned model.
Goldine C. Gleser (1915 – 2004) was an American psychologist and statistician known for her research on the statistics of psychological testing, on generalizability theory, on defence mechanisms, on the psychological effects on child survivors of the Buffalo Creek flood, for her work with Mildred Trotter on estimation of stature, and for her participation in the Cincinnati Radiation Experiments.
December 4, 2024 at 3:07 PM. How Your Cholesterol Could Indicate Dementia Risk Qi Yang ... But new research finds that there could be a less obvious risk factor out there: your cholesterol levels. ...
Using factor analysis and three independent samples, the authors concluded that modifying the original scale to only include 10-items would improve the validity of the scale. They deleted items that, theoretically, would make sense to include in a measure of resilience but that did not carry enough statistical weight to still be included (e.g ...