Optimal Sampling Strategies for Validation Studies.
In selection instrument validation studies the situation occasionally arises in which there are a large number of observations on the predictor but criterion data are very expensive or difficult to obtain, thus making it necessary to sample values of the predictor. Three strategies (random, rectangu...
| Publicado en: | Journal of Applied Psychology Vol. 63; no. 5; pp. 602 - 609 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
American Psychological Association
Oct78
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=6239205&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 6239205 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00219010 JAY jtl: Journal of Applied Psychology issn: 00219010 maglogo: N pubinfo: dt: Oct78 vid: 63 iid: 5 pid: 34 pub: American Psychological Association artinfo: ui: 6239205 10.1037/0021-9010.63.5.602 ppf: 602 ppct: 7 formats: tig: atl: Optimal Sampling Strategies for Validation Studies. aug: au: Osburn, H.G. Greener, Jack M. affil: University of Houston su: Statistical sampling Analysis of variance Sampling (Process) Decision making Criterion (Theory of knowledge) Heteroscedasticity sug: subj: Statistical sampling Analysis of variance Sampling (Process) Decision making Criterion (Theory of knowledge) Heteroscedasticity ab: In selection instrument validation studies the situation occasionally arises in which there are a large number of observations on the predictor but criterion data are very expensive or difficult to obtain, thus making it necessary to sample values of the predictor. Three strategies (random, rectangular, and extreme groups) for sampling predictor values were compared with respect to accuracy and statistical power in estimating the total group validity. Comparisons were made on samples drawn from six large N (approximately 10,000) bivariate test score distributions known to contain some departures from linearity and homoscedasticity. It was shown that in this situation selecting values of the predictor that form a rectangular distribution gave, in all instances studied, at least equal accuracy and greater statistical power in estimating the total group validity compared with random sampling. When the predictor-criterion relationship was generally linear with only modest departures from linearity, selecting values from the extremes of the predictor distribution was optimal in terms of accuracy and statistical power and clearly superior to rectangular sampling. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 1978 holdings: @attributes: islocal: N |
|---|