Criterion-Related Validity in Multiple-Hurdle Designs : Estimation and Bias  

Oleh:

Mumford, Michael D. ; Mendoza, Jorge L. ; Bard, David E. ; Siew, C. Ang

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Organizational Research Methods vol. 7 no. 4 (Oct. 2004), page 418-441.
Topik: estimation; selection; range restriction; multiple - hurdle design; missing data; corrections
Fulltext: 418.pdf (184.61KB)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: OO3.6 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Employee selection often involves a series of sequential tests (or hurdles). However, validation strategies under this complex design are not found in the literature. Missing is a discussion of the statistical properties important in establishing criterion - related validity in multiple - hurdle designs. The authors address this gap in the literature by suggesting a general statistical model for range restriction correction. Because the multiple - hurdle design includes as special case predictive and concurrent designs, the corrections apply also to these designs. The general correction model is based on algorithms for the missing data literature. Two missing data procedures are examined : the estimation - maximation procedure and the bayesian multiple imputation (MI) procedure. These procedures are large - sample equivalent and often yield similar results. The MI procedure, however, has the added advantage of providing easily obtainable standard errors. A hypothetical example of a multiple - hurdle design is used to illustrate the procedures.

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