What is unit weighting and when is it appropriate to use?
What will be an ideal response?
Unit weighting (in which all predictors are weighted by 1.0) does extremely well in a variety of contexts. Unit weighting also is appropriate when populations change from time to time (Lawshe & Schucker, 1959) and when predictors are combined into a composite to boost effect size (and, therefore, statistical power) in criterion-related validity studies (Cascio, Valenzi, & Silbey, 1978, 1980). These studies all demonstrate that unit weighting does just as well as optimal weighting when the weights are applied to a new sample. Furthermore, Schmidt (1971) has shown that, when the ratio of subjects to predictors is below a critical sample size, the use of regression weights rather than unit weights could result in a reduction in the size of obtained correlations. In general, unit weights perform well compared to weights derived from simple or multiple regression when sample size is small (i.e., below 75; Bobko et al., 2007).
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