Estimating Generalizability to a Latent Variable Common to All of a Scale’s Indicators: A Comparison of Estimators for ω h Richard E. Zinbarg, Northwestern University and The Family Institute at Northwestern University Iftah Yovel, Northwestern University William Revelle, Northwestern University Roderick P. McDonald, University of Illinois The extent to which a scale score generalizes to a latent variable common to all of the scale’s indicators is indexed by the scale’s general factor saturation. Seven techniques for estimating this parameter—omega hierarchical (ω h )—are compared in a series of simulated data sets. Primary comparisons were based on 160 artificial data sets simulating perfectly simple and symmetric structures that contained four group factors, and an additional 200 artificial data sets confirmed large standard deviations for two methods in these simulations when a general factor was absent. Major findings were replicated in a series of 40 additional artificial data sets based on the structure of a real scale widely believed to contain three group factors of unequal size and less than perfectly simple structure. The results suggest that alpha and methods based on either the first unrotated principal factor or component should be rejected as estimates of ω h . Index terms: generalizability, alpha, omega, factor analysis, measurement, reliability. Many scales are assumed by their developers and users to be primarily a measure of one latent variable. When it is also assumed that the scale conforms to the effect indicator model of measure- ment (as is almost always the case in psychological assessment), it is important to support such an interpretation with evidence regarding the internal structure of that scale (Bollen & Lennox, 1991). In particular, it is important to examine two related properties pertaining to the internal structure of such a scale. The first property relates to whether all the indicators forming the scale measure a latent variable in common. The second internal structural property pertains to the proportion of variance in the scale scores (derived from summing or averaging the indicators) accounted for by this latent variable that is common to all the indicators (Cronbach, 1951; McDonald, 1999; Revelle, 1979). That is, if an effect indicator scale is primarily a measure of one latent variable common to all the indica- tors forming the scale, then that latent variable should account for the majority of the variance in the scale scores. Put differently, this variance ratio provides important information about the sampling fluctuations when estimating individuals’ standing on a latent variable common to all the indicators arising from the sampling of indicators (i.e., when dealing with either Type 2 or Applied Psychological Measurement, Vol. 30 No. 2, March 2006, 121–144 DOI: 10.1177/0146621605278814 121 Ó 2006 Sage Publications