This research note proposes two reliability coefficients for tests with components of unknown functional lengths. The derived coefficients are extensions of the techniques devised by Kristof and Feldt and do not require a reduction of test components into parts. Simulation study indicates that the new coefficients yield reasonably stable reliability estimates when the number of test components is small.

The separate questions on an essay test or the individual judges on a rater panel may constitute congeneric parts rather than tau-equivalent parts. Also, it may be necessary to infer the lengths of the congeneric parts from their variances and covariances, rather than from some obvious feature of each part, such as the range of possible scores. Cronbach's alpha coefficient applied to such part-tests data will underestimate total score reliability. Several reliability coefficients are developed for such instruments. They may be regarded as extensions of the coefficient developed by Kristof for a three-part test.

In many instances it is reasonable to assume that the population covariance matrix has positive elements. This assumption implies for the single factor analysis model that the loadings and regression weights for best linear factor prediction are positive. For the multiple factor analysis model where each variable loads on a single factor and a hierarchical factor model, it implies that the loadings and the factor correlations are positive. For the latter model it also implies that the regression weights for first- and second-order factor prediction are positive.