Orthogonal Prediction Configural Frequency Analysis by Chi‐Square Partitioning
Erwin Lautsch, Gustav Adolf Lienert, Alexander von Eye · Biometrical Journal · 1992
Abstract Prediction Configural Frequency Analysis is reconceptualized in terms of orthogonal Chi‐Square decomposition. The predictor‐criterion contingency table is subdivided into fourfold tables. The chisquare components of these tables, calculated using Kimball's shortcut formulas, sum up to the total chi‐square of the r × c table. As a result of this decomposition, the number of r × c prediction tests of classical Prediction CFA is reduced to R = (r ‐ 1) (c ‐ 1) biprediction types. The resulting version of Prediction CFA is termed orthogonal Prediction CFA. Orthogonal Prediction CFA is illustrated using data describing pupils' performance in German language as predicted from performance in two verbal tests.