A confidence interval for ordinal multiple regression weights

A confidence interval (CI) for a population predictor weight for use with N . Cliff a (1994) method of ordinal multiple regression (OMR) is presented. The OMR CI is based on an estimated standard error of a weight derived from a fixed-effects model. A simulation was performed to examine the sampling properties of the OMR CI. The results show that the OMR CI had good Type I error rate and coverage. The OMR CI had lower power than the least-squares multiple regression (LSMR) CI when predictors were not correlated but had h igher power when predictor correlations were moderate to high. In addition to discussing the simulation results, it is pointed out that the OMR CI can have superior sampling properties when the fixed-effects assumptions are v iolated. The OMR CI is recommended when a researcher wants to consider only ordinal information in multivariate prediction, when predictor correlation s are moderate to high, and when the assumptions of fixed-effects LSMR are violated.