Use of double cross-validation and bootstrap methods to estimate replicability of results of multiple regression

Researchers have all too often ignored replicability of results because they overly rely on significance testing. This is a misinformed view because statistical significance does not evaluate the importance or replicability of a result. This paper focuses on two methods of assessing replicability of results, double cross-validation and bootstrap procedures. Selected variables from Hughes, Cavell, and Grossman's (1997) data set of 112 cases are used to illustrate all these techniques as applied to the interpretation of multiple regression results. One statistical computer package SPSS is used for the double cross-validation procedure, and a 1987 microcomputer program package of Lunneborg is used to demonstrate the bootstrap procedure.