Miller, Patterson, and Ulrich (1998) introduced a jackknife-based method for measuring the differences between two conditions in the onset latencies of the lateralized readiness potential (LRP). The present paper generalizes such jackknife-based methods to factorial experiments with any combination of within- and between subjects factors. Specifically, we introduce a subsample scoring method to assess potential main and interaction effects on LRP onsets within conventional yet slightly adjusted analyses of variance (ANOVAs) and post hoc comparison procedures.

Studies that measure the onset of the lateralized readiness potential (LRP) could well provide researchers with important new data concerning the information-processing locus of experimental effects of interest. However, detecting the onset of the LRP has proved difficult. The present study used computer simulations involving both human and artificial data, and both stimulus- and response-locked effects, to compare a wide variety of techniques for detecting and estimating differences in the onset latency of the LRP. Across the two sets of simulations, different techniques were found to be the most accurate and reliable for the analysis of stimulus- and response-locked data. On the basis of these results, it is recommended that regression-based methods be used to analyze most LRP data.

A new method based on jackknifing is presented for measuring the difference between two conditions in the onset latencies of the lateralized readiness potential (LRP). The method can be used with both stimulus- and response-locked LRPs, and simulations indicate that it provides accurate estimates of onset latency differences in many common experimental conditions.

A new method based on jackknifing is presented for measuring the difference between two conditions in the onset latencies of the lateralized readiness potential (LRP). The method can be used with both stimulus- and response-locked LRPs, and simulations indicate that it provides accurate estimates of onset latency differences in many common experimental conditions.