DETECTING CHANGES IN NON-SIMULATED EVENTS USING PARTIAL INTERVAL RECORDING AND MOMENTARY TIME SAMPLING: EVALUATING FALSE POSITIVES, FALSE NEGATIVES, AND TRENDING

Authors


  • This study was completed by the first author in partial fulfillment of a master's degree in Behavior Analysis at St. Cloud State University.

Correspondence to: John T. Rapp, St. Cloud State University, Education Building, A 261, 720 4th Avenue South, St. Cloud, MN 56301-4498, USA. E-mail: jtrapp@stcloudstate.edu

Abstract

Several studies have evaluated false positives and false negatives produced with partial interval recording (PIR) and momentary time sampling (MTS) using simulated data. However, no study to date has evaluated false positives and negatives using a large sample of non-simulated behaviors. In addition, few studies have evaluated whether interval methods of data collection alter trends that are evident in continuous records. We conducted three experiments to evaluate the extent to which various interval sizes of MTS and PIR produced false negatives (Experiment 1), false positives (Experiment 2), and trends that were inconsistent with the continuous records (Experiment 3). Collectively, the results show the following: (i) 10-s PIR and 10-s MTS produced few false negatives and few false positives (i.e., both were sensitive) to changes in duration events; (ii) 10-s PIR produced very few false negatives, but an unexpected high percentage of false positives for frequency events; and (iii) each interval size of PIR and MTS produced a high percentage of changes in trending for duration events and frequency events. We briefly discuss the potential limitations and clinical implications of these findings. Copyright © 2012 John Wiley & Sons, Ltd.

Ancillary