title: Detecting false positives in multielement designs: implications for brief assessments.
abstract: The authors assessed the extent to which multielement designs produced false positives using continuous duration recording (CDR) and interval recording with 10-s and 1-min interval sizes. Specifically, they created 6,000 graphs with multielement designs that varied in the number of data paths, and the number of data points per data path, using a random number generator. In Experiment 1, the authors visually analyzed the graphs for the occurrence of false positives. Results indicated that graphs depicting only two sessions for each condition (e.g., a control condition plotted with multiple test conditions) produced the highest percentage of false positives for CDR and interval recording with 10-s and 1-min intervals. Conversely, graphs with four or five sessions for each condition produced the lowest percentage of false positives for each method. In Experiment 2, they applied two new rules, which were intended to decrease false positives, to each graph that depicted a false positive in Experiment 1. Results showed that application of new rules decreased false positives to less than 5% for all of the graphs except for those with two data paths and two data points per data path. Implications for brief assessments are discussed.
authors.affiliation: St. Cloud State University, St. Cloud, MN 56301-4498, USA.
authors.forename: Sara M
authors.initials: SM
authors.lastname: Bartlett
authors.forename: John T
authors.initials: JT
authors.lastname: Rapp
authors.forename: Marissa L
authors.initials: ML
authors.lastname: Henrickson
mesh_terms: D035841:Behavioral Research / Q000379:methods*; D005189:False Positive Reactions; D006801:Humans; D008960:Models, Psychological; D012107:Research Design / Q000592:standards*; D013223:Statistics as Topic / Q000379:methods*