title: Neural network simulation of visual inspection of graphs of single-subject interventions.
abstract: Judgments of the effectiveness of single-subject behavioral interventions are often based on visual examination of graphs of response data, but previous research indicates that such judgments are often unreliable and flawed. Here it is proposed that artificial neural networks could be developed to simulate the judgments of expert judges. A prototype of such a network was designed and trained in the present study, and its use in novel experiments matched the estimates of the expert whose judgments were simulated significantly better than did a prediction equation developed using a multiple regression approach.
authors.affiliation: Department of Psychology, University of Northern Iowa, Cedar Falls 50614-0505, USA. andy.gilpin@uni.edu
authors.forename: A R
authors.initials: AR
authors.lastname: Gilpin
mesh_terms: D001185:Artificial Intelligence; D001521:Behavior Therapy / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005103:Expert Systems; D006801:Humans; D008432:Mathematical Computing; D016571:Neural Networks, Computer; D011340:Problem Solving; D015203:Reproducibility of Results; D016896:Treatment Outcome