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TIME‐SERIES ANALYSIS IN OPERANT RESEARCH1

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Jones, Richard R., Vaught, Russell S., Weinrott, Mark·1977·Journal of Applied Behavior Analysis

Abstract

A time‐series method is presented, nontechnically, for analysis of data generated in individual‐subject operant studies, and is recommended as a supplement to visual analysis of behavior change in reversal or multiple‐baseline experiments. The method can be used to identify three kinds of statistically significant behavior change: (a) changes in score levels from one experimental phase to another, (b) reliable upward or downward trends in scores, and (c) changes in trends between phases. The detection of, and reliance on, serial dependency (autocorrelation among temporally adjacent scores) in individual‐subject behavioral scores is emphasized. Examples of published data from the operant literature are used to illustrate the time‐series method.

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Metadata

Authors
Jones, R. R., Vaught, R. S., & Weinrott, M.
Venue
Journal of Applied Behavior Analysis
Publisher
Wiley
Published
1977-03
Volume
10
Issue
1
Pages
151-166
ISSN
  • 0021-8855 (ISSN-L)
  • 1938-3703
OpenAlex
W2052302051
Cited by
185
References
0
FWCI
16.76
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: TIME‐SERIES ANALYSIS IN OPERANT RESEARCH1. https://app.cochat.ai/papers/10.1901/jaba.1977.10-151
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Jones, R. R., Vaught, R. S., & Weinrott, M. (1977). TIME‐SERIES ANALYSIS IN OPERANT RESEARCH1. Journal of Applied Behavior Analysis. https://doi.org/10.1901/jaba.1977.10-151

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.