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. 1977 Spring;10(1):151–166. doi: 10.1901/jaba.1977.10-151

Time-series analysis in operant research1

Richard R Jones 1,2, Russell S Vaught 1,2, Mark Weinrott 1,2
PMCID: PMC1311162  PMID: 16795544

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.

Keywords: ANOVA, experimental design, methodology, multiple baseline, serial dependency, single-organism research, statistics, time-series analysis

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

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