Autocorrelation and Estimates of Treatment Effect Size for Single‐Case Experimental Design Data | Journal Club Series

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This installment in our Journal Club Series will cover the article, “Autocorrelation and estimates of treatment effect size for single‐case experimental design data” authored by Barnard-Brak, Watkins, Richman and published in Behavioral Interventions. CEUs are provided for reading the article, participating in an online discussion, and completing an article content quiz.

Log into your account with the BACB and click on resources for a free copy of this article! Need help with accessing free articles via your BACB account? Visit our handy how-to guide here!

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Data analysis in behavior analysis involves visual inspection of behavior change over time, often with the introduction of a treatment or intervention. There are various ways to evaluate these behavior changes or treatment effects. This paper examines degrees of autocorrelation and six different effect size measures commonly used with single subject research.


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The Article

This installment in our Journal Club Series will cover the article, “Autocorrelation and estimates of treatment effect size for single‐case experimental design data” authored by Barnard-Brak, Watkins, Richman and published in Behavioral Interventions. CEUs are provided for reading the article, participating in an online discussion, and completing an article content quiz.

Log into your account with the BACB and click on resources for a free copy of this article!

Need help with accessing free articles via your BACB account? Visit our handy how-to guide here!

Learning Objectives

Objectives:

  1. Define autocorrelation
  2. Describe the purpose of this study
  3. Define the six effect size measures included in this investigation
  4. Describe the results of this study
  5. List some of the suggestions for future research when considering effect size values

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