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Area of Science:

  • Behavioral Science
  • Research Methodology
  • Evidence-Based Practice

Background:

  • Single-case designs (SCDs) are crucial in clinical and school settings.
  • Meta-analysis of SCDs is needed for broader generalizations.
  • Direct observation measures (rates, proportions) are common outcomes.

Purpose of the Study:

  • To describe methods for meta-analyzing SCDs using log response ratios.
  • To provide a quantitative effect size measure for proportionate change from baseline.
  • To inform evidence-based practice and research synthesis.

Main Methods:

  • Estimating log response ratios for behavior measures.
  • Combining effect size estimates using meta-analysis.
  • Utilizing a simple model for two-phase comparisons with stable outcomes.
  • Employing robust variance estimation for auto-correlated data.

Main Results:

  • The paper details the estimation and meta-analysis of log response ratios.
  • Methods are robust to auto-correlation using variance estimation procedures.
  • Demonstrated with data from a meta-analysis on group contingency interventions.

Conclusions:

  • The described methods facilitate robust meta-analysis of SCDs.
  • Log response ratios offer a valuable effect size measure for behavioral research.
  • These techniques support evidence-based practice and research synthesis in SCDs.