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Using Single-Case Experiments to Support Evidence-Based Decisions: How Much Is Enough?

Marc J Lanovaz1, John T Rapp2

  • 1Université de Montréal, Québec, Canada marc.lanovaz@umontreal.ca.

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|November 6, 2015
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Summary
This summary is machine-generated.

This study introduces a statistical method using success rates to determine the effectiveness of interventions validated through single-case experiments (SCEDs). It helps practitioners decide how many SCEDs are sufficient for evidence-based decisions.

Keywords:
empirically supported treatmentsevidence-based practiceexternal validityreplicationsingle-case experimental designs

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Area of Science:

  • Behavioral Science
  • Applied Psychology
  • Research Methodology

Background:

  • Practitioners question the number of single-case experiments (SCEDs) needed to confirm intervention effectiveness.
  • Existing guidelines for SCED sufficiency lack strong theoretical or empirical grounding.

Purpose of the Study:

  • To provide evidence-based guidelines for decision-making in SCED research.
  • To introduce a statistical approach for quantifying intervention support from SCEDs.

Main Methods:

  • Proposing the use of success rates to aggregate results from multiple SCEDs.
  • Developing a methodology to estimate the probability of intervention success.

Main Results:

  • Success rates offer a quantifiable measure to supplement evidence-based decisions.
  • The proposed method allows aggregation of findings across SCEDs.

Conclusions:

  • The statistical approach enhances evidence-based decision-making for interventions validated with SCEDs.
  • Practitioners can better estimate intervention efficacy using aggregated success rates.