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The Design of Making Pre-K count and High Fives: Two-Stage, Multiyear Random Assignment at Different Levels.

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Design Parameters for Planning the Sample Size of Individual-Level Randomized Controlled Trials in Community

Marie-Andrée Somers1, Michael J Weiss2, Colin Hill2

  • 1MDRC, Los Angeles, CA, USA.

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PubMed
Summary

Planning sample sizes for randomized controlled trials (RCTs) in community colleges requires careful consideration of outcome variance. Researchers should account for varying standard deviations and covariate effects across semesters and studies for accurate minimum detectable true effect (MDTE) calculations.

Keywords:
community collegedesign parameterspostsecondaryrandomized controlled trialstatistical power

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Area of Science:

  • Educational Research
  • Statistics
  • Higher Education

Background:

  • Randomized controlled trials (RCTs) in community colleges have increased significantly over the last two decades.
  • Empirical data on sample size planning parameters for these RCTs remains limited.
  • Key parameters for blocked student-level random assignment designs include within-block outcome standard deviation and variance explained by baseline covariates.

Purpose of the Study:

  • To provide empirical estimates of key design parameters for sample size calculations in community college RCTs.
  • To analyze patterns in these parameters across different outcomes, semesters, and studies.
  • To inform researchers on best practices for planning sample sizes in this context.

Main Methods:

  • Analysis of student-level data from 8 to 14 RCTs, involving 5,649-7,099 students.
  • Examination of outcomes including enrollment, credits earned, credential attainment, and grade point average over a 3-year follow-up.
  • Estimation of within-block outcome standard deviation and the proportion of variance explained by baseline covariates.

Main Results:

  • Within-block standard deviation and minimum detectable true effect (MDTE) can increase in later semesters for enrollment and credit accumulation.
  • Substantial study-to-study variation exists in the standard deviation for degree attainment.
  • Baseline covariates explain less than 10% of the variation in student outcomes.

Conclusions:

  • Researchers planning sample sizes should consider the follow-up period and use a range of values for MDTE calculations.
  • A within-block variance explained value between 0 and 0.05 is recommended.
  • A public database of parameter estimates is provided to aid future research.