Randall Juras1. 1. Abt Associates, Cambridge, MA, USA randall_juras@abtassoc.com.
Abstract
INTRODUCTION: When cluster randomized trials are used to evaluate school-based nutritional interventions such as school lunch programs, design-stage estimates of the required sample size must take into account the correlation in outcomes among individuals within each cluster (e.g., classrooms, schools, or districts). Estimates of the necessary parameters have been carefully developed for educational interventions, but for nutritional interventions the literature is thin. METHODS: Using data from two large multi-school, multi-district impact evaluations conducted in the United States, this article calculates estimates of the design parameters required for sizing school-based nutritional studies. The large size of the trials (252 and 1,327 schools) yields precise estimates of the parameters of interest. Variance components are estimated by fitting random-intercept multilevel models in Stata. RESULTS: School-level intraclass correlations are similar to those typically found for educational outcomes. In particular, school-level estimates range from less than .01 to .26 across the two studies, and district-level estimates ranged from less than .01 to .19. This suggests that cluster randomized trials of nutritional interventions may require samples with numbers of schools similar to the education studies to detect similar effect sizes.
INTRODUCTION: When cluster randomized trials are used to evaluate school-based nutritional interventions such as school lunch programs, design-stage estimates of the required sample size must take into account the correlation in outcomes among individuals within each cluster (e.g., classrooms, schools, or districts). Estimates of the necessary parameters have been carefully developed for educational interventions, but for nutritional interventions the literature is thin. METHODS: Using data from two large multi-school, multi-district impact evaluations conducted in the United States, this article calculates estimates of the design parameters required for sizing school-based nutritional studies. The large size of the trials (252 and 1,327 schools) yields precise estimates of the parameters of interest. Variance components are estimated by fitting random-intercept multilevel models in Stata. RESULTS: School-level intraclass correlations are similar to those typically found for educational outcomes. In particular, school-level estimates range from less than .01 to .26 across the two studies, and district-level estimates ranged from less than .01 to .19. This suggests that cluster randomized trials of nutritional interventions may require samples with numbers of schools similar to the education studies to detect similar effect sizes.
Authors: Marie Murphy; Miranda Pallan; Emma Lancashire; Rhona Duff; Ashley J Adamson; Suzanne Bartington; Emma Frew; Tania Griffin; Kiya L Hurley; Jayne Parry; Sandra Passmore; Vahid Ravaghi; Alice J Sitch; Suzanne Spence; Maisie K Rowland; Scott Wheeldon; Peymane Adab Journal: BMJ Open Date: 2020-10-16 Impact factor: 2.692