The Reading Recovery i3 multi-site RCT finds large positive overall effects on reading outcomes with substantial variation in impacts across sites¶
Claim · All claims
Evidence · 1 study · causalr2·q3
Currency · newest study 2014 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q3 i? HLM analyses of the Reading Recovery i3 multi-site randomized trial revealed overall effects that are large and positive, with Glass's delta between .36 and .68, and substantial variation in impact estimates across sites. → Henry May 2014
Evidence¶
Henry May 2014¶
Henry May. (2014). Distortions in Distributions of Impact Estimates in Multi-Site Trials: The Central Limit Theorem is Not Your Friend. SREE Fall 2014 Conference. https://eric.ed.gov/?id=ED562702
q3 · i? · causal · r2
Analysis of 1,148 treatment and 1,148 control students from 380 schools in the Reading Recovery i3 multi-site randomized trial, using a three-level HLM with students nested in matched pairs nested in schools. The article reports "large and positive" overall effects with "substantial variation in impact estimates across sites".
"HLM analyses revealed overall effects of Reading Recovery in this multi-site study are large and positive (i.e., Glass’ between .36 and .68) with substantial variation in impact estimates across sites"
Discussion¶
Related Claims¶
- Random effects HLM models produce an unbiased estimate of the variance of true site-specific impacts regardless of the shape of the true distribution — related
- Cross-site standard deviations of ITT effects were estimated for education and workforce interventions using data from 16 large multisite randomized controlled trials — a broader claim this one bears on
- Methods for estimating impacts when treatment effects vary apply to randomized controlled trials and are also applicable to quasi-experimental designs — a broader claim this one bears on
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