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The authors examine the reassessments of the National Reading Panel (NRP) report (National Institute of Child Health and Human Development, 2000) by G. Camilli, S. Vargas, and M. Yurecko (2003); G. Camilli, P. M. Wolfe, and M. L. Smith (2006); and D. D. Hammill and H. L. Swanson (2006) that disagreed with the NRP on the magnitude of the effect of systematic phonics instruction. Using the coding of the NRP studies by Camilli et al. (2003, 2006), multilevel regression analyses show that their findings do not contradict the NRP findings of effect sizes in the small to moderate range favoring systematic phonics. Extending Camilli et al. (2003, 2006), the largest effects are associated with reading instruction enhanced with components that increase comprehensiveness and intensity. In contrast to Hammill and Swanson, binomial effect size displays show that effect sizes of the magnitude found for systematic phonics by the NRP are meaningful and could result in significant improvement for many students depending on the base rate of struggling readers and the size of the effect. Camilli et al. (2003, 2006) and Hammill and Swanson do not contradict the NRP report, concurring in supporting comprehensive approaches to reading instruction. Keywords: reading instruction, phonics, National Reading Panel, meta-analysis

We conducted a meta-analysis of 28 studies comprising 39 samples to ask the question, “What is the magnitude of the association between various baseline child cognitive characteristics and response to reading intervention?” Studies were located via literature searches, contact with researchers in the field, and review of references from the National Reading Panel Report. Eligible participant populations included at-risk elementary school children enrolled in the third grade or below. Effects were analyzed using a shifting unit of analysis approach within three statistical models: cognitive characteristics predicting growth curve slope (Model 1, mean r = .31), gain (Model 2, mean r = .21), or postintervention reading controlling for preintervention reading (Model 3, mean r = .15). Effects were homogeneous within each model when effects were aggregated within study. The small size of the effects calls into question the practical significance and utility of using cognitive characteristics for prediction of response when baseline reading is available. [ABSTRACT FROM AUTHOR]

A meta-analysis of 22 studies evaluating the relation of different assessments of IQ and intervention response did not support the hypothesis that IQ is an important predictor of response to instruction. We found an R² of. 03 in models with IQ and the auto regressor as predictors and a unique lower estimated R² of .006 and a higher estimated R² of .013 in models with IQ, the autoregressor, and additional covariates as predictors. There was no evidence that these aggregated effect sizes were moderated by variables such as the type of IQ measure, outcome, age, or intervention. In simulations of the capacity of variables with effect sizes of .03 and .001 for predicting response to intervention, we found little evidence of practical significance. [ABSTRACT FROM AUTHOR]