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On Ideology, Causal Inference and the Reification of Statistical Methods: Reflections on "Examining Instruction, Achievement and Equity with NAEP Mathematics Data" Harold Wenglinsky Academy for Educational Development Regional Educational Laboratory of the Southeast Citation: Wenglinsky, H. (2006). On ideology, causal inference and the reification of statistical methods: Reflections on "Examining instruction, achievement and equity with NAEP mathematics data." Education Policy Analysis Archives, 14(17). Retrieved [date] from http://epaa.asu.edu/epaa/v14n17/. Abstract The purpose of this article is to comment on the prior article entitled "Examining Instruction, Achievement and Equity with NAEP mathematics data," by Sarah Theule Lubienski. That article claims that a prior article by the author suffered from three weaknesses: (1) An attempt to justify No Child Left Behind (NCLB); (2) drawing causal inferences from cross-sectional data; (3) and various statistical quibbles. The author responds to the first claim, by indicating that any mention of NCLB was intended purely to make the article relevant to a policy journal; to the second claim, by noting his own reservations about using cross-sectional data to draw causal inferences; and to the third claim by noting potential issues of quantitative methodology in the Lubienski article. He concludes that studies that use advanced statistical methods are often so opaque as to be difficult to compare, and suggests some advantages to the quantitative transparency that comes from the findings of randomly controlled field trials. Keywords: equity, mathematics achievement; mathematics instruction; NAEP. Resumen El objetivo de este articulo es comentar el trabajo "Examinando instrucción, logros, y equidad usando resultados de matemáticas de NAEP" de Sarah Theule Lubienski previamente publicado en EPAA. Ese articulo sostenía que otro articulo publicado por mi sufría de tres debilidades: (1) Intentaba justificar la ley federal sin abandonar ningún niño (2) Realizaba inferencias causales a partir de datos obtenidos en estudios cross seccionales; (3) otras objeciones sobre las estadísticas usadas. Este autor responde a la primera objeción indicando que cualquier mención a la ley federal sin abandonar ningún niño tuvo como objetivo establecer la relevancia de este trabajo para una revista de análisis político; a la segunda objeción, respondo indicando mis propias reservas al uso de estudios cross seccionales para establecer relaciones causales; y a la tercer objeción, indicando algunos problemas potenciales en la metodología cuantitativa del trabajo de Lubienski. Este autor concluye que los estudios que usan métodos cuantitativos avanzados suelen ser opacos y difíciles de entender y comparar, y sugiere que la transparencia cuantitativa deviene obtener resultados en experimentos con poblaciones seleccionadas al azar y campos controlados. Editor's Note: This article is a response to Sarah Lubienski's (2006) article that appears at http://epaa.asu.edu/epaa/v14n14/, which discussed Wenglinsky's (2004) article available at http://epaa.asu.edu/epaa/v12n64/. It is the practice of Education Policy Analysis Archives to publish one round of responses to articles where it is merited. Additional discussion of this and other articles is welcome online at http://epaa.info/wordpress. Access this article in PDF format.   Readers are free to copy, display, and distribute this abstract and the associated article, as long as the work is attributed to the author(s) and Education Policy Analysis Archives, it is distributed for non-commercial purposes only, and no alteration or transformation is made in the work. All other uses must be approved by the author(s) or EPAA. EPAA is published jointly by the Mary Lou Fulton College of Education at Arizona State University and the College of Education at the University of South Florida. Articles are indexed by H.W. Wilson & Co. Please contribute commentary at http://epaa.info/wordpress/ and send errata notes to Sherman Dorn (epaa-editor@shermandorn.com).