Bias and causation models and judgment for valid comparisons

A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in...

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Detalles Bibliográficos
Autor principal: Weisberg, Herbert I., 1944- (-)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, NJ : Wiley c2010.
Edición:1st edition
Colección:Wiley series in probability and statistics.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628427206719
Descripción
Sumario:A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causa
Notas:Description based upon print version of record.
Descripción Física:1 online resource (366 p.)
Bibliografía:Includes bibliographical references and index.
ISBN:9781282707740
9786612707742
9780470631102
9780470631096