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...
Autor principal: | |
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Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
Hoboken, NJ :
Wiley
c2010.
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Edición: | 1st edition |
Colección: | Wiley series in probability and statistics.
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Materias: | |
Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628427206719 |
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 |
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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 |