1.

Record Nr.

UNINA9910822673803321

Autore

Weisberg Herbert I. <1944->

Titolo

Bias and causation : models and judgment for valid comparisons / / Herbert I. Weisberg

Pubbl/distr/stampa

Hoboken, NJ, : Wiley, c2010

ISBN

9786612707742

9781282707740

1282707744

9780470631102

0470631104

9780470631096

0470631090

Edizione

[1st edition]

Descrizione fisica

1 online resource (366 p.)

Collana

Wiley series in probability and statistics

Classificazione

70.03

Disciplina

519.5/35

Soggetti

Discriminant analysis

Paired comparisons (Statistics)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Bias and Causation: Models and Judgment for Valid Comparisons; Contents; Preface; CHAPTER 1: What Is Bias?; CHAPTER 2: Causality and Comparative Studies; CHAPTER 3: Estimating Causal Effects; CHAPTER: 4 Varieties of Bias; CHAPTER 5: Selection Bias; CHAPTER 6: Confounding: An Enigma?; CHAPTER 7: Confounding: Essence, Correction, and Detection; CHAPTER 8: Intermediate Causal Factors; CHAPTER 9: Information Bias; CHAPTER 10: Sources of Bias; CHAPTER 11: Contending with Bias; Glossary; Bibliography; Index

Sommario/riassunto

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