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Causal Inference: A Statistical Paradigm for Inferring Causality

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Statistical Causal Inferences and Their Applications in Public Health Research

Part of the book series: ICSA Book Series in Statistics ((ICSABSS))

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Abstract

Inferring causation is one important aim of many research studies across a wide range of disciplines. In this chapter, we will introduce the concept of potential outcomes for its application to causal inference as well as the basic concepts, models, and assumptions in causal inference. An overview of statistical methods for causal inference will be discussed.

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Author information

Authors and Affiliations

  1. Value Institute, Christiana Care Health System, Newark, DE, 19718, USA

    Pan Wu

  2. Department of Biostatistics, School of Public Health & Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA

    Wan Tang

  3. Department of Mathematics and Statistics, University of Toledo, Toledo, OH, 43606, USA

    Tian Chen

  4. Department of Epidemiology, School of Public Health & Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA

    Hua He

  5. Center for Health Care & Policy, MetroHealth Medical Center, Case Western Reserve University, Cleveland, OH, 44109, USA

    Douglas Gunzler

  6. Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, 14642, USA

    Xin M. Tu

Authors
  1. Pan Wu
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  2. Wan Tang
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  3. Tian Chen
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  4. Hua He
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  5. Douglas Gunzler
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  6. Xin M. Tu
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Corresponding authors

Correspondence to Pan Wu or Xin M. Tu .

Editor information

Editors and Affiliations

  1. Department of Epidemiology School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, USA

    Hua He

  2. Christiana Care Health System, Value Institute, Newark, Delaware, USA

    Pan Wu

  3. School of Social Work and Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, USA

    Ding-Geng (Din) Chen

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Wu, P., Tang, W., Chen, T., He, H., Gunzler, D., Tu, X.M. (2016). Causal Inference: A Statistical Paradigm for Inferring Causality. In: He, H., Wu, P., Chen, DG. (eds) Statistical Causal Inferences and Their Applications in Public Health Research. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-41259-7_1

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