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5 results

  • 2 - Key Terms

  • Donald P. Green, Columbia University, New York
  • Book:
    Social Science Experiments
    Published online:
    08 September 2022
    Print publication:
    29 September 2022, pp 6-22

  • Summary

    This chapter introduces key terms used to describe experiments and, more generally, the investigation of cause and effect. Because so many different disciplines use experiments, layers of overlapping terminology have accumulated, and this chapter tries to cut through the clutter by grouping synonyms, thereby keeping jargon to a minimum. In addition to providing definitions, this chapter explains why these key concepts are important in practice. The chapter starts with the basic ingredients of an experiment (treatments, outcomes). Next, we define what we mean by a causal effect, introducing the concept of potential outcomes. The chapter culminates in the presentation of three core assumptions for unbiased causal inference. These core assumptions figure prominently throughout the book, as readers are continually encouraged to assess whether illustrative experiments satisfy these assumptions in practice.

  • 1 - Experiments as Fair Tests

  • Donald P. Green, Columbia University, New York
  • Book:
    Social Science Experiments
    Published online:
    08 September 2022
    Print publication:
    29 September 2022, pp 1-5

  • Summary

    Social Science Experiments: A Hands-on Introduction is an accessible textbook for undergraduates. Why a hands-on approach that urges readers to roll up their sleeves and conduct their own experiments? When students design their own experiments, they must reflect on basic questions. What is the treatment … and control? Who are the participants? What is the outcome? The process of conducting an experiment builds other important skills: Creating a dataset, inspecting the results, and drawing inferences. Learning is easier when the motivation to acquire specific skills emerges organically through hands-on experience.

  • Exact estimation for Markov chain equilibrium expectations

  • Part of
  • Peter W. Glynn, Chang-Han Rhee
  • Journal:
    Journal of Applied Probability / Volume 51 / Issue A / December 2014
    Published online by Cambridge University Press:
    30 March 2016, pp. 377-389
    Print publication:
    December 2014
    • Article
      • You have access
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  • We introduce a new class of Monte Carlo methods, which we call exact estimation algorithms. Such algorithms provide unbiased estimators for equilibrium expectations associated with real-valued functionals defined on a Markov chain. We provide easily implemented algorithms for the class of positive Harris recurrent Markov chains, and for chains that are contracting on average. We further argue that exact estimation in the Markov chain setting provides a significant theoretical relaxation relative to exact simulation methods.

  • Complex correlation structure in consumption rates of major food groups: implications for the assessment of radiation exposure

  • Melanie I Breuninger, Gabriel A Schachtel, Petra M Lührmann, Bernd Hartmann, Monika Neuhäuser-Berthold
  • Journal:
    Public Health Nutrition / Volume 6 / Issue 1 / February 2003
    Published online by Cambridge University Press:
    16 October 2007, pp. 87-94
    • Article
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  • Objective:

    An extensive dataset on individual food consumption was analysed in order to study all pairwise correlations between the consumption rates of 11 major food groups. Additionally, the project aimed to examine and quantify the accuracy of a recently proposed estimator of total food consumption to be used for the estimation of radiation exposure by food. Such an inquiry seems justified, because the proposed estimator implicitly presumes an essentially positive correlation structure in food consumption rates.

    Design:

    Statistical analysis using representative data gathered in Germany in a nation-wide food consumption survey.

    Setting:

    Germany.

    Subjects:

    Individuals aged between 4 and 94 years namely 10901 males and 12308 females.

    Results:

    The consumption rates of 11 major food categories showed several significantly positive, but also a number of significantly negative, correlations. Negative associations between cereal and potato products persisted consistently over all age groups, independent of sex. Other significantly negative correlations were limited to certain age groups. Reflecting these negative correlations, a subsequent analysis of relative ranks of consumption revealed that no person in the sample had the highest consumption rates in all food groups simultaneously. Based on representative samples, overestimations of 34 to 53% were obtained if – as recently suggested in the context of radiation exposure prediction – the 95th percentiles of total food consumption were determined as sums of the corresponding percentiles of the food groups.

    Conclusions:

    The complex correlation structure of food group consumption rates, as identified in this study, bears important implications for various health-related issues. Ignoring them could lead to overly conservative estimations of radiation exposure due to food ingestion or to confounding effects in epidemiological studies on nutritional risk factors of diseases. The results also indicate that a distinction into different dietary patterns might be useful in characterising different consumption habits.