Literature DB >> 22477557

Introducing the at-risk average causal effect with application to HealthWise South Africa.

Donna L Coffman1, Linda L Caldwell, Edward A Smith.   

Abstract

Researchers often hypothesize that a causal variable, whether randomly assigned or not, has an effect on an outcome behavior and that this effect may vary across levels of initial risk of engaging in the outcome behavior. In this paper, we propose a method for quantifying initial risk status. We then illustrate the use of this risk-status variable as a moderator of the causal effect of leisure boredom, a non-randomized continuous variable, on cigarette smoking initiation. The data come from the HealthWise South Africa study. We define the causal effects using marginal structural models and estimate the causal effects using inverse propensity weights. Indeed, we found leisure boredom had a differential causal effect on smoking initiation across different risk statuses. The proposed method may be useful for prevention scientists evaluating causal effects that may vary across levels of initial risk.

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Year:  2012        PMID: 22477557      PMCID: PMC3405190          DOI: 10.1007/s11121-011-0271-0

Source DB:  PubMed          Journal:  Prev Sci        ISSN: 1389-4986


  6 in total

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Journal:  Psychol Methods       Date:  2008-12

5.  A simple G-computation algorithm to quantify the causal effect of a secondary illness on the progression of a chronic disease.

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Journal:  Stat Med       Date:  2009-08-15       Impact factor: 2.373

6.  Constructing inverse probability weights for marginal structural models.

Authors:  Stephen R Cole; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2008-08-05       Impact factor: 4.897

  6 in total
  5 in total

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  5 in total

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