By Tyler VanderWeele
The booklet presents an obtainable yet finished assessment of equipment for mediation and interplay. there was massive and quick methodological improvement on mediation and moderation/interaction research in the causal-inference literature during the last ten years. a lot of this fabric seems in numerous really good journals, and a few of the papers are relatively technical. There has additionally been massive curiosity in those advancements from empirical researchers within the social and biomedical sciences. besides the fact that, a lot of the cloth isn't at the moment in a layout that's obtainable to them. The publication closes those gaps by means of delivering an obtainable, accomplished, book-length insurance of mediation.
The booklet starts with a accomplished creation to mediation research, together with chapters on ideas for mediation, regression-based equipment, sensitivity research, time-to-event results, tools for a number of mediators, equipment for time-varying mediation and longitudinal information, and kin among mediation and different ideas regarding intermediates reminiscent of surrogates, crucial stratification, instrumental variables, and Mendelian randomization. the second one a part of the ebook issues interplay or "moderation," together with suggestions for interplay, statistical interplay, confounding and interplay, mechanistic interplay, bias research for interplay, interplay in genetic reviews, and tool and sample-size calculation for interplay. the ultimate a part of the ebook offers entire dialogue in regards to the relationships among mediation and interplay and unites those innovations inside a unmarried framework. This ultimate half additionally offers an creation to spillover results or social interplay, concluding with a dialogue of social-network analyses.
The publication is written to be obtainable to someone with a simple wisdom of data. finished appendices supply extra technical info for the reader. utilized empirical examples from a number of fields are given all through. software program implementation in SAS, Stata, SPSS, and R is equipped. The ebook may be obtainable to scholars and researchers who've accomplished a first-year graduate series in quantitative equipment in a single of the social- or biomedical-sciences disciplines. The booklet will merely presuppose familiarity with linear and logistic regression, and will very likely be used as a complicated undergraduate ebook to boot.
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Extra resources for Explanation in Causal Inference: Methods for Mediation and Interaction
Techniques for assessing these so-called “qualitative” or “crossover” interactions will also be discussed in Chapter 9 and are useful in this regard. We will describe there, for example, a breast cancer treatment setting in which, for young patients under age 50 with low progesterone receptor levels, treatment without tamoxifen led to higher proportions who were disease-free at 3 years, but for all other groups (who were either older or had higher progesterone receptor levels, or both), treatment with tamoxifen led to higher proportions who were disease-free at 3 years.
For example, there might be (a) social and biological factors, such as income and hypertension status (C1 ), that affect decisions about the level of treatment (A) and the work activity outcome (Y) or (b) other factors, such as neighborhood of residence or alcohol consumption (C2 ), that affect both the level of drug use (M) and the working activity outcome (Y). For the effect estimates to have a causal interpretation, control must be made for the confounding variables. In order to be able to estimate the controlled direct effect using the formula above, two assumptions are needed.
1. Motivations for Assessing Mediation Methods for mediation help understand the mechanisms, pathways, and intermediates whereby a cause affects an outcome. There are a number of motivations for wanting to understand the phenomenon of mediation. In some instances, the motivation may principally be simply explanation and understanding. For example, in Chapter 2 we will consider an example from genetic epidemiology in which genetic variants were found to be associated with both smoking behavior and lung cancer.
Explanation in Causal Inference: Methods for Mediation and Interaction by Tyler VanderWeele