| Autor: |
Coffman DL; Department of Epidemiology and Biostatistics, Temple University., Dziak JJ; Edna Bennett Pierce Prevention Research Center, The Pennsylvania State University., Litson K; Instructional Technology & Learning Sciences Department, Utah State University., Chakraborti Y; Department of Epidemiology and Biostatistics, Temple University., Piper ME; Center for Tobacco Research Intervention, University of Wisconsin., Li R; Department of Statistics, The Pennsylvania State University. |
| Jazyk: |
angličtina |
| Zdroj: |
Multivariate behavioral research [Multivariate Behav Res] 2023 Sep-Oct; Vol. 58 (5), pp. 859-876. Date of Electronic Publication: 2023 Jan 09. |
| DOI: |
10.1080/00273171.2022.2149449 |
| Abstrakt: |
The increase in the use of mobile and wearable devices now allows dense assessment of mediating processes over time. For example, a pharmacological intervention may have an effect on smoking cessation via reductions in momentary withdrawal symptoms. We define and identify the causal direct and indirect effects in terms of potential outcomes on the mean difference and odds ratio scales, and present a method for estimating and testing the indirect effect of a randomized treatment on a distal binary variable as mediated by the nonparametric trajectory of an intensively measured longitudinal variable (e.g., from ecological momentary assessment). Coverage of a bootstrap test for the indirect effect is demonstrated via simulation. An empirical example is presented based on estimating later smoking abstinence from patterns of craving during smoking cessation treatment. We provide an R package, funmediation, available on CRAN at https://cran.r-project.org/web/packages/funmediation/index.html, to conveniently apply this technique. We conclude by discussing possible extensions to multiple mediators and directions for future research. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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