التفاصيل البيبلوغرافية
| العنوان: |
Synthesizing subject-matter expertise for variable selection in causal effect estimation: A case study |
| المؤلفون: |
Debertin, Julia, Jurado Vélez, Javier A, Corlin, Laura, Hidalgo, Bertha, Murray, Eleanor J |
| المصدر: |
Epidemiology ; ISSN 1044-3983 |
| بيانات النشر: |
Ovid Technologies (Wolters Kluwer Health) |
| سنة النشر: |
2024 |
| الوصف: |
Background: Causal graphs are an important tool for covariate selection but there is limited applied research on how best to create them. Here, we used data from the Coronary Drug Project (CDP) trial to assess a range of approaches to directed acyclic graph (DAG) creation. We focused on the effect of adherence on mortality in the placebo arm, since the true causal effect is believed with a high degree of certainty. Methods: We created DAGs for the effect of placebo adherence on mortality using different approaches for identifying variables and links to include or exclude. For each DAG, we identified minimal adjustment sets of covariates for estimating our causal effect of interest, and applied these to analyses of the CDP data. Results: When we used only baseline covariate values to estimate the cumulative effect of placebo adherence on mortality, all adjustment sets performed similarly. The specific choice of covariates had minimal effect on these (biased) point estimates, but including non-confounding prognostic factors resulted in smaller variance estimates. When we additionally adjusted for time-varying covariates of adherence using inverse probability weighting, covariates identified from the DAG created by focusing on prognostic factors performed best. Conclusion: Theoretical advice on covariate selection suggests including prognostic factors that are not exposure predictors can reduce variance without increasing bias. In contrast, for exposure predictors that are not prognostic factors, inclusion may result in less bias control. Our results empirically confirm this advice. We recommend that hand-creating DAGs begin with identification of all potential outcome-prognostic factors. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| DOI: |
10.1097/ede.0000000000001758 |
| DOI: |
10.1097/EDE.0000000000001758 |
| الإتاحة: |
https://doi.org/10.1097/ede.0000000000001758Test |
| حقوق: |
http://creativecommons.org/licenses/by-nc-nd/4.0Test/ |
| رقم الانضمام: |
edsbas.C71EC33B |
| قاعدة البيانات: |
BASE |
