Missing Data Methods in Mendelian Randomization Studies With Multiple Instruments
Author:
Publisher
Oxford University Press (OUP)
Subject
Epidemiology
Link
http://academic.oup.com/aje/article-pdf/174/9/1069/17339390/kwr235.pdf
Reference27 articles.
1. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*
2. What can mendelian randomisation tell us about modifiable behavioural and environmental exposures?
3. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology
4. Mendelian randomization as an instrumental variable approach to causal inference
5. An introduction to instrumental variables for epidemiologists
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1. Missing data approaches in longitudinal studies of aging: A case example using the National Health and Aging Trends Study;PLOS ONE;2023-06-08
2. Strengthening the reporting of observational studies in epidemiology using mendelian randomisation (STROBE-MR): explanation and elaboration;BMJ;2021-10-26
3. Efficient Nonparametric Causal Inference with Missing Exposure Information;The International Journal of Biostatistics;2020-03-14
4. Handling Missing Data in Instrumental Variable Methods for Causal Inference;Annual Review of Statistics and Its Application;2019-03-07
5. GMM with Multiple Missing Variables;Journal of Applied Econometrics;2015-02-04
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