Software Application Profile: SUMnlmr, an R package that facilitates flexible and reproducible non-linear Mendelian randomization analyses

被引:8
|
作者
Mason, Amy M. [1 ]
Burgess, Stephen [1 ,2 ]
机构
[1] Univ Cambridge, Dept Publ Hlth & Primary Care, British Heart Fdn, Cardiovasc Epidemiol Unit, Cambridge, England
[2] Univ Cambridge, Sch Clin Med, MRC Biostat Unit, Cambridge, England
基金
英国惠康基金; 英国医学研究理事会;
关键词
causal inference; fractional polynomials; piecewise linear; walled garden; INSTRUMENTAL VARIABLES; RISK;
D O I
10.1093/ije/dyac150
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Motivation: Mendelian randomization methods that estimate non-linear exposure-outcome relationships typically require individual-level data. This package implements non-linear Mendelian randomization methods using stratified summarized data, facilitating analyses where individual-level data cannot easily be shared, and additionally increasing reproducibility as summarized data can be reported. Dependence on summarized data means the methods are independent of the form of the individual-level data, increasing flexibility to different outcome types (such as continuous, binary or time-to-event outcomes). General features: The package implements the previously proposed fractional polynomial and piecewise linear methods on stratified summarized data that can either be estimated from individual-level data using the package or supplied by a collaborator. It constructs plots to visualize the estimated exposure-outcome relationship, and provides statistics to assess preference for a non-linear model over a linear model.
引用
收藏
页码:2014 / 2019
页数:6
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