Invited Commentary: Dealing With the Inevitable Deficiencies of Bias Analysis-and All Analyses

被引:9
|
作者
Greenland, Sander [1 ,2 ]
机构
[1] Univ Calif Los Angeles, Dept Epidemiol, Fielding Sch Publ Hlth, Los Angeles, CA 90095 USA
[2] Univ Calif Los Angeles, Dept Stat, Coll Letters & Sci, Los Angeles, CA 90095 USA
关键词
Bayesian methods; bias; epidemiologic methods; observational studies; uncertainty analysis; SENSITIVITY-ANALYSIS; SELECTION BIAS; RANDOMIZED-TRIALS; MISCLASSIFICATION; INFERENCE; DESIGN; PRIORS;
D O I
10.1093/aje/kwab069
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Lash et al. (Am J Epidemiol. 2021;190(8):1604-1612) have presented detailed critiques of 3 bias analyses that they identify as "suboptimal." This identification raises the question of what "optimal" means for bias analysis, because it is practically impossible to do statistically optimal analyses of typical population studies-with or without bias analysis. At best the analysis can only attempt to satisfy practice guidelines and account for available information both within and outside the study. One should not expect a full accounting for all sources of uncertainty; hence, interval estimates and distributions for causal effects should never be treated as valid uncertainty assessments-they are instead only example analyses that follow from collections of often questionable assumptions. These observations reinforce those of Lash et al. and point to the need for more development of methods for judging bias-parameter distributions and utilization of available information.
引用
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页码:1617 / 1621
页数:5
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