Imputation Procedures for Cognitive Variables in the Mexican Health and Aging Study: Evaluating the Bias from Excluding Participants with Missing Data.

Brian Downer, Jaqueline Avila, Nai-Wei Chen, Rebeca Wong
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Abstract

Non-response of cognitive data in cohort studies is a barrier to cognitive aging research. We describe the procedures for the imputation of non-responses for cognitive data in the Mexican Health and Aging Study (MHAS). Data came from the 2001-2015 MHAS waves. We also describe the association of cognition with education, age, and other variables in 2015 with and without the imputed values. Between 12.3% and 37.9% of participants were missing data for at least one cognition variable. When we conducted the analysis with and without the imputed values, the relationships between education, age, and cognition were similar in direction and significance, but different in magnitude. Non-response of cognitive data is common and non-random in the MHAS. Investigators should use the data sets that include the imputed values, which are publicly available.

墨西哥健康与老龄化研究中认知变量的归因程序:评估排除数据缺失参与者的偏倚
队列研究中认知数据的不响应是认知衰老研究的一个障碍。我们描述了在墨西哥健康和老龄化研究(MHAS)的认知数据的非反应的归因程序。数据来自2001年至2015年的MHAS波。我们还描述了2015年认知与教育、年龄和其他变量的关联,有和没有输入值。12.3%至37.9%的参与者至少缺少一个认知变量的数据。当我们在有和没有输入值的情况下进行分析时,教育程度、年龄和认知之间的关系在方向和意义上是相似的,但在量级上是不同的。认知数据无反应在MHAS中是常见且非随机的。调查人员应该使用包含估算值的数据集,这些数据集是公开的。
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