Missing Step Count Data? Step Away From the Expectation–Maximization Algorithm
نویسندگان
چکیده
In studies that compare physical activity between groups of individuals, it is common for to be quantified by step count, which measured accelerometers or other wearable devices. Missing count data often arise in these settings and can lead bias imprecision the estimated effect if handled inappropriately. Replacing each missing value accelerometer with a single using Expectation–Maximization (EM) algorithm has been advocated literature, but underestimation variances could seriously compromise study conclusions. We performance terms variance two methods, EM Multiple Imputation (MI), through simulation where are generated from parametric model reflect characteristics trial on activity. also conduct reanalysis 2019 MOVE-IT trial. The leads an underestimate effects interest, both MI should preferred approach handling accelerometer, provides valid point estimates.
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ژورنال
عنوان ژورنال: Journal for the measurement of physical behaviour
سال: 2022
ISSN: ['2575-6605', '2575-6613']
DOI: https://doi.org/10.1123/jmpb.2022-0002