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Since scoring algorithm of each instrument did not include guideline to deal with missing data, subjects with missing data in one of the instrument items were excluded in this study.
To study the effect of missing data and model stability on model composition, the following four methods were compared: To handle missing data, subjects with missing values on any of the variables were omitted and only those subjects with information on all variables in the model were included for analysis.
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Previous work has simulated missing data subject to a known mechanism whereas we have used real data to test procedures.
To minimize the impact of missing data, each subject's cortisol measurements at T0, T1, T2 and T3 were averaged over the three collection days within each year for the four separate years per subject.
Missing data per subject ranged from 0.5%too 11.3% with a mean of 2.9% (N = 57).
Missing data on 1 3 subjects; Missing data on 4 7 subjects; Missing data on 8 17 subjects; Missing data on 18 30 subjects; Missing data on 31 36 subjects.
a = missing data from two subjects b = missing data from two subjects.
Due to missing data on 4 subjects, we had complete questionnaire results and S-TOFHLA scores on 1002 subjects with confirmed diabetes.
Medication administration time missing data for 5 subjects.
The ADHD-prison group (n = 22) had missing data for eight subjects.
The remaining studies used a variety of other approaches to dealing with missing data including excluding subjects with missing data, or excluding variables with too much missing data, or it was unclear what approach was taken.
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