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D3S1304 and D3S1580 were excluded, as missing rates of the two markers for the above 4 populations were much greater than our tolerance of 40%.
We adopted the settings of the missing rates of Jung et al. for comparison purposes.
Returned questionnaires with items missing rates of 20%% or more were rejected, leaving 1379 to be included for statistical analysis.
The data were randomly selected with missing rates of 5%, 10 %, 15, and 20% from the totandof 20% × 6 = 1620 SNPs.
However, the missing rates of the other items were comparably lower than the ones encountered during the translation and validation of the same instrument in other populations [ 16– 16].
This was tested for samples of n=50, 100, and 200 under MCAR and two MAR mechanisms, including auxiliary variables with low or moderate correlations, and missing rates of up to 64%.
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The final dataset used in our analysis contained 96,448 records of medical services, with a missing rate of 10% (n=11,264 missing values), a quite low missing rate for a 24-month prospective cohort study.
First, missing rate of the GO was lower in the high-motivation situation, suggesting that the participants were motivated and became more alert to the response cues.
For example, the missing rate of MIF is 33.3% for m = 3.
Figure 8 Fault missing rate of SSC-DM-CRC and MSC-DM-CRC.
For a specified n, the sum of probabilities for all bars in Figure 7 correspond to the fault missing rate of SSC in Figure 8, and the sum of probabilities for 2-6 congruentve congruent samples correspond to the fault missing rate of MSC with N = 2.
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