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With an expected missing data rate of around 25%, 2000 students needed to be enrolled in the study.
Because of expected missing data for different variables from different studies, only simple meta-regression was planned and performed.
Our data in Table 1 and Table 2 suggest GBS has a higher than expected missing data ratio.
Owing to the sensitivity of some questionnaire items, the expected missing data rate in the study was assumed to be 0.25; thus, the sample size was increased by a factor of 1.25 to 842 subjects.
Random effects modelling and multiple imputation methods will be considered to address the limitations due to expected missing data during follow up assessments and to enhance the power of the statistical evaluation.
These data losses are within the expected missing data range of 6-30% for TMA-based methodologies [ 34].
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In the former case, we would expect the birth certificate to have missing data about both the father and the mother, while in the latter case we would expect missing information only about the father.
As expected, the missing data for the seven variables of interest in our dataset were correlated with each other and with the outcome of interest, suggesting that the data are MAR or MNAR.
This type of correlation is also expected if missing data are due to "true missingness"—for example, null alleles segregating in the population at certain loci, as a result of polymorphic deletions in primer regions (e.g., Pemberton et al. 1995; Dakin and Avise 2004).
Expecting 8% missing data and 25% of patients lost in follow-up, the number of patients to be recruited was set at 200.
*N smaller than expected due to missing data.
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