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APACHE II score was not used in the propensity model, due to the large number of missing observations (about 27%).
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*Between 0 3 missing observations per period.
Although some genotype imputation has been proposed to infer missing observations, little is known about the reliability of a genetic diversity analysis of GBS data, with up to 90% of observations missing.
Therefore multiple imputations were used in multivariable models assuming the data were missing at random to avoid excluding different injectors from different analyses.[ 34] This involved creating or imputing plausible values for missing observations reflecting the uncertainty about the non-response model.
Third, all relevant variables are screened for missing observations.
*Three missing observations.
Some variables have missing observations.
cN = 3 with missing observations.
dN = 6 with missing observations.
b1, c2 and d14 missing observations.
Last observation carried forward (LOCF) was used for missing observations.
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