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The absence of specific genes on organisms' genomes cannot be separated from missing data given the unsaturated status of the metagenome sequences.
Apart from the distribution of the a priori missing data, given by Equation (10), application of EM requires information about the distribution of ε, the error on the ratios of fluxes and enzyme concentrations.
MI involves specifying a parametric model for the missing data given the observed data and drawing missing values from the posterior predictive distribution M>1 times.
The essence of the chained equations approach is that a univariate regression model consistent with the scale of the variable with missing data is used to provide predicted values of the missing data given the observed data.
It may be desirable, however, to relax assumptions regarding the posterior distributions of the model parameters, and to do this requires a replacement of the step that draws the conditional predictive distribution of the missing data given the observed data.
There were no missing data given the questionnaires were filled under the control of operators.
Similar(49)
Some cases were dropped due to missing data giving us a final analytic sample of 2781.
Inclusion of cases with missing data gives more credibility to the prediction model.
From this sample, 43 were excluded from the analyses due to missing data, giving a net sample of 1927 employees.
Other approaches that used each person's observed longitudinal data and the date of death to impute missing data gave similar results.
These tests gave similar results to our analyses that ignored missing data, giving confidence that there is no selection bias inherent in excluding those with missing region of birth.
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