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Exact(6)
Nevertheless, the reconstruction artifacts caused by (i) the missing data issue (this is the missing wedge/pyramid problem) and (ii) the discretization problem, can only be attenuated through more sampling, and in some extent by computationally intensive iterative reconstruction methods.
This data attrition can be viewed as a missing data issue, and mixed effect modeling that we used in this study has been found robust in this setting [50], as they implicitly impute outcome trajectories beyond the time of death or extubation.
Since, the pick-up mice for each experiment is random, we assume the loss of mice is completely random, the missing data issue does not consider.
The second component of the missing data issue is non-response to either the baseline or follow-up questionnaires.
Because particle species were not measured every day, we computed the mean monthly ratios of the elemental concentrations to the total PM2.5 mass for each month therefore eliminating the missing data issue.
While a number of these variables were included as predictors in the models used to impute missing postdischarge healthcare resource use data, we chose not to impute informal care costs and productivity losses given the magnitude of the missing data issue.
Similar(53)
We have dropped some observations due to missing data issues; the total sample size is 6,735.
To address missing data issues, the full information maximum likelihood (FIML, Muthén and Muthén 1998 2012) was used under the assumption of missing at random (MAR).
Comorbidities were derived from ICD-9-CM coding and therefore were not subject to missing data issues.
However, our study shares the disadvantages of most retrospective studies, including missing data issues [ 43], lack of randomization, and a potential for model misspecification.
Indeed, missing data issues restricted our ability to consider all classes of factors in one multivariate model because the sample size was substantially reduced when we did so.
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