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In addition, it was inevitable that missing data existed in a cohort study.
No missing data existed for the variables included in the prognostic score, but for other tested variables, cases sometimes were excluded if data were missing, although no more than two cases in each analysis had to be excluded due to a high degree of data availability.
No missing data existed for the variables included in the prognostic score, but for other tested variables, cases sometimes were excluded if data were missing, although no more than two cases in each analysis had to be excluded because of a high-degree of data availability.
Missing data existed for all variables in the sample (see Table 1).
Missing data existed in a cohort study.
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The results show that the process non-linearity can also be addressed under this modeling method and the change of the process is also well tracked when missing data exist in the observed data.
Indeed, a variety of mechanisms and methods to handle missing data exists and could be used.
Three types of missing data exist according to Little and Rubin's classification [ 5].
In addition, differences between the final numbers of samples in both analyses are due to missing data; SAS excludes samples if missing data exists for one covariate in the model.
5 Although these have been shown to be effective with other types of missing data, little data exist regarding the absolute or comparative effectiveness of these methods in accurately imputing missing laboratory data in predictive models.
Although these have been shown to be effective with other types of missing data, few data exist regarding the absolute or comparative effectiveness of these methods in accurately imputing missing completely at random laboratory data in predictive models.
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