You can set values to missing within your DATA step by using program statements such as this one: if age<0 then age=.; This statement sets the stored value of AGE to a numeric missing value if AGE has ...

When the BY value changes, the variables are set to missing and remain missing because the data set contains no additional observations to provide replacement values. When all of the rows in a data ...

Objectives Missing data is the most common data quality issue in electronic health records (EHRs). Missing data checks implemented in common analytical software are typically limited to counting the ...

This process reflects the uncertainty in each guess. Repeat these steps for the missing value in each of the other copies of the data set. Once you’ve filled in all the missing data, you can analyze ...

Missing-indicator method. The missing-indicator method was proposed for missing confounder data in etiologic research7, 8 and has since received much attention in the medical literature.3 – 6, 10, 12 ...

Table 2 Comparison of the accuracy of haplotype frequency estimations in the presence of missing values in the data set, restricted to estimations above 1/2000. Full size table. Figure 1.

Objectives Missing laboratory data is a common issue, but the optimal method of imputation of missing values has not been determined. The aims of our study were to compare the accuracy of four ...