Sentence examples for missing data rather from inspiring English sources

To examine this issue, we fitted the models shown in Table 4 using only non-missing data on sexual partners (excluding cases with missing data rather than imputing their values for this variable).

However, this does not necessarily preclude missing data rather just that the data we do have is self-consistent.

Multiple imputation (MI) was developed as a method to enable valid inferences to be obtained in the presence of missing data rather than to re-create the missing values.

Time bins or taxonomic categories in which no report of repeated evolution was found were treated as missing data rather than evidence for lack of repeated evolution among taxa at that phylogenetic separation.

We do not examine the early 6-state models, such as those proposed by Tillier and Collins (1995), because with modern computing power it is unreasonable to recode unstable base pairs as missing data, rather than explicitly incorporate them into the model.

The main difference from the JOINMAP approach in this final step is that the censored BI-markers were replaced by "missing data" rather than excluded, and that the markers belonging to the same LGs were analysed together instead of in two separate groups.

We did not aim to compare different approaches to deal with missing data but rather to provide a solution accessible to the majority of epidemiologists by the use of standard statistical software.

It is always of importance to report both positive and negative findings; however, the lack of such related data was missing information rather than negative.

The causes of missing data for BMI have rather been found correlated with emotional, behavioral and social aspects such as young age, poor body satisfaction and poor social networks [ 29].

Deleted and duplicated genomic regions in Burkholderia are frequent [ 11, 21, 50, 13] and can lead to missing data and sampling paralogous rather than orthologous loci [ 51, 52], respectively.

Therefore, we adopted the strategy of removing units with any missing data from further analysis rather than replacing the missing data with mean values which could lead to distortion when the intent of the analysis was to compare reported staffing levels to DoH national guidelines.