Sentence examples for missing data analysis from inspiring English sources

In addition, a fault isolation algorithm based on missing data analysis is designed for EMVU to identify the variables contributing most to the faults.

A great deal of recent methodological research has focused on two modern missing data analysis methods: maximum likelihood and multiple imputation.

Considering the fact that a more detailed discussion of the statistics dealing with missing data is beyond of the scope of this article, more details about missing data analysis can be found in Schafer and Graham (2002).

The ripple test, which can cause serious problems with missing data analysis, strongly increases the reliability of the marker order when analyzing markers of each maternal linkage phase separately in JOINMAP.

The multiple imputation method will be used for missing data analysis[ 27].

Information from in-complete observations was taken into account using missing data analysis.

The supplementary data appendix gives details of missing data, univariable analysis, and multivariable analysis.

Other methods include for example modelling missing data, scenario analysis or sensitivity analysis [ 21].

We performed per-protocol analysis, analysis with baseline values for missing data and analysis with multiple imputation for missing data.

We did not use data imputation and excluded cases with missing data on analysis-by-analysis basis (unless mentioned otherwise).

For these models, full information maximum likelihood estimation was used to account for missing data, and analysis was conducted on the original raw dataset.