Sentence examples for models missing data from inspiring English sources

To avoid excluding patients with missing factors in regression models, missing data were imputed using chained equation methods with 20 imputations[19].

Subsequently, mixed modeling has become a major area of statistical research, including work on the computation of maximum likelihood estimates, nonlinear mixed effect models, missing data in mixed effects models, and Bayesian estimation of mixed effects models (West et al. 2007).

The GBD systematically collects timely disease-specific epidemiologic information and models missing data to estimate a variety of measures of burden [15], [16].

In all models, missing data were assumed to be missing completely at random (Diggle et al. 1994).

In certain types of models, missing data can be replaced by suitable procedures, with negligible or tolerable loss of predictive performance.

In this model and all subsequent models, missing data were handled by means of a maximum likelihood estimation technique, which minimizes bias due to listwise deletion [ 13].

This method of modeling missing data assumes that the data are missing at random and permits inclusion of all available cases, although it is not as efficient as multiple imputation procedures.

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

In order to model missing data, information about three of the variables listed is needed.

The program has the ability to model missing data in the dependent variable under certain conditions.

The common solution – modeling missing data, or extrapolating data of one country to another country – yields epistemic uncertainty.