Sentence examples for missing data mechanism from inspiring English sources

The missing data mechanism is modeled by nonparametric prior processes.

Conditions on the missing data mechanism are presented under which SSIL gives consistent estimates, but both CC and IL are inconsistent.

Since the probability of a non-detection is a function of the unobserved flux, the missing data mechanism is non-ignorable.

By correcting for the non-ignorable missing data mechanism and other detection phenomena, we are able to obtain corrected estimates of the flux and luminosity distribution of source populations.

Knowledge of the probability of non-detection allows us to correct for the non-ignorable missing data mechanism and to build a hierarchical Bayesian model leads to inference for physical model parameters and the log N - log S distribution.

A more realistic situation is one in which the missing data mechanism is non‐ignorable.

This missing data mechanism is the most difficult to treat as it renders the usual imputation methods meaningless.

This assumption may not be valid and one may need to consider adjustment for a possible non-ignorable verification bias resulting from the non-ignorable missing data mechanism.

An ignorable missing data mechanism is one in which inferences are not affected by the process that generated the missing data.

The sensitivity analysis is most often accomplished by perturbing parameters in the chosen model for the missing data mechanism, and it has a local flavour because perturbations are around the fitted model.

The results suggested that WGEE estimator is consistent under various scenarios of percentage of missing data and sample size, while the WLS approach could yield biased estimators due to a misspecified missing data mechanism.