Sentence examples for missing data bias from inspiring English sources

> A comparison of observations with missing values to the non-missing-data population did not identify any pattern that might introduce missing data bias into the estimates.

Sixty-four percent of patients (N = 303) provided baseline NPS data, and those without baseline data were excluded from the respective analysis to limit missing data bias.

While height and weight were incompletely recorded for hospitalized patients, our results were robust to various assumptions about these missing data and we conclude that the observed associations with morbid obesity were unlikely to be due to missing data bias.

However, with higher rates of missing data, bias increased.

This sampling and missing data bias implies that comparisons across income groups should be interpreted with caution.

One limitation of inverse probability weighting is that residual confounding, missing data bias, and/or selection bias could still occur.

All cases with missing data were compared to cases with complete data to evaluate whether missing data biased our estimations.

Although BMI data were missing for 17% of participants, we do not believe the missing data biased the observed association.

Due to a modest amount of missing data for participant occupation (8%) we carried out multiple imputation of missing observations to assess whether the missing data biased our results.

By extending the TGLMM to account for missing data, potential bias in disease prevalence estimate can be adjusted and thus, bias in PPV and NPV estimates can be avoided.

We also find no evidence that missing data consistently bias branch length estimates.