Sentence examples for imputation in order to from inspiring English sources

The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset.

All these methods are compared using single imputation and multiple imputation in order to assess the gain induced by the multiple imputation.

However, the patients who were non-respondents and those who stopped during follow-up differed from the whole-course respondents in a number of aspects, so we used multiple imputation in order to diminish selection bias.

The resultant data set was subjected to column mean imputation in order to fill in the missing trait values, given that the data were missing at random, i.e. not missing over all measures within a battery.

We have shown the advantages of using multiple imputation rather than single imputation, in order to deal with the uncertainty problem and provide better and more stable validation statistics.

In order to assess the robustness of the achieved results, another exploratory factor analysis was conducted on the full set of N = 315 patients as a sensitivity analysis, using single mean imputation in order to replace missing values on respective item scales.

However, regarding the weights and imputations, in order to verify the robustness of our results, we also performed exploratory factor analysis and MG-CFA with the weights (we recall that using weights in the MG-CFA with alignment is not feasible in Mplus).

Reporting alcohol consumption is strongly related to the sociodemographic characteristics [ 35] that can be included in the imputation model in order to reduce non-response bias.

We used multiple imputation procedures in order to analyse changes in religious participation across all five waves included in our analyses.

Missing parental data were a potential source of selection bias, and we performed a multiple imputation procedure in order to obtain complete parental data to help minimise this bias.

Previous work (Schafer, 1997; Moons et al., 2006; Sterne et al., 2009; White et al., 2011) emphasizes the importance of including the outcome in imputation models in order to maintain observed relationships between covariates and the outcome as required for regression modeling.