Sentence examples for approaches for imputing from inspiring English sources

We compared several approaches for imputing the response variables BA and TD, aggregated at the plot-scale and species-level, from topographic and canopy structure predictor variables derived from discrete-return airborne LiDAR data.

To explore various approaches for imputing untyped markers to augment sequence data, using a reference panel determined from sequencing a portion of the study participants, we will utilize sequence data available for GENE1 and COMT.

There are currently two main approaches for imputing data when the missingness mechanism is ignorable.

The different approaches for imputing missing GHb data did not change effect size, and adjustment for non-Hispanic white race/ethnicity also did not change effect size.

MICE is a practical approach for imputing missing datasets based on a set of imputation models, given that there is one model for each variable with missing values.

MICE has been described in the context of medical research conducted by Royston and White (2011), Van Buuren et al. (1999), and White et al. (2011), and it is seen as a suitable approach for imputing incomplete large, national, public datasets.

There were up to 11% missing values for at least one variable in the dataset, which we imputed using a chained regression procedure, which is recognised as a suitable approach for imputing incomplete large, national and public datasets [ 55– 55].

A more cost effective approach would be to sequence a portion of the individuals, followed by the application of genotype imputation methods for imputing markers in the remaining individuals.

For women missing one or two CCI responses (n = 55 women, 57 observations) or one MHI-5 response (n = 44 women, 46 observations), we used the standard approach of imputing the total score for the scale by dividing their score by the fraction of questions answered and rounding to the nearest integer (DeVellis 1991; Ware et al. 2000).

We also are working on improving our approach, for example by developing systematic approaches for grouping similar values for categorical variables and investigating enhanced methods for imputing missing values.

The proposed imputation technique employs Probabilistic Neural Network (PNN) preceded by mode for imputing the missing categorical data.