Sentence examples for techniques for missing data from inspiring English sources
Linear interpolation is the simplest interpolation techniques for missing data imputation using the two known neighbours.
The software also includes classical imputation techniques for missing data: by zeros, (un conditional line/column mean/median, last observation carried forward, KNN-imputation.
We opted to exclude participants with missing data on all other predictors, given the challenges of applying advanced imputation techniques for missing data in validation studies of risk models.
Because a single imputation strategy based upon regression predictions (as above mentioned) could underestimate the standard errors of estimates, we also used multiple imputation techniques for missing data, previously described by Rubin (1987) and Little and Rubin (2002).
Logistic regression models which incorporate techniques for missing data estimation are used for risk-adjustment; the change in two-year health status is determined as: better than expected, same as expected, or worse than expected [ 10].
Therefore, no imputation technique for missing data was applied.
17 18 We applied five imputations using the Markov chain Monte Carlo technique for missing data in the sample of 18 168 individuals, using the SAS MI and MIANALYSE procedures.
These included the use of multiple imputation rather than the carry forward technique for missing data, consistent with recent recommendations [ 24], as well as a reduced data collection period due to a higher than expected rate of participant recruitment.
Statistical techniques to account for missing data, such as full information maximum likelihood and most current forms of multiple imputation, are less efficient when missingness is dependent on variables with missing data than when it is only dependent on variables with information from all participants [ 20].
The last observed value carried forward technique was used for missing data.
We employed Mplus 5.21 to perform these multivariate analyses and used its full information maximum likelihood technique to account for missing data (Muthén and Muthén, 1998).
