Exact(14)
Secondly, persons with missing predictors are often excluded.
Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures.
Therefore, we also calculated a second set of weights by multiply imputing missing predictors of missingness.
Alternatively, it is possible to quantify the usefulness of a prediction model in a more realistic future clinical setting where individuals may have some missing predictors.
This imputation procedure is useful to imitate a future clinical setting in which individuals have unknown outcome and partly missing predictors.
Robins and Gill (1997) propose a procedure for handling such missingness, but this is complicated to use and limited in practice to a small number of missing predictors.
Similar(46)
To illustrate the sequence of steps needed to develop and validate a clinical prediction model, when missing predictor values have been multiply imputed.
We therefore restricted ourselves to a comparison of cases with and without missing predictor values.
Missing predictor values were dealt with using a multiple imputation method.
The proportions of missing predictor values were between 5.5 and 6.5 %.
Our primary method for dealing with missing predictor values will be multiple imputation using a regression modeling approach [ 60].
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