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We present a method for imputing or estimating the objective function, based on observations of optimal or nearly optimal choices of the variable for several values of the parameter, and prior knowledge (or assumptions) about the objective.
We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data.
A common method for imputing missing data in such complex studies is to specify, for each of J variables with missing values, a univariate conditional distribution given all other variables, and then to draw imputations by iterating over the J conditional distributions.
We evaluated the KNN method for imputing missing values in the microarray data.
A method for imputing missing data will be considered if necessary.
Moreover, the convergence problems will greatly hinder the application of this method for imputing missing binary data.
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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.
We did not impute missing birth certificate data because validated methods for imputing missing data are unavailable and simple imputation techniques are likely to result in biased estimates [ 31].
11 Mean imputation is one of the most naive and easiest methods for imputing missing values.
It is possible that imputation methods based on ordinal logistic regression, or similar methods for imputing ordinal data would perform well for ordinal variables with a small number of categories.
Attrition bias is common in exercise interventions; we classified studies as having a high risk of bias if they reported different rates of drop out between groups, if they lacked proper methods for controlling for attrition or used inappropriate methods for imputing missing data.
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