ethnicity: a missing variable when defining normative values for reporting echocardiographic studies

Missing values in epidemiological studies

Handling Missing Values when Applying Classication Models

Much work has studied the e¤ect of di¤erent treatments of missing values on model induction, but little work has analyzed treatments for the common case of missing values at prediction time. This paper …rst compares several di¤erent methods— predictive value imputation, the distribution-based imputation used by C4.5, and using reduced models— for applying classi…cation trees to instances with m...

Handling Missing Values when Applying Classification Models

Much work has studied the effect of different treatments of missing values on model induction, but little work has analyzed treatments for the common case of missing values at prediction time. This paper first compares several different methods—predictive value imputation, the distributionbased imputation used by C4.5, and using reduced models—for applying classification trees to instances with...

A BAYESIAN APPROACH TO COMPUTING MISSING REGRESSOR VALUES

In this article, Lindley's measure of average information is used to measure the information contained in incomplete observations on the vector of unknown regression coefficients [9]. This measure of information may be used to compute the missing regressor values.

Optimal Design When Outcome Values Are Not Missing at Random

The presence of missing values complicates statistical analyses. In design of experiments, missing values are particularly problematic when constructing optimal designs, as it is not known which values are missing at the design stage. When data are missing at random it is possible to incorporate this information into the optimality criterion that is used to find designs; Imhof, Song, and Wong (...

Dealing with missing predictor values when applying clinical prediction models.

BACKGROUND Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with such missing values. We evaluated 6 strategies to deal with missing values. METHODS We developed an...