Sentence examples for between the missing values from inspiring English sources
Missing completely at random There are no systematic differences between the missing values and the observed values.
The analysis assumes any systematic difference between the missing values and the observed values can be explained by differences in observed data.
Some data are inherently missing not at random because it is not possible to account for systematic differences between the missing values and the observed values using the observed data.
For example, blood pressure measurements may be missing because of breakdown of an automatic sphygmomanometer Missing at random Any systematic difference between the missing values and the observed values can be explained by differences in observed data.
For example, missing blood pressure measurements may be lower than measured blood pressures but only because younger people may be more likely to have missing blood pressure measurements Missing not at random Even after the observed data are taken into account, systematic differences remain between the missing values and the observed values.
Multiple imputation yields valid results under the condition that there are no systematic differences between the missing values and the observed values (missing completely at random) or if systematic differences between missing and observed values can be explained by differences in observed data (missing at random).
All ANOVA analyses contained the following seven factors, each with two levels: β 1 *, β 2 *, missing proportion on X1 (missing missing proportion on X2 (m(X2)), dependency between θ* and the missing values on X1 (d(X1, θ*)), dependency between θ* and the missing values on X2 (d(X2, θ*)), and the imputation method (SMI vs. MMI).
The Linear Mixed Models permit correlations (due to repeated measuring over time) between variables and can handle the missing values in a proper way.
We observed missing data for only 2%% of SOFA scores, for which we calculated mean values between previous and consecutive days around the missing values [ 36].
However, the multifactor dimensionality reduction will tend to give more significant results if the distribution of the missing values is differential between cases and controls, as it assumes one case for every control.
