Missing indicator method was used to analyze categorical variables with missing data.
Finally, a composite indicator method was used to construct the SVI for each year using the following mathematical expression: {text{SVI}} = mathop sum limits_{i}^{n} pm {text{NI}}_{i}where NI is the normalized indicator considered for the computation of the index.
As noted, the indicator method is of general utility and could readily be applied to longer sequences or concatenated multi-gene alignments without substantially increasing computation time, which might address some of these limitations.
The single-thermal indicator method was much more reliable than the prototype, but agreement with the double-indicator method was still disappointing.
Where applicable, the missing indicator method was used [ 18], so that patients with a missing baseline value could be incorporated.
The Missing Indicator Method is applied to categorical exposures and includes an extra category of the exposure variable for those individuals with missing data.
† = In the analysis of the final visit measure adjusting for a baseline that has occasional missing data, the missing indicator method is used.
To handle missing baseline measurements (and therefore increase power), the missing indicator method was used in linear mixed models analyses [ 29].
Although complete case analysis and other ad hoc methods, like mean substitution and the missing-indicator method, are still widely used, researchers are becoming more aware of the perils of applying such methods and many are now employing multiple imputation methods to address the missingness in their data.
The advantages of measuring EVLW by the single or double indicator dilution methods are several; the methods are (superficially) simple to implement, safe, reproducible, and repeatable.
