This procedure imputes a number of values for the missing data incorporating both the variability of the QoL measure and the uncertainty surrounding the missing observation.
This approach permits complete data methods for analysis, reduces bias due to missing data, and incorporates imputation error into standard errors.
An appropriate analysis should then use these variables to model the likelihood of having missing data, and incorporate the uncertainty associated with the modeling process.
This approach has a solid theoretical foundation, offers a probabilistic framework to describe the variation typically observed in microarray data, accommodates missing data, and incorporates prior knowledge on gene relationships.
To study the effects of accounting for missing data and incorporating model stability we used a large clinical data set in which we empirically evaluated different methods of deriving a prognostic model.
Mixed-model repeated measures (MMRM) analyses will be used since this approach can include participants with missing data and incorporate data from intermediate measurement time points of four and eight weeks.
Second, by virtue of its probabilistic nature, uncertain observations can be incorporated, missing data can be managed, and flexible queries to probe and explain predictions can be entertained [ 20, 21].
Thus, to have a balanced design, the analysis for Year 1 was conducted using a reduced form, that is using only the three common abilities in the eight units since systematic missing data cannot be legitimately incorporated in the model proposed.
The only principled approach is to attempt to model the missing data mechanism and incorporate this into one's analysis.
Methods of item and person parameter estimation which incorporate missing data in the item responses have long been developed and have been proved to be suitable (Lord [1974], [1983]; Mislevy et al. [1992]).
