Clinical Trials

❘❙❚■ Chapter 30 | Missing DataWhat are the commonly used strategies for dealingwith missing data?When the response is continuous, there are several commonly used strategiesavailable for handling missing data. We will consider these in four categories:• analysis of complete cases only• analysis of all available data without data replacement• last observation carried forward (LOCF) and other ad hoc methodsfor replacing missing values• multiple imputations for replacementAnalysis of complete cases onlyA complete case analysis involves analysis of only those participants who have nomissing values. When dealing with a process that is MCAR, such an analysis willbe unbiased. However, discarding data on participants with some missing valuescan lead to a loss of efficiency. Molenberghs et al. point out that this loss ofefficiency can be particularly severe when there are a large number ofmeasurement occasions [7]. If data are not MCAR then an analysis of completecases will, in general, be biased [7].Analysis of all available dataAnalysis of all available data is generally preferable to analysis of complete cases.Indeed, if the data are MAR (rather than MCAR) then a valid analysis can beobtained through a likelihood-based analysis of all available data, ignoring themissingness mechanism (provided that parameters describing the measurementprocess are functionally independent of parameters describing the missingnessprocess [8,9]).Since an analysis of all available data can still generate unbiased parameterestimates, researchers have coined MAR data as ‘ignorable missingness’. Itshould, however, be borne in mind that the missing data can only be ignored if anappropriate analysis is carried out. We describe such an analysis in a later section.Last observation carried forwardLOCF is another popular strategy, particularly when participants drop out, or thetrial terminates, on a set date (in contrast to intermittent missing values). Here,the last observed value for a participant who drops out is carried forward to eachof the subsequent missed measurement occasions. The analysis that follows doesnot distinguish between the observed and ‘carried forward’ data.342