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Monotone missing data occurs frequently in longitudinal studies.
The problem of missing data occurs in almost all retrospective studies using routine health databases.
Longitudinal data of this kind benefit from careful analysis, especially in small samples or where missing data occurs.
When missing data occurs in a single response (typically analysed within the general linear model), any way of substituting a response will introduce noise rather than being helpful if auxiliary variables are not used [ 12].
For example, if in a clinical trial comparing different types of hip replacement all of the missing data occurs in one particular arm of the trial, the remaining data is unlikely to be representative of the overall result in that group of patients; the missing data may be because those patients went to another hospital for their revision surgery.
Similar(55)
The approach is to use information common to both surveys to impute plausible values of the missing data occurring in both surveys.
Biased estimates from missing data occur when the data are not missing at random [ 42].
The majority of missing data occurred for two items – informal care and medications.
When we aligned the two kinds of monitors, missing data occurred for almost half of the PM2.5 monitors.
To a lesser extent, missing data occurred when there was co-elution between the target chemical and interfering compounds.
We used the chi-square and Fischer's exact tests to examine whether missing data occurred completely at random.
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