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Lost in random review download8/31/2023 ![]() ![]() This can be achieved by minimizing the number of follow-up visits, collecting only the essential information at each visit, and developing the userfriendly case-report forms. įirst, the study design should limit the collection of data to those who are participating in the study. The following are suggested to minimize the amount of missing data in the clinical research. The best possible method of handling the missing data is to prevent the problem by well-planning the study and collecting the data carefully. Each of these distortions may threaten the validity of the trials and can lead to invalid conclusions. Fourth, it may complicate the analysis of the study. Third, it can reduce the representativeness of the samples. Second, the lost data can cause bias in the estimation of parameters. First, the absence of data reduces statistical power, which refers to the probability that the test will reject the null hypothesis when it is false. The general topic of missing data has attracted little attention in the field of anesthesiology. However, until recently, most researchers have drawn conclusions based on the assumption of a complete data set. Accordingly, some studies have focused on handling the missing data, problems caused by missing data, and the methods to avoid or minimize such in medical research. The problem of missing data is relatively common in almost all research and can have a significant effect on the conclusions that can be drawn from the data. Missing data (or missing values) is defined as the data value that is not stored for a variable in the observation of interest.
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