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in this video I will give a brief overview and a demonstration of how to perform a technique to deal with missing data called multiple imputation this technique is used when we have data that may be missing due to non-response or due to dropout of subjects and if we want to maintain sample size or if we have a situation in which data thats missing is missing in a systematic way which may introduce some bias its in our best interest in order to develop a good hypothesis decision that we replace the data in some way now in other videos I talked about techniques of dealing with missing data called trimming and winds arising in which we just basically remove subjects that have data that are missing and thats certainly appropriate when we have small numbers of missing data usually less than 5% but if we have large numbers of missing data or trimming or winds rising is not appropriate because it may docHubly reduce the sample size we can try and replace the missing data with with one