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Tag Archive for rcluster-analysisimputationdimensionality-reduction

Number of observations changing significantly after imputing using mice() in R

My data has a significant number of missing values, so I can’t use the na.omit() default in order to conduct downstream analysis on my dataset, as this removes the whole row if there is even one value absent. It is my understanding that the mice package is a robust way to perform so many consecutive imputations of the data, but after I perform the complete() function, my number of observations jumps from ~60 to 300.