The number of imputations is not most important for me. I am always trying to minimise the bias in point estimates. If I believe that this is successful reasonably, I will continue to estimate the best possible variances (as unbiased as possible, a small overestimate is not not so bad than an underestimate, since it is obvious that our estimate is not completely unbiased). MI does not automatically give any guarantee to the unbiasedness, its 'single basis' should be unbiased. The number of MI-based imputations depends so much on how complex is the variability of the statistic being estimated. In real life the distributions are often complex (skewed, ouliers, etc.). It follows that the number of imputations needs to be higher, 5 or 7 give rarely a satisfactory result. Seppo
Paul von Hippel (28.5.2005 1:57): >I'm looking for work that relates the fraction of missing information >(gamma) to other properties of the data -- e.g., the correlation matrix and >the fraction of values that are missing. > >Any references most appreciated. > >Thanks! >Paul > >Paul von Hippel >Department of Sociology / Initiative in Population Research >Ohio State University > > >_______________________________________________ >Impute mailing list >[email protected] >http://lists.utsouthwestern.edu/mailman/listinfo/impute
