Paul Allison wrote: > I completely agree with Frank Harrell that this is not, in general, a good > method. I haven't checked out all his references but, for me, the definitive > refutation was Jones' 1996 paper in the Journal of the American Statistical > Association.
And I reference your excellent 2001 book, p. 9-11. > > Nevertheless, I still believe that this method may be useful in two > situations: > > 1. Data are "missing" because a variable doesn't apply or is undefined for > some fraction of cases. For example, suppose you have a measure of marital > happiness, dichotomized as high or low, but your sample contains some > unmarried people. Then it is entirely appropriate to have a 3-category > variable with values high, low, and unmarried. Nice example Paul. I've added that to my notes and book, with attribution. > > 2. The goal is to build a forecasting model, and it is anticipated that a > substantial fraction of the new cases to be forecast will have missing data > on one or more variables. Here, the goal is not to get unbiased estimates of > population parameters but to minimize some function of prediction errors. A > workable forecasting model must have some way of dealing with the cases that > have missing data. Maybe there are better ways, but I've found almost no > literature on this topic (with the exception of Warren Sarle's unpublished > paper). My colleagues Janssen, Donders, and Moons in The Netherlands are working on that. Averaging predictions over multiple imputations is one approach but there are others. There are some logistical problems to imputing especially with regard to updating the imputation rules. Cheers, Frank > > ----------------------------------------------------------------- > Paul D. Allison, Professor > Department of Sociology > University of Pennsylvania > 581 McNeil Building > 3718 Locust Walk > Philadelphia, PA 19104-6299 > 215-898-6717 > 215-573-2081 (fax) > http://www.ssc.upenn.edu/~allison > > > -----Original Message----- > From: [email protected] > [mailto:[email protected]] On Behalf Of Maria da > Conceicao-Saraiva > Sent: Saturday, July 04, 2009 9:19 AM > To: [email protected] > Subject: [Impute] weird question > > > > > Sorry about this question, > > I have been discussing with some people I am working about the need of > imputation with some of our data. What some of analysist are doing is just > to creating a category of missing values inside some variables, they argue > this is enough. It has been hard to argue with them that this is not the > best way to do. Specially in our variable income, we have about 30% of > missings. > Does anybody know about refereces discussing this approach of just > creating a category for missing values inside a variable? > > Maria > > > > > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > ~~ > Maria da Conceicao P. Saraiva DDS, MSc, Ph.D > Departamento de Clinica Infantil e Odontologia Social e Preventiva > Faculdade de Odontologia de Ribeirao Preto-Universidade de Sao Paulo > > Aviso: Esta mensagem destina-se exclusivamente ao destinatario, sendo > confidencial. Se V. Sa. nao eh o destinatario, fique advertido de que a > divulgacao, distribuicao ou copia desta mensagem eh estritamente proibida. > Caso tenha recebido esta mensagem por engano, por favor avise > imediatamente seu remetente atraves de resposta por e-mail. Obrigado. > -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University
