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From |
Richard Williams <richardwilliams.ndu@gmail.com> |

To |
statalist@hsphsun2.harvard.edu, statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Imputation of missing data in an unbalanced panel using ICE |

Date |
Fri, 25 Oct 2013 12:04:15 -0500 |

At 09:09 AM 10/25/2013, James Bernard wrote:

Thanks Antonis, How about taking the average of the imputations for an observation. Let's say we have 7 imputations (m=7). Then for a particular obesrvation, we could take the average of the 7 imputed value? Does this work?

Thanks James On Fri, Oct 25, 2013 at 9:41 PM, A Loumiotis <antonis.loumiotis@gmail.com> wrote: > I would first create a dummy that will be used to tell -ice- which > values to impute: > > ***** > clear > input str1 Firm Year X > "A" 2000 . > "A" 2001 10 > "A" 2002 6 > "A" 2003 . > > "B" 1998 3 > "B" 1999 . > "B" 2000 . > "B" 2001 4 > "B" 2002 6 > "B" 2003 2 > end > > replace X=.a if X==. > reshape wide X, i(Firm) j(Year) > foreach v of varlist X* { > gen c`v'=`v'!=. > replace `v'=0 if c`v'==0 > } > ****** > > I would then run -ice- using the -conditional()- option (you should > fill in the remaining parts for the -ice- command: > ice ..., conditional(X1998:cX1998==1, ...) > > I don't think it is a good idea to use only the results from the first > imputation because your estimates will underestimate the true > variance. > > Antonis >> On Fri, Oct 25, 2013 at 2:46 PM, James Bernard<jamesstatalist@gmail.com> wrote:>> Hi all, >> >> I have been using imputation techniques. Stata offers a wide range of >> commands to conduct imputation. >> >> I have a unbalanced panel data. Several variables have missing values. >> To benefit from the fact that the available observation of a variable >> at certain times can help estimate the missing values at other times, >> I changed the format of my data from long to wide and used ICE using >> the instruction from this site: >> http://www.ats.ucla.edu/stat/stata/faq/mi_longitudinal.htm >> >> These instructions work for a balanced panel data set where all firms >> are supposed to have values in all years. >> >> But, imagine that one firm has to have values from 2000-2003, and >> another from 1998-2003. And, suppose we have a variable (X) for which >> some observations across these two firms are missing >> >> Firm Year X >> --------- --------- ------- >> A 2000 . >> A 2001 10 >> A 2002 6 >> A 2003 . >> >> B 1998 3 >> B 1999 . >> B 2000 . >> B 2001 4 >> B 2002 6 >> B 2003 2 >> >> Reshaping the data from long to wide would lead to: creation of 6 new >> varibale named "X1998", "X1999",......"X2003".... and values of X1998 >> and X1999 will be missing for firm A >> >> And running the ICE, it would predict values for X1998 and X1999 for >> both firm A and B. >> >> The next step is to get the data into long form and run the -mi- >> commands to make the estimation which use Rubin rules for combining >> the data on the m imputations made. >> >> One may argue that I can let the ICE predict the values of X1998 and >> X1999 for firm A. Reshape the data into long format and remove the >> values of X from firm A in 1998 and in 1999, because firm A is not >> supposed to have values in 1998 and 1999. >> >> My question is: Does asking ICE to predict values of X1998 and X1999 >> for firm A affect the way it predicts the value of X2000 (which is the >> main observation we have to impute)? >> >> Does the technique I used make sense? >> >> Also, how wrong is to use only the first imputation (M=1) to run the >> model, instead of using all the imputations? >> >> Thanks, >> James >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/faqs/resources/statalist-faq/ >> * http://www.ats.ucla.edu/stat/stata/ > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

------------------------------------------- Richard Williams, Notre Dame Dept of Sociology OFFICE: (574)631-6668, (574)631-6463 HOME: (574)289-5227 EMAIL: Richard.A.Williams.5@ND.Edu WWW: http://www.nd.edu/~rwilliam * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Imputation of missing data in an unbalanced panel using ICE***From:*James Bernard <jamesstatalist@gmail.com>

**References**:**st: Imputation of missing data in an unbalanced panel using ICE***From:*James Bernard <jamesstatalist@gmail.com>

**Re: st: Imputation of missing data in an unbalanced panel using ICE***From:*A Loumiotis <antonis.loumiotis@gmail.com>

**Re: st: Imputation of missing data in an unbalanced panel using ICE***From:*James Bernard <jamesstatalist@gmail.com>

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