Matt: I have a follow-up question. The situation is I'm pooling probation data across states and years (1980 to 2011) in the early years there were only a handful of questions, and in the mid-1990s the government (Department of Justice) included several new items. So, for instance, they started to ask about the number of people on probation for DWI. I'm thinking the answer is no. By the way, I'm not seeing the vignettes - did you mean page 4 of the Amelia user guide or one of the related publications? I checked both, but must be missing it. Thanks for your help. Matthew From: Matt Blackwell [mailto:m.blackwell@rochester.edu] Sent: Thursday, November 14, 2013 3:55 PM To: DeMichele, Matthew Cc: amelia(a)lists.gking.harvard.edu Subject: Re: [amelia] amelia help Hi Matthew, It is definitely acceptable to impute earlier questions as long as they overlap with other questions that are asked throughout the entire dataset and that those observed values predict the missing values. The key idea to consider is whether or not that data is missing at random (MAR) given you set of observed variables (see pg 4 of our vignette/documentation). If it is, then you can and should impute those observations. Hope that helps! Cheers, Matt ~~~~~~~~~~~ Matthew Blackwell Assistant Professor of Political Science University of Rochester url: http://www.mattblackwell.org On Thu, Nov 14, 2013 at 3:20 PM, DeMichele, Matthew <mdemichele(a)rti.org> wrote: I have a question about the appropriateness of using Amelia to impute some data for items that were not asked in earlier years of a survey. I'm working with a governmental survey collection that started in 1975 and continues up to the present day. The data are in long form arranged by state and year. My question is that certain items were not asked in the earlier years that are asked now. Is appropriate to impute the data for these earlier years? Initially, I planned to develop multiple datasets to maximize years and states, but I started thinking this may be an imputation issue as well. Best regards, Matthew -- Amelia mailing list served by HUIT [Un]Subscribe/View Archive: https://urldefense.proofpoint.com/v1/url?u=http://lists.gking.harvard.ed u/?info%3Damelia&k=p4Ly7qpEBiYPBVenR9G2iQ%3D%3D%0A&r=jLgdG6f%2BQq4pzHWI0 S37ROhc5Jfy9q9oKEsPDdQXskc%3D%0A&m=ye9%2FRpgELrol%2BEn7oUPshDjffMGguNCpz 3ETPlSZ5%2FU%3D%0A&s=e0d8d8226141c0c58799504c6596958593befbfa6080ce8bd98 1f50276a05dc8 More info about Amelia: https://urldefense.proofpoint.com/v1/url?u=http://gking.harvard.edu/amel ia&k=p4Ly7qpEBiYPBVenR9G2iQ%3D%3D%0A&r=jLgdG6f%2BQq4pzHWI0S37ROhc5Jfy9q9 oKEsPDdQXskc%3D%0A&m=ye9%2FRpgELrol%2BEn7oUPshDjffMGguNCpz3ETPlSZ5%2FU%3 D%0A&s=ac1ac4d23c61675a23da3af6f97d04de9576897ca928c0c17d040c06bd126a04 Amelia mailing list Amelia(a)lists.gking.harvard.edu To unsubscribe from this list or get other information: https://urldefense.proofpoint.com/v1/url?u=https://lists.gking.harvard.e du/mailman/listinfo/amelia&k=p4Ly7qpEBiYPBVenR9G2iQ%3D%3D%0A&r=jLgdG6f%2 BQq4pzHWI0S37ROhc5Jfy9q9oKEsPDdQXskc%3D%0A&m=ye9%2FRpgELrol%2BEn7oUPshDj ffMGguNCpz3ETPlSZ5%2FU%3D%0A&s=20346a43e06d5ab87f7654e0728a5e10626f07987 849e362d244206cd852b4e0

Hi Matt: Yes, that definitely helps. Thanks for the explanation. Best, Matthew From: Matt Blackwell [mailto:m.blackwell@rochester.edu] Sent: Thursday, November 14, 2013 4:15 PM To: DeMichele, Matthew Cc: amelia(a)lists.gking.harvard.edu Subject: Re: [amelia] amelia help Hi Matthew, The imputations you get will be based on the observed data you do have. So, what Amelia would do is impute the earlier data using the relationships between the always observed variables and the new DoJ items from the later part of the data. This is perfectly valid as long as the always observed variables are good predictors of the DoJ items in both time periods. It's much less important that there are other variables that are also missing in the earlier time period. This might increase the uncertainty of the imputations, but this would be reflected in the variance of the imputed values between imputations. Here's a link to the vignette/manual: http://cran.r-project.org/web/packages/Amelia/vignettes/amelia.pdf You can also see the second and third pages of the 2001 APSR article: http://gking.harvard.edu/files/gking/files/evil.pdf Hope that helps! Cheers, Matt On Thu, Nov 14, 2013 at 4:09 PM, DeMichele, Matthew &lt;mdemichele(a)rti.org&gt; wrote: Matt: I have a follow-up question. The situation is I'm pooling probation data across states and years (1980 to 2011) in the early years there were only a handful of questions, and in the mid-1990s the government (Department of Justice) included several new items. So, for instance, they started to ask about the number of people on probation for DWI. I'm thinking the answer is no. By the way, I'm not seeing the vignettes - did you mean page 4 of the Amelia user guide or one of the related publications? I checked both, but must be missing it. Thanks for your help. Matthew From: Matt Blackwell [mailto:m.blackwell@rochester.edu] Sent: Thursday, November 14, 2013 3:55 PM To: DeMichele, Matthew Cc: amelia(a)lists.gking.harvard.edu Subject: Re: [amelia] amelia help Hi Matthew, It is definitely acceptable to impute earlier questions as long as they overlap with other questions that are asked throughout the entire dataset and that those observed values predict the missing values. The key idea to consider is whether or not that data is missing at random (MAR) given you set of observed variables (see pg 4 of our vignette/documentation). If it is, then you can and should impute those observations. Hope that helps! Cheers, Matt ~~~~~~~~~~~ Matthew Blackwell Assistant Professor of Political Science University of Rochester url: http://www.mattblackwell.org[mattblackwell.org] <https://urldefense.proofpoint.com/v1/url?u=http://www.mattblackwell.org &k=p4Ly7qpEBiYPBVenR9G2iQ%3D%3D%0A&r=jLgdG6f%2BQq4pzHWI0S37ROhc5Jfy9q9oK EsPDdQXskc%3D%0A&m=j8KabD9876UGwmw%2Fh2oog4UEo0VeP9BT0rC8o28GdFs%3D%0A&s =83816f026a9f7793e4370876fe625205c891d79fe6e08b1d28dd28bfef6695b8> On Thu, Nov 14, 2013 at 3:20 PM, DeMichele, Matthew &lt;mdemichele(a)rti.org&gt; wrote: I have a question about the appropriateness of using Amelia to impute some data for items that were not asked in earlier years of a survey. I'm working with a governmental survey collection that started in 1975 and continues up to the present day. The data are in long form arranged by state and year. My question is that certain items were not asked in the earlier years that are asked now. Is appropriate to impute the data for these earlier years? Initially, I planned to develop multiple datasets to maximize years and states, but I started thinking this may be an imputation issue as well. Best regards, Matthew -- Amelia mailing list served by HUIT [Un]Subscribe/View Archive: https://urldefense.proofpoint.com/v1/url?u=http://lists.gking.harvard.ed u/?info%3Damelia&k=p4Ly7qpEBiYPBVenR9G2iQ%3D%3D%0A&r=jLgdG6f%2BQq4pzHWI0 S37ROhc5Jfy9q9oKEsPDdQXskc%3D%0A&m=ye9%2FRpgELrol%2BEn7oUPshDjffMGguNCpz 3ETPlSZ5%2FU%3D%0A&s=e0d8d8226141c0c58799504c6596958593befbfa6080ce8bd98 1f50276a05dc8 More info about Amelia: https://urldefense.proofpoint.com/v1/url?u=http://gking.harvard.edu/amel ia&k=p4Ly7qpEBiYPBVenR9G2iQ%3D%3D%0A&r=jLgdG6f%2BQq4pzHWI0S37ROhc5Jfy9q9 oKEsPDdQXskc%3D%0A&m=ye9%2FRpgELrol%2BEn7oUPshDjffMGguNCpz3ETPlSZ5%2FU%3 D%0A&s=ac1ac4d23c61675a23da3af6f97d04de9576897ca928c0c17d040c06bd126a04 Amelia mailing list Amelia(a)lists.gking.harvard.edu To unsubscribe from this list or get other information: https://urldefense.proofpoint.com/v1/url?u=https://lists.gking.harvard.e du/mailman/listinfo/amelia&k=p4Ly7qpEBiYPBVenR9G2iQ%3D%3D%0A&r=jLgdG6f%2 BQq4pzHWI0S37ROhc5Jfy9q9oKEsPDdQXskc%3D%0A&m=ye9%2FRpgELrol%2BEn7oUPshDj ffMGguNCpz3ETPlSZ5%2FU%3D%0A&s=20346a43e06d5ab87f7654e0728a5e10626f07987 849e362d244206cd852b4e0