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Imputation of missing data - Multiple imputation using SPSS 

Roger Go
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27 окт 2024

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Комментарии : 23   
@zippity61
@zippity61 Месяц назад
Lifesaver! This is essential when SPSS is unable to handle analysis without that manual pooling of data (which is sometimes the case). I would never have figured this one out!
@nickymccrudden5503
@nickymccrudden5503 11 месяцев назад
Thank you so much for this easy to follow step-by-step guide. Super helpful!!
@junaidkp1941
@junaidkp1941 2 года назад
it was a comprehensive video on handling missing data using MI, especially because you explained how to combine the multiple imputed datasets into a single dataset which I could not see in other videos. if you can explain what to do if there is more than 50% of data missing, and time series missing data, it would be great. thank you for your video...
@Tomekaful
@Tomekaful 3 года назад
Very nicely done and explained when you allow SPSS to choose automatically the imputation approach. I appreciate the OMS walk through.
@chuck636
@chuck636 2 месяца назад
Thanks for this video. Is SPSS pooling the different datasets using Rubin’s rules?
@khadidjabelmouhoub4324
@khadidjabelmouhoub4324 8 дней назад
can I use this method when the missing data are categorical? if so, are there conditions to check out before using the method?
@badawysaied7069
@badawysaied7069 Год назад
Thank you so much for that. That's really helpful.
@qimeng9800
@qimeng9800 4 года назад
Much appreciated for your wonderful video! So after the pooled dataset is created, we can use this final dataset to do further analysis right? Will it happen that some values in the output are not shown? Cause it does happen when I use several imputation datasets to do t-test or regression. Looking forward to hearing from you!
@maryamdanesh6558
@maryamdanesh6558 4 года назад
Thank you so much, this was really helpful and all clear.
@lattesrgood
@lattesrgood 2 года назад
Hi thank you for this video, it was so helpful!! Why would you use the random number generator instead of the replace missing values function? Thanks again :)
@MegaSvechen
@MegaSvechen 3 года назад
Thanks for the video! Does this method apply for only left censored data (concentrations below the lower detection limit)?
@nihilfit4537
@nihilfit4537 2 года назад
Any methods paper citation for this approach?
@gracehou467
@gracehou467 7 месяцев назад
can i add "IF" statement in the MI syntax?
@azku
@azku 2 года назад
When we analyse the data, can we mix the dependent and independent variables?
@darrengeorge3417
@darrengeorge3417 3 года назад
Well done!
@mosun6390
@mosun6390 3 года назад
Thank you! But, help! when I do the "split file" step, the warning says:The dataset cannot be analyzed as a multiple imputation dataset unless variable Imputation_ is defined as a SPLIT FILE variable.
@OhMyGodItsPianoMusic
@OhMyGodItsPianoMusic 3 года назад
I'm having the same issue. Did you found any solution?
@justinedewith7037
@justinedewith7037 2 года назад
@@OhMyGodItsPianoMusic I have to same problem, how did you solve this? Thank you!:)
@gonzalorenatoquintanazunin6984
@gonzalorenatoquintanazunin6984 2 года назад
gee I got the same error. Were you able to find an answer?
@ffrroottmaann
@ffrroottmaann 2 года назад
the same error was displayed at my datas. I just continued with the steps and it worked out perfectly :) and the datas seem to be correct
@nguyenthithanhtam721
@nguyenthithanhtam721 Год назад
Thanh ou for very comprehensive video. I followed until the splits table steps then it became struggled. Its said " >Warning # 4762. Command name: SPLIT FILE >Final (pooled) results for multiply imputed data cannot be added to output >tables when the SPLIT FILE SEPARATE option is chosen. Use the SPLIT FILE >LAYERED option instead. Can anyone explain me why?
@toumighada3275
@toumighada3275 Год назад
I dont know why it didn't work with me 😢
@datascientist2958
@datascientist2958 4 года назад
How can we implement Predictive mean matching for missing values?
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