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  • Hot deck to impute wind series

    hello with everyone
    I am a new user in SATA, I investigated a bit about the imputation of data and I saw that the HOT DECK method was very useful, I saw that there is a library or a command to be able to impute the data, but I am not sure how is it done or how does it work in if the codifo, if anyone knows please could you assist me with your help thank you

  • #2
    Jorge:
    welcome to this forum.
    The hot deck approach (ie, drawing a random value from the ones observed and use it to replace a missing value in the same dataset) is a bit old fashioned and suffers from some drawbacks, the most relevant being the absence of variance of the imputed value.
    A preferable approach is multiple imputation, that Stata offers under -mi- entries (see the Stata .pdf manual).
    Kind regards,
    Carlo
    (StataNow 18.5)

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    • #3
      Hi Carlos, I think I will have a problem since I must use the hot deck method for an article, I read several articles where I found that the Hot Deck method also makes a multiple imputation, you know something about it. thanks for your help

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      • #4
        Jorge:
        you can find an interesting description of the single imputation method called "hot deck" at https://www.guilford.com/books/Missi.../9781593853938, pages 182-184.
        Kind regards,
        Carlo
        (StataNow 18.5)

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        • #5

          Carlo: I could not see the book you sent me, since it has a cost, if you could help me with this method or how to use it in STATA it would be very helpful,

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          • #6
            Jorge:
            see: https://www.ncbi.nlm.nih.gov/pmc/art...ihms299474.pdf.
            Sorry I cannot be more helpful.
            Kind regards,
            Carlo
            (StataNow 18.5)

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            • #7
              jorge quishpe , you need to explain how your data are set up. I suspect that wind data are highly skewed and irregular, and hot deck is a method that only works with highly stable and easy to predict data that can be fully explained by less than a handful of categorical variables.
              -- Stas Kolenikov || http://stas.kolenikov.name
              -- Principal Survey Scientist, Abt SRBI
              -- Opinions stated in this post are mine only

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