Little's test for Missing Completely At Random (MCAR) in R/Stata/SPSS

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Stats with Mia

Stats with Mia

Күн бұрын

Пікірлер: 14
@Sathynne
@Sathynne Жыл бұрын
Yes! Just what I'm studying right now 😭😭, thank you
@thetasworld
@thetasworld 9 ай бұрын
Thank you for this video. I am trying to perform the Little's test using python. Most solutions online weren't really useful, so was wondering if there is a step by step methodology somewhere (video, book etc.)
@carlaprieto1310
@carlaprieto1310 Жыл бұрын
Thanks! I enjoyed this video; however, in R, the "naniar" package's function is only reliable (and only runs) when the dataset is equal or less than 30 variables. Other functions are similarly limited. Are you aware of any alternatives?
@statswithmia
@statswithmia Жыл бұрын
Thanks Carla for this great question. I'm aware of the LittleMCAR function in the BaylorEdPsych package which can handle up to 50 variables. However, this package was removed from the CRAN repository. To use it, you'll need to obtain it from the archive along with the mvnmle package which is required for the LittleMCAR function, as stated here: rdrr.io/cran/misty/man/na.test.html Hope this helps. If anyone has further suggestions for Carla, please leave a comment!
@carlaprieto1310
@carlaprieto1310 Жыл бұрын
@@statswithmia Thank you Mia!
@theresazickert8222
@theresazickert8222 Жыл бұрын
The na.test function of the Misty package can also do it, if I'm not mistaken. :)
@Hkim321
@Hkim321 Жыл бұрын
thank you for the video. very easy to understand!
@statswithmia
@statswithmia Жыл бұрын
Thanks for the feedback!
@MedhaAnand-c4m
@MedhaAnand-c4m Жыл бұрын
Hi.. What if my dataset has categorical variables too? will this still work?
@MasterOfThermik
@MasterOfThermik 5 ай бұрын
Yes, if the data is normal distributed (vgl. Li 2013: 797).
@LeoDupuy
@LeoDupuy 4 ай бұрын
I thought missing at random did not rely on itself but rather other variables?
@moulayyaakoub2931
@moulayyaakoub2931 Жыл бұрын
thanks
@yasserali-uu2vd
@yasserali-uu2vd Жыл бұрын
Using this test gives me a completely right answer: the missing data is MCAR? I really love your learning style.
@statswithmia
@statswithmia Жыл бұрын
If you do not reject H0 (data are MCAR), this means that there is no evidence from your observed data to suggest that the missing data mechanism is MAR. However, you cannot be absolutely certain that the data is not MAR given some variable you haven't observed. You also cannot know if the data is actually MNAR. Hope that helps.
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