Timeline for Which mixed model in lme4 best mimics the unstructured covariance in GLS?
Current License: CC BY-SA 4.0
9 events
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| Apr 1 at 18:26 | comment | added | Evan | @Tereira maybe the mmrm package (cran.r-project.org/web/packages/mmrm/index.html)? | |
| Apr 5, 2022 at 5:42 | history | edited | Tereira | CC BY-SA 4.0 |
added 165 characters in body; edited title
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| Apr 5, 2022 at 5:40 | comment | added | Tereira | Can anyone help me in my problem, rather than telling me it's not my problem? I said that nothing else will be accepted in my work, regardless of whether it's good or not, and I strongly, kindly please guiding me in THIS very problem, rather than giving me twice an advice that doesn't help me. | |
| Apr 4, 2022 at 12:59 | comment | added | Frank Harrell | Any method for longitudinal data analysis in frequentist statistics is approximate so I personally wouldn't get so connected to any one method such as Kenward-Rogers. | |
| Apr 4, 2022 at 6:51 | comment | added | Tereira | @BenBolker maybe you could guide me, please? | |
| Apr 3, 2022 at 18:50 | comment | added | Tereira | The GLS naturally supports the "unstructured", it doesn't support the Kenward-Roger. It's a must in my field and I was told no other degrees of freedom will be accepted. Only the lme4 supports this, but it's a different approach. Could you guide me, please, which approach is the closest to the unstructured R in lme4? I'm allowed only to use this very package. So I can choose: either random slopes, or random both. | |
| Apr 3, 2022 at 18:44 | comment | added | Frank Harrell |
There must be a way to use an unstructure covariance matrix with the gls function. If you can't find the trick there there is probably a different implementation of GLS that will do it. Random slopes and intercepts introduce computational problems and complexity. But if you want to mimic an unstructure correlation pattern you may need a random shapes model.
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| S Apr 3, 2022 at 16:37 | review | First questions | |||
| Apr 3, 2022 at 17:36 | |||||
| S Apr 3, 2022 at 16:37 | history | asked | Tereira | CC BY-SA 4.0 |