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Apr 7, 2022 at 14:25 history edited kjetil b halvorsen CC BY-SA 4.0
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Sep 27, 2018 at 10:42 history edited kjetil b halvorsen
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Sep 23, 2018 at 19:04 vote accept ecjb
Sep 23, 2018 at 15:51 comment added ecjb Dear @mdewey. Thank you very much for your answer. Provided the simulated data, do you have an idea of the code which should be run to perform a logistic regression using glmnet?
Sep 23, 2018 at 15:22 answer added Sal Mangiafico timeline score: 2
Sep 23, 2018 at 14:52 comment added mdewey If your outcome variable is genuinely always 1 as you suggest in your introduction then you have separation in your mixed model which probably accounts for (a) the huge estimates on the log scale, (b) the huge standard errors, (c) the failure of the model to converge. See stats.stackexchange.com/questions/11109/… for some more information.
Sep 23, 2018 at 14:18 history edited ecjb CC BY-SA 4.0
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Sep 23, 2018 at 14:11 comment added ecjb Thank you for your comment @SalMangiafico. I added your seed and adapted the ouput. Any idea why there is a difference between output of post hoc chi square and logistic regression?
Sep 23, 2018 at 14:06 history edited ecjb CC BY-SA 4.0
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Sep 23, 2018 at 13:39 comment added Sal Mangiafico As you say in your question, the mixed model is the preferable one. When I run your code, I get very different answers for each run. Maybe you want to start your sample code with e.g. set.seed(12345), so that everyone gets the same results?
Sep 23, 2018 at 13:28 comment added mdewey The best model is the mixed one.
Sep 23, 2018 at 10:59 history edited ecjb CC BY-SA 4.0
removed the serial chi square tests by one single post-hoc t-test
S Sep 23, 2018 at 9:14 history suggested Patty CC BY-SA 4.0
Added formatting to variables for ease of reading
Sep 23, 2018 at 9:05 review Suggested edits
S Sep 23, 2018 at 9:14
Sep 23, 2018 at 7:30 history edited ecjb CC BY-SA 4.0
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Sep 23, 2018 at 6:56 history migrated from stackoverflow.com (revisions)
Sep 22, 2018 at 22:40 history asked ecjb CC BY-SA 4.0