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May 5, 2017 at 20:59 history edited amoeba
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Jul 26, 2013 at 8:00 answer added tiantianchen timeline score: 2
Jun 20, 2013 at 10:27 comment added Glen_b That's a very good question to ask. You should edit to add that to your question.
Jun 20, 2013 at 10:26 history edited tiantianchen CC BY-SA 3.0
added 38 characters in body
Jun 20, 2013 at 10:20 comment added tiantianchen I know a more standard way to obtain something similar to model2: introduce a second stratification variable-group and apply the model ($\beta$,$\beta_{group}$) to the total_data. The likelihood ratio test would be to test against H0:$\beta_{group}=0$. Is this the same as the method I described above?
Jun 20, 2013 at 10:19 comment added Glen_b You still need to resolve the question of what you mean by "maxlog-likelihood" earlier; I suggest making an edit to clarify both parts of your question.
Jun 20, 2013 at 10:17 comment added tiantianchen Yes, this is what I suppose in this method: the log-likelihoods for the subsets can be added to obtain the overall log-likelihood. I don't know whether this is valid and I need some expert to point out what's the problem with this.
Jun 20, 2013 at 9:40 comment added Glen_b What is 'maxlog-likelihood'? Is it the maximum of the log-likelihood, or the maximizer of it? Whichever it is, why can you sum them? Do you mean instead that the log-likelihoods for the subsets can be added to obtain the overall log-likelihood, or that the maximum value of the overall log-likelihood must always be the sum of the two maximum values obtained on the subsets?
Jun 20, 2013 at 9:38 history edited Glen_b CC BY-SA 3.0
formatting, spelling etc
S Jun 20, 2013 at 9:27 history suggested jonsca CC BY-SA 3.0
Removed thanks, minor grammar
Jun 20, 2013 at 8:51 review Suggested edits
S Jun 20, 2013 at 9:27
Jun 20, 2013 at 8:44 history asked tiantianchen CC BY-SA 3.0