Timeline for Mixed model for learning data?
Current License: CC BY-SA 3.0
9 events
| when toggle format | what | by | license | comment | |
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| May 22, 2015 at 1:07 | comment | added | rnso | I agree with you. I have removed that part from my answer. | |
| May 22, 2015 at 1:07 | history | edited | rnso | CC BY-SA 3.0 |
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| May 21, 2015 at 18:46 | comment | added | Cliff AB | So it's my understanding that the number of sessions per subject is fixed, so yes, the estimate of the difference between groups would be same. But the standard error would be invalid because the assumption of independent measurements would be (very) incorrect. | |
| May 21, 2015 at 18:32 | comment | added | rnso | I believe number of sessions are same for each subject. Hence it may not matter very much if we make means for each subject first and then do the t-test or do t-test for whole data. Though sample size will be larger but so will be the variability. | |
| May 21, 2015 at 17:56 | comment | added | Cliff AB | But t-test(resp ~ sex) sounds like you are just doing a test on all the individual scores for each subject, not the combined scores, which would not account for repeated measures on the same subject. Or am I misunderstanding what you mean by t-test(resp~sex)? I'm just not clear on how this accounts for within subject correlation (but perhaps I'm not quite following what you mean). | |
| May 21, 2015 at 17:55 | comment | added | Cliff AB | I'm very much a fan of using a combined score (i.e. mean of all scores) for each subject. Then each combined score is then assumed independent and a simple t-test can be used. It probably even makes sense to have a weighted average, where the later responses are heavier weighted (as we would expect difference in learning to show up in the later trials). | |
| May 21, 2015 at 16:59 | history | edited | rnso | CC BY-SA 3.0 |
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| May 21, 2015 at 16:38 | review | Low quality posts | |||
| May 21, 2015 at 16:48 | |||||
| May 21, 2015 at 16:21 | history | answered | rnso | CC BY-SA 3.0 |