Timeline for Is LMM a good alternative for Repeated Measures ANOVA with Missing Data?
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| S Nov 20 at 3:04 | history | suggested | Mario | CC BY-SA 4.0 |
Edit and grammar correction in title and question body for better understanding
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| Nov 20 at 1:51 | review | Suggested edits | |||
| S Nov 20 at 3:04 | |||||
| Nov 19 at 9:08 | comment | added | Sointu | In my opinion, yes. Or well, wrong is of course relative, but it gives you a very different sample size estimate from all other software I'm aware of. See here: stats.stackexchange.com/questions/535159/… | |
| Nov 17 at 17:23 | comment | added | anna eyre | @Sointu Hi, I was reading about the differences between the effect size specifications in GPower. Do you think using the default option is the wrong choice? Or can it be somehow justified? I've seen published papers where the default option was used for sample size calculation. Thank you for your insight. | |
| Nov 16 at 19:24 | comment | added | anna eyre | @Sointu Hi, thank you for the message. Yes, I used the default settings. I was trying to figure out if that option is justifiable, and I have also contacted the GPower creators, who recommended that it be. If you think using the default option is an issue, I'm happy to hear your suggestion. | |
| Nov 16 at 10:25 | comment | added | Sointu | Sorry to comment on a side issue, but about your power calculations: did you change the effect size specification from GPower options to "As in Cohen (1988)"? If you used the default "As in GPower 3.0", you likely got a too small sample size estimate. The default uses an uncommon effect size metric that incorporates the assumed repeated-measures correlation into the formula. | |
| Nov 15 at 0:55 | history | became hot network question | |||
| Nov 14 at 18:32 | answer | added | jarbet | timeline score: 8 | |
| Nov 14 at 16:54 | history | asked | anna eyre | CC BY-SA 4.0 |