Timeline for Standard errors of parameters in IRT
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 17, 2019 at 20:33 | comment | added | carlo | This whole speech was about unconditioned distribution of $\theta$, after estimating the model you can infer each $\theta_i$ knowing $y_i$. Of course assumptions on its unconditional distribution are still needed, otherwise you woudn't even know what scale to use. | |
| Oct 17, 2019 at 20:31 | comment | added | carlo | $\theta$ is a latent variable which is not observed in any way, so you don't know its position (mean) nor its scale (variance). that's why, since some assumption about it is necessary, it is fixed to have mean 0 and variance 1. Normal distribution is very convenient in general and it's also the maximum entropy distribution given these constraints, but assuming it doesn't bring any further practical consequence | |
| Oct 17, 2019 at 19:11 | vote | accept | Bananin | ||
| Oct 17, 2019 at 19:11 | comment | added | Bananin | Thanks for the answer, it's great but Ido have one question still. How come you say $theta$ is assumed as a standard normal? I thought both $theta$ and the item parameters were both estimated (by JMLE or MMLE), not fixed. | |
| Oct 15, 2019 at 18:01 | history | bounty ended | CommunityBot | ||
| Oct 14, 2019 at 11:59 | history | answered | carlo | CC BY-SA 4.0 |