Instructions
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1. Each variable must be coded as 0 or 1 with the type of numeric-continuous in jamovi.
2. Person Analysis will be displayed in the datasheet.
3. The result tables are estimated by Marginal Maximum Likelihood estimation(MMLE).
4. The rationale of snowIRT module is described in the documentation.
5. Feature requests and bug reports can be made on my GitHub.
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| Model Fit | |||
|---|---|---|---|
| Person Reliability | |||
| scale | -0.260 | ||
| [3] | |||
| Item Statistics | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Proportion | Measure | S.E.Measure | Infit | Outfit | |||||||
| Item1 | 0.0500 | 2.944 | 0.324 | 1.000 | 1.000 | ||||||
| Item2 | 0.0850 | 2.376 | 0.254 | 1.000 | 1.000 | ||||||
| Item3 | 0.0750 | 2.512 | 0.268 | 1.000 | 1.000 | ||||||
| Item4 | 0.6600 | -0.663 | 0.149 | 1.000 | 1.000 | ||||||
| Item5 | 0.1350 | 1.857 | 0.207 | 1.000 | 1.000 | ||||||
| Item6 | 0.2100 | 1.325 | 0.174 | 1.000 | 1.000 | ||||||
| Item7 | 0.3650 | 0.554 | 0.147 | 1.000 | 1.000 | ||||||
| Item8 | 0.3000 | 0.847 | 0.154 | 1.000 | 1.000 | ||||||
| Item9 | 0.2700 | 0.995 | 0.159 | 1.000 | 1.000 | ||||||
| Item10 | 0.2000 | 1.386 | 0.177 | 1.000 | 1.000 | ||||||
| Note. Infit= Information-weighted mean square statistic; Outfit= Outlier-sensitive means square statistic. | |||||||||||
| [3] | |||||||||||
[5]
| Model Info | |||
|---|---|---|---|
| Info | |||
| Get started | Select the dependent variable | ||
| Get started | Select at least one cluster variable | ||
| Get started | Select at least one term in Random Effects | ||
| [6] | |||
| Fixed Effect Omnibus tests | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| F | Num df | Den df | p | ||||||
| Fixed Effects Parameter Estimates | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Names | Effect | Estimate | SE | Lower | Upper | df | t | p | |||||||||
| Random Components | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Groups | Name | SD | Variance | ICC | |||||
[1] The jamovi project (2022). jamovi. (Version 2.3) [Computer Software]. Retrieved from https://www.jamovi.org.
[2] R Core Team (2021). R: A Language and environment for statistical computing. (Version 4.1) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from MRAN snapshot 2022-01-01).
[3] Robitzsch,A., Kiefer, T., & Wu, M. (2020). TAM: Test Analysis Modules. (Version 4.1.4)[R package]. Retrieved from https://CRAN.R-project.org/package=TAM.
[4] Martinkova, P., & Drabinova, A. (2018). ShinyItemAnalysis: for teaching psychometrics and to enforce routine analysis of educational tests. (Version 1.4.2)[R package]. Retrieved from https://CRAN.R-project.org/package=ShinyItemAnalysis.
[5] Seol, H. (2023). snowIRT: Item Response Theory for jamovi. (Version 4.8.8)[jamovi module]. URL https://github.com/hyunsooseol/snowIRT.
[6] Gallucci, M. (2019). GAMLj: General analyses for linear models. [jamovi module]. Retrieved from https://gamlj.github.io/.