| Model Info | |||
|---|---|---|---|
| Info | |||
| Estimate | Linear mixed model fit by REML | ||
| Call | JOLs ~ 1 + Race + Tipicality + Race:Tipicality+( 0+Race | Subject ) | ||
| AIC | 12668 | ||
| BIC | 12728 | ||
| R-squared Marginal | NaN | ||
| R-squared Conditional | NaN | ||
| Note. R-squared cannot be computed. | |||
| [3] | |||
| Fixed Effect Omnibus tests | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| F | Num df | Den df | p | ||||||
| Race | 3.68 | 1 | 54.0 | 0.060 | |||||
| Tipicality | 61.91 | 1 | 3188.0 | < .001 | |||||
| Race ✻ Tipicality | 6.28 | 1 | 3188.0 | 0.012 | |||||
| Note. Satterthwaite method for degrees of freedom | |||||||||
| Fixed Effects Parameter Estimates | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 95% Confidence Interval | |||||||||||||||||
| Names | Effect | Estimate | SE | Lower | Upper | df | t | p | |||||||||
| (Intercept) | (Intercept) | 4.644 | 0.1317 | 4.38560 | 4.902 | 54.0 | 35.27 | < .001 | |||||||||
| Race1 | White - Black | 0.228 | 0.1188 | -0.00498 | 0.461 | 54.0 | 1.92 | 0.060 | |||||||||
| Tipicality1 | LowTip - HighTip | 0.434 | 0.0551 | 0.32585 | 0.542 | 3188.0 | 7.87 | < .001 | |||||||||
| Race1 ✻ Tipicality1 | White - Black ✻ LowTip - HighTip | 0.276 | 0.1103 | 0.06018 | 0.493 | 3188.0 | 2.51 | 0.012 | |||||||||
| Random Components | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Groups | Name | SD | Variance | ICC | |||||
| Subject | RaceBlack | 0.979 | 0.959 | ||||||
| RaceWhite | 1.081 | 1.168 | |||||||
| Residual | 1.584 | 2.509 | |||||||
| Note. Number of Obs: 3300 , groups: Subject , 55 | |||||||||
| Random Parameters correlations | |||||||
|---|---|---|---|---|---|---|---|
| Groups | Param.1 | Param.2 | Corr. | ||||
| Subject | RaceBlack | RaceWhite | 0.717 | ||||
[1] The jamovi project (2020). jamovi. (Version 1.2) [Computer Software]. Retrieved from https://www.jamovi.org.
[2] R Core Team (2019). R: A Language and envionment for statistical computing. (Version 3.6) [Computer software]. Retrieved from https://cran.r-project.org/.
[3] Gallucci, M. (2019). GAMLj: General analyses for linear models. [jamovi module]. Retrieved from https://gamlj.github.io/.