| Model Info | |||||
|---|---|---|---|---|---|
| Info | |||||
| Model Type | Mixed Model | Linear Mixed model for continuous y | |||
| Model | lmer | varA ~ 1 + varB + condition + condition:varB + ( 1 + varB | subjects ) | |||
| Distribution | Gaussian | Normal distribution of residuals | |||
| Direction | y | Dependend variable scores | |||
| Optimizer | bobyqa | ||||
| DF method | Satterthwaite | ||||
| Sample size | 52 | ||||
| Converged | yes | ||||
| Y transform | none | ||||
| C.I. method | Wald | ||||
| Note. (Almost) singular fit. Maybe random coefficients variances are too small or correlations among them too large. | |||||
| [3] | |||||
| Model Fit | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Type | R² | df | LRT X² | p | |||||
| Conditional | 0.1184 | 6 | 2.8669 | 0.825 | |||||
| Marginal | 0.0536 | 3 | 2.8669 | 0.413 | |||||
| Note. There were problems in model convergence. Results may be biased. Try to specify a different random component. | |||||||||
| [4] | |||||||||
| Fixed Effects Omnibus Tests | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| F | df | df (res) | p | ||||||
| varB | 0.02159 | 1 | 3.919 | 0.890 | |||||
| condition | 2.46168 | 1 | 46.551 | 0.123 | |||||
| varB ✻ condition | 0.41201 | 1 | 46.558 | 0.524 | |||||
| Parameter Estimates (Fixed coefficients) | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 95% Confidence Intervals | |||||||||||||||||
| Names | Effect | Estimate | SE | Lower | Upper | df | t | p | |||||||||
| (Intercept) | (Intercept) | 0.54175 | 0.04147 | 0.45817 | 0.6253 | 19.240 | 13.0632 | < .001 | |||||||||
| varB | varB | 0.02916 | 0.19843 | -0.37075 | 0.4291 | 3.919 | 0.1469 | 0.890 | |||||||||
| condition1 | cond_B - cond_A | 0.12869 | 0.08202 | -0.03662 | 0.2940 | 46.551 | 1.5690 | 0.123 | |||||||||
| varB ✻ condition1 | varB ✻ (cond_B - cond_A) | -0.21469 | 0.33447 | -0.88876 | 0.4594 | 46.558 | -0.6419 | 0.524 | |||||||||
| [5] | |||||||||||||||||
| Random Components | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Groups | Name | Variance | SD | ICC | |||||
| subjects | (Intercept) | 8.044e-4 | 0.02836 | 0.009850 | |||||
| varB | 0.08319 | 0.28842 | |||||||
| Residual | 0.08087 | 0.28437 | |||||||
| Note. Number of Obs: 52 , Number of groups: subjects 9 | |||||||||
Note: The X-axis is in the X-variable original scale
[1] The jamovi project (2024). jamovi. (Version 2.5) [Computer Software]. Retrieved from https://www.jamovi.org.
[2] R Core Team (2023). R: A Language and environment for statistical computing. (Version 4.3) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2024-01-09).
[3] Gallucci, M. (2019). GAMLj: General analyses for linear models. [jamovi module]. Retrieved from https://gamlj.github.io/.
[4] Gallucci, M. (2020). Model goodness of fit in GAMLj. . link.
[5] Lüdecke, Ben-Shachar, Patil & Makowski (2020). Extracting, Computing and Exploring the Parameters of Statistical Models using R. CRAN. link.