Mixed Model

Model Info
Info 
EstimateLinear mixed model fit by REML
CallPassung ~ 1 + content + Umhuellung + content:Umhuellung+( 1 | subject )
AIC11328.206
BIC11375.725
LogLikel.-5659.397
R-squared Marginal0.113
R-squared Conditional0.225
Convergedyes
Optimizerbobyqa
[3]

 

Model Results

Fixed Effect Omnibus tests
 FNum dfDen dfp
content5.87211800.003
Umhuellung30.5311226< .001
content ✻ Umhuellung10.9321182< .001
Note. Satterthwaite method for degrees of freedom

 

Fixed Effects Parameter Estimates
95% Confidence Interval
NamesEffectEstimateSELowerUpperdftp
(Intercept)(Intercept)62.6501.575559.56365.738227039.77< .001
content1Orchester - Trompete-5.3202.9706-11.1420.50221183-1.790.074
content2Sprache - Trompete5.4253.0010-0.45711.306811781.810.071
UmhuellungUmhuellung-0.1260.0228-0.170-0.08121226-5.52< .001
content1 ✻ UmhuellungOrchester - Trompete ✻ Umhuellung-0.2160.0507-0.315-0.11671182-4.26< .001
content2 ✻ UmhuellungSprache - Trompete ✻ Umhuellung-0.1950.0542-0.301-0.08891178-3.60< .001

 

Random Components
GroupsNameSDVarianceICC
subject(Intercept)8.7376.30.126
Residual 22.99528.5 
Note. Number of Obs: 1232 , groups: subject 88

 

Random Effect LRT
TestN. parAICLRTdfp
(1 | subject)7.001140167.71.00< .001

 

Simple Effects

Simple effects of Umhuellung : Omnibus Tests
Moderator levels
contentFNum dfDen dfp
Trompete0.09801.0012140.754
Orchester30.52301.001196< .001
Sprache19.00701.001204< .001

 

Simple effects of Umhuellung : Parameter estimates
Moderator levels95% Confidence Interval
contentEstimateSELowerUpperdftp
Trompete0.01120.0357-0.05890.081312140.3130.754
Orchester-0.20480.0371-0.2775-0.13211196-5.525< .001
Sprache-0.18390.0422-0.2667-0.10121204-4.360< .001

 

Effects Plots

Note: Random effects are plotted by subject

References

[1] The jamovi project (2020). jamovi. (Version 1.6) [Computer Software]. Retrieved from https://www.jamovi.org.

[2] R Core Team (2020). R: A Language and environment for statistical computing. (Version 4.0) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from MRAN snapshot 2020-08-24).

[3] Gallucci, M. (2019). GAMLj: General analyses for linear models. [jamovi module]. Retrieved from https://gamlj.github.io/.