Results

Descriptives

Descriptives
	group	A	B
N	young	15	15
	old	5	5
Mean	young	-0.257	0.693
	old	0.729	1.564

Repeated Measures ANOVA

Within Subjects Effects
	Sum of Squares	df	Mean Square	F	p
Condition	5.977	1	5.977	11.049	0.004
Condition ✻ group	0.025	1	0.025	0.046	0.833
Residual	9.738	18	0.541
Note. Type 3 Sums of Squares

[3]

Between Subjects Effects
	Sum of Squares	df	Mean Square	F	p
group	6.463	1	6.463	2.070	0.167
Residual	56.191	18	3.122
Note. Type 3 Sums of Squares

Post Hoc Tests

Post Hoc Comparisons - Condition ✻ group
Comparison
Condition	group		Condition	group	Mean Difference	SE	df	t	p
A	young	-	A	old	-0.986	0.699	24.057	-1.411	0.171
		-	B	young	-0.950	0.269	18.000	-3.538	0.002
		-	B	old	-1.821	0.699	24.057	-2.606	0.015
	old	-	B	young	0.036	0.699	24.057	0.051	0.960
		-	B	old	-0.835	0.465	18.000	-1.795	0.089
B	young	-	B	old	-0.871	0.699	24.057	-1.246	0.225

[4]

Estimated Marginal Means

Condition

Estimated Marginal Means - Condition
			95% Confidence Interval
Condition	Mean	SE	Lower	Upper
A	0.004	0.310	-0.634	0.641
B	0.896	0.310	0.259	1.534

group

Estimated Marginal Means - group
			95% Confidence Interval
group	Mean	SE	Lower	Upper
young	-0.014	0.427	-0.911	0.882
old	0.914	0.427	0.018	1.811

Condition ✻ group

Estimated Marginal Means - Condition ✻ group
				95% Confidence Interval
group	Condition	Mean	SE	Lower	Upper
young	A	-0.489	0.447	-1.418	0.440
	B	0.461	0.447	-0.468	1.390
old	A	0.497	0.486	-0.499	1.492
	B	1.332	0.486	0.336	2.328

[4]

Mixed Model

Model Info
Info
Estimate		Linear mixed model fit by REML
Call		Y ~ 1 + group2 + cond + group2:cond+( 1 \| sub_id )
AIC		131.782
BIC		142.365
LogLikel.		-60.116
R-squared Marginal		0.173
R-squared Conditional		0.756
Converged		yes
Optimizer		bobyqa

[5]

Model Results

Fixed Effect Omnibus tests
	F	Num df	Den df	p
group2	2.070	1	18.000	0.167
cond	11.049	1	18.000	0.004
group2 ✻ cond	0.046	1	18.000	0.833
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)	0.682	0.323	0.050	1.314	18.000	2.115	0.049
group21	old - young	0.928	0.645	-0.336	2.193	18.000	1.439	0.167
cond1	B - A	0.893	0.269	0.366	1.419	18.000	3.324	0.004
group21 ✻ cond1	old - young ✻ B - A	-0.115	0.537	-1.168	0.938	18.000	-0.214	0.833

Random Components
Groups	Name	SD	Variance	ICC
sub_id	(Intercept)	1.136	1.290	0.705
Residual		0.736	0.541
Note. Number of Obs: 40 , groups: sub_id 20

Estimated Marginal Means

group2
				95% Confidence Interval
group2	Mean	SE	df	Lower	Upper
young	0.218	0.323	18.000	-0.460	0.896
old	1.146	0.559	18.000	-0.028	2.320
Note. Estimated means are estimated averaging across interacting variables

cond
				95% Confidence Interval
cond	Mean	SE	df	Lower	Upper
A	0.236	0.349	24.057	-0.485	0.957
B	1.129	0.349	24.057	0.407	1.850
Note. Estimated means are estimated averaging across interacting variables

cond:group2
					95% Confidence Interval
cond	group2	Mean	SE	df	Lower	Upper
A	young	-0.257	0.349	24.057	-0.978	0.464
B	young	0.693	0.349	24.057	-0.028	1.414
A	old	0.729	0.605	24.057	-0.520	1.978
B	old	1.564	0.605	24.057	0.315	2.813

References

[1] The jamovi project (2021). 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] Singmann, H. (2018). afex: Analysis of Factorial Experiments. [R package]. Retrieved from https://cran.r-project.org/package=afex.

[4] Lenth, R. (2020). emmeans: Estimated Marginal Means, aka Least-Squares Means. [R package]. Retrieved from https://cran.r-project.org/package=emmeans.

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