Generation

code to explanationSun, 23 Apr 2023

> model1 <- lme(FOD_FODs ~ 0 + Condition_FODs*Age_FODs, random=~1|subject_FODs, + na.action=na.omit, + method = "ML", data=indvar_FODs,control = lmeControl(opt = "optim")) > ano <- anova(model1) > round(ano, 3) numDF denDF F-value p-value Condition_FODs 4 3139 0.347 0.846 Age_FODs 15 3139 0.084 1.000 Condition_FODs:Age_FODs 45 3139 0.046 1.000 > eta_squared(anova(model1), partial=TRUE) # Effect Size for ANOVA Parameter | Eta2 (partial) | 95% CI ------------------------------------------------------- Condition_FODs | 4.42e-04 | [0.00, 1.00] Age_FODs | 4.02e-04 | [0.00, 1.00] Condition_FODs:Age_FODs | 6.52e-04 | [0.00, 1.00] - One-sided CIs: upper bound fixed at [1.00]. > library(MuMIn) > r.squaredGLMM(model1) R2m R2c [1,] 0.001171854 0.001178491 Can you please report these results in APA style?

The output shows a main effect of condition F(4,3139)=0.347, p=0.846 and a main effect of age F(15,3139)=0.84, p=1.000, no significant interaction effect F(45,3139)=0.046, p=1.000. The partial eta squared values were 0.0004 for condition, 0.0004 for age and 0.0006 for the interaction term. The marginal and conditional R squared values were 0.0012 and 0.0011 respectively.

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