model1 <- lme(FOD_FODs ~ 0 + Condition_FODs*language_used_FODs_ind, random=~1|subject_FODs, na.action=na.omit, method = "ML", data=indvar_FODs,control = lmeControl(opt = "optim")) > p_value <- shapiro.test(resid(model1))$p.value > round(p_value, 3) [1] 0 > check_singularity(model1) [1] FALSE > ano <- anova(model1) > round(ano, 3) numDF denDF F-value p-value Condition_FODs 4 3262 0.402 0.807 language_used_FODs_ind 4 40 0.008 1.000 Condition_FODs:language_used_FODs_ind 12 3262 0.053 1.000 > library(predictmeans) > eta_squared(anova(model1), partial=TRUE) # Effect Size for ANOVA Parameter | Eta2 (partial) | 95% CI --------------------------------------------------------------------- Condition_FODs | 4.93e-04 | [0.00, 1.00] language_used_FODs_ind | 8.36e-04 | [0.00, 1.00] Condition_FODs:language_used_FODs_ind | 1.95e-04 | [0.00, 1.00] please report these results in APA style

{r}
# first calculate the effect size
library(predictmeans)

model1_eta <- eta_squared(anova(model1), partial = TRUE)

round(model1_eta, 3)

# now report in APA style
apa.table(model1_eta, 
          p.value = ano$p.value, 
          stars = c("ns","ns","ns"), 
          digits = c(3,3,3),
          custom.stars = TRUE, 
          custom.stars.table = c("", "*", "**", "***"),
          star.symbol = "",
          star.fontface = "plain", 
          star.cex = 1,
          border = "topbottom", 
          caption = "",
          align = "c",
          booktab = TRUE,
          space = "",
          only.means = FALSE,
          omit.empty.rows = TRUE,
          print.results = "none",
          file = NULL, 
          table.placement = NULL,