Chapter 28 emtrends(model.npsexpectdemean, var = ‘EXPECT_demean’, lmer.df = “asymptotic”)

28.0.0.1 This is it

# https://stats.stackexchange.com/questions/365466/significance-of-slope-different-than-zero-in-triple-interaction-with-factors

28.0.0.2 ACCURATE: NPS ~ demean + CMC

model.npsexpectdemean <- lmer(NPSpos ~ 
                          CUE_high_gt_low*EXPECT_demean  +  EXPECT_cmc + factor(ses) +
                          (1|sub), data = demean_dropna
                    )
# CUE_high_gt_low+STIM+EXPECT_demean
sjPlot::tab_model(model.npsexpectdemean,
                  title = "Multilevel-modeling: \nlmer(NPSpos ~ CUE * STIM * EXPECT_demean + (1| sub), data = pvc)",
                  CSS = list(css.table = '+font-size: 12;'))

Multilevel-modeling: lmer(NPSpos ~ CUE * STIM * EXPECT_demean + (1| sub), data = pvc)
	NPSpos
Predictors	Estimates	CI	p
(Intercept)	6.63	5.40 – 7.86	<0.001
CUE high gt low	-0.69	-1.34 – -0.03	0.039
EXPECT demean	-0.00	-0.01 – 0.01	0.648
EXPECT cmc	0.07	0.03 – 0.12	0.002
factor(ses)ses-03	0.10	-0.61 – 0.80	0.791
factor(ses)ses-04	1.13	0.44 – 1.83	0.001
CUE high gt low * EXPECT demean	-0.02	-0.04 – 0.01	0.219
Random Effects
σ²	64.28
τ₀₀ _sub	26.96
ICC	0.30
N _sub	86
Observations	3765
Marginal R² / Conditional R²	0.038 / 0.322