Exclude participants

LexTALE

Statistic analysis

Accuracy

# Model accuracy 

df %>% mutate_if(is.character, as.factor) %>% 
  mutate(age = scale(age), age = as.double(age),
         frequency = scale(frequency), frequency = as.double(frequency), 
         AoO = scale(AoO), AoO = as.double(AoO)) -> df 
glmer(accuracy ~ 
        # group * condition * frequency + 
        # group * condition + 
        group + 
        condition + 
        frequency + 
        age + 
        AoO * group + 
        (1 + condition|ID) + (1|word), 
      data = df, 
      family = "binomial",
      control = glmerControl(optimizer = "bobyqa")) -> m1

# test model 
# drop1(m1, test = "Chisq")
# Anova(m1, type = "III")

Model accuracy

	Chisq	Df	Pr(>Chisq)
(Intercept)	17.06	1	0.000
group	13.53	1	0.000
condition	9.27	1	0.002
frequency	8.06	1	0.005
age	11.11	1	0.001
AoO	8.75	1	0.003
group:AoO	4.10	1	0.043

group	AoO.trend	SE	df	asymp.LCL	asymp.UCL	z.ratio	p.value
DYS	-0.28	0.10	Inf	-0.47	-0.10	-2.96	0.003
TD	-0.06	0.05	Inf	-0.16	0.04	-1.25	0.212

RT

df %>% 
  # only correct answers 
  filter(accuracy == 1) %>% 
  mutate(rt = log(reaction_time)) %>% 

# model 
lmer(formula = 
        rt ~ 
        # frequency * group +
        frequency + 
        group + 
        condition + 
        # condition * group + 
        age +
        # AoO * group + 
        AoO + 
        (1 + condition|ID) + (1|word)) -> m2

# test
# drop1(m2, test = "Chisq")
# Anova(m2, type = "III")

Model RT

	Chisq	Df	Pr(>Chisq)
(Intercept)	12504.26	1	0.000
frequency	15.67	1	0.000
group	25.08	1	0.000
condition	2.32	1	0.128
age	0.01	1	0.918
AoO	2.73	1	0.099

LexTALE total score

• Variable tot.lextale comparable to LexITA: tot.yes.words - 2* tot.yes.nonwords

Group	Accuracy (M)	sd	range
DYS	8.79	6.18	-2
DYS	8.79	6.18	29
TD	13.33	6.32	0
TD	13.33	6.32	34

### Model accuracy 

df1 %>% 
  mutate_if(is.character, as.factor) %>% 
  mutate(tot.lextale = if_else(tot.lextale < 0, 0, tot.lextale)) %>% 
  glm(formula = tot.lextale ~ group + age + AoO, family = poisson(link = "log")) -> m3

	tot lextale
Predictors	Incidence Rate Ratios	CI	p
(Intercept)	8.46	7.43 – 9.58	<0.001
group [TD]	1.59	1.37 – 1.85	<0.001
age	1.17	1.09 – 1.24	<0.001
AoO	0.91	0.86 – 0.97	0.002
Observations	80
R2 Nagelkerke	0.571