Bifactor Models
Mood
rputamenMood <- gam(rputamen ~ s(age) + sex + mood, data=r2star, method="REML")
visreg(rputamenMood,"mood")

rput_mood_pval <- as.data.frame(summary(rputamenMood)$p.table[3,4])
names(rput_mood_pval) <- "rputamen_mood_pval"
print(rput_mood_pval)
## rputamen_mood_pval
## 1 0.03504195
lputamenMood <- gam(lputamen ~ s(age) + sex + mood, data=r2star, method="REML")
visreg(lputamenMood,"mood")

lput_mood_pval <- as.data.frame(summary(lputamenMood)$p.table[3,4])
names(lput_mood_pval) <- "lputamen_mood_pval"
print(lput_mood_pval)
## lputamen_mood_pval
## 1 0.03869431
putamenMood <- gam(putamen ~ s(age) + sex + mood, data=r2star, method="REML")
visreg(putamenMood,"mood")

put_mood_pval <- as.data.frame(summary(putamenMood)$p.table[3,4])
names(put_mood_pval) <- "putamen_mood_pval"
print(put_mood_pval)
## putamen_mood_pval
## 1 0.01216773
Psychosis
rputamenpsychosis <- gam(rputamen ~ s(age) + sex + psychosis, data=r2star, method="REML")
visreg(rputamenpsychosis,"psychosis")

rput_psychosis_pval <- as.data.frame(summary(rputamenpsychosis)$p.table[3,4])
names(rput_psychosis_pval) <- "rputamen_psychosis_pval"
print(rput_psychosis_pval)
## rputamen_psychosis_pval
## 1 0.001823309
lputamenpsychosis <- gam(lputamen ~ s(age) + sex + psychosis, data=r2star, method="REML")
visreg(lputamenpsychosis,"psychosis")

lput_psychosis_pval <- as.data.frame(summary(lputamenpsychosis)$p.table[3,4])
names(lput_psychosis_pval) <- "lputamen_psychosis_pval"
print(lput_psychosis_pval)
## lputamen_psychosis_pval
## 1 0.00744302
putamenpsychosis <- gam(putamen ~ s(age) + sex + psychosis, data=r2star, method="REML")
visreg(putamenpsychosis,"psychosis")

put_psychosis_pval <- as.data.frame(summary(putamenpsychosis)$p.table[3,4])
names(put_psychosis_pval) <- "putamen_psychosis_pval"
print(put_psychosis_pval)
## putamen_psychosis_pval
## 1 0.000870209
Externalizing
rputamenexternalizing <- gam(rputamen ~ s(age) + sex + externalizing, data=r2star, method="REML")
visreg(rputamenexternalizing,"externalizing")

rput_externalizing_pval <- as.data.frame(summary(rputamenexternalizing)$p.table[3,4])
names(rput_externalizing_pval) <- "rputamen_externalizing_pval"
print(rput_externalizing_pval)
## rputamen_externalizing_pval
## 1 0.01181279
lputamenexternalizing <- gam(lputamen ~ s(age) + sex + externalizing, data=r2star, method="REML")
visreg(lputamenexternalizing,"externalizing")

lput_externalizing_pval <- as.data.frame(summary(lputamenexternalizing)$p.table[3,4])
names(lput_externalizing_pval) <- "lputamen_externalizing_pval"
print(lput_externalizing_pval)
## lputamen_externalizing_pval
## 1 0.0364483
putamenexternalizing <- gam(putamen ~ s(age) + sex + externalizing, data=r2star, method="REML")
visreg(putamenexternalizing,"externalizing")

put_externalizing_pval <- as.data.frame(summary(putamenexternalizing)$p.table[3,4])
names(put_externalizing_pval) <- "putamen_externalizing_pval"
print(put_externalizing_pval)
## putamen_externalizing_pval
## 1 0.005234008
Fear
rputamenfear <- gam(rputamen ~ s(age) + sex + fear, data=r2star, method="REML")
visreg(rputamenfear,"fear")

rput_fear_pval <- as.data.frame(summary(rputamenfear)$p.table[3,4])
names(rput_fear_pval) <- "rputamen_fear_pval"
print(rput_fear_pval)
## rputamen_fear_pval
## 1 0.001718764
lputamenfear <- gam(lputamen ~ s(age) + sex + fear, data=r2star, method="REML")
visreg(lputamenfear,"fear")

lput_fear_pval <- as.data.frame(summary(lputamenfear)$p.table[3,4])
names(lput_fear_pval) <- "lputamen_fear_pval"
print(lput_fear_pval)
## lputamen_fear_pval
## 1 0.01338387
putamenfear <- gam(putamen ~ s(age) + sex + fear, data=r2star, method="REML")
visreg(putamenfear,"fear")

put_fear_pval <- as.data.frame(summary(putamenfear)$p.table[3,4])
names(put_fear_pval) <- "putamen_fear_pval"
print(put_fear_pval)
## putamen_fear_pval
## 1 0.0009817216
P values
pvalues = list(rput_mood_pval, lput_mood_pval, put_mood_pval, rput_psychosis_pval, lput_psychosis_pval, put_psychosis_pval, rput_externalizing_pval, lput_externalizing_pval, put_externalizing_pval, rput_fear_pval, lput_fear_pval, put_fear_pval)
pvals <- Reduce(merge, lapply(pvalues, function(x) data.frame(x, rn = row.names(x))))
pvalst <- t(pvals)
# fdr corrections
fdr <- as.data.frame(p.adjust(pvals[1,], "fdr"))
names(fdr) <- "fdr"
pvals_fdr <- as.data.frame(cbind(pvalst, fdr))
pvals_fdr <- pvals_fdr[-c(1), ]
print(pvals_fdr)
## pvalst fdr
## rputamen_mood_pval 0.03504195 0.041918831
## lputamen_mood_pval 0.03869431 0.041918831
## putamen_mood_pval 0.01216773 0.019332255
## rputamen_psychosis_pval 0.001823309 0.005925754
## lputamen_psychosis_pval 0.00744302 0.016126543
## putamen_psychosis_pval 0.000870209 0.005925754
## rputamen_externalizing_pval 0.01181279 0.019332255
## lputamen_externalizing_pval 0.0364483 0.041918831
## putamen_externalizing_pval 0.005234008 0.013608422
## rputamen_fear_pval 0.001718764 0.005925754
## lputamen_fear_pval 0.01338387 0.019332255
## putamen_fear_pval 0.0009817216 0.005925754