library(dplyr)
library(magrittr)
fread("df.csv") -> df
cols <- c("pp", "blockorder", "contrast", "seqlength","lg","gender")
df %<>%
  mutate_each_(funs(factor(.)),cols)

summary(glmer(response ~ contrast + seqlength + lg + gender + blockorder + exp + (1|seq) + (1|pp), df,contrasts = list(seqlength=contr.sdif),family = binomial)) -> df.summ
summary(glmer(response ~ exp * contrast + seqlength + (1|seq) + (1|pp), df,contrasts = list(seqlength=contr.sdif),family = binomial)) -> df.summ
df.summ

df %>%
  group_by(exp,seqlength,contrast) %>%
  summarise(m=mean(response), sd=sd(response)) -> tbl

ggplot(df,aes(x = seqlength, y = response, group=interaction(exp,contrast), shape=exp,linetype=contrast)) +
  geom_pointrange(stat="summary", size=1)+
  geom_line(stat="summary") +
  theme_bw() +
  xlab("sequence length") +
  ylab("score") +
  theme(legend.position="none",axis.title = element_text(size = 20),axis.text = element_text(size=20),strip.text = element_text(size = 20))