@PBulls thank you for your reply. I changed the ggemmeans code as you suggested. However, the outcome is still not linear. The Y-scale shows percentages, not log odds. Any idea how I can solve this?

ggemmeans(LMM_acc, terms = c("time_position.c", "response_side"), back.transform = FALSE) %>% 
  plot() +
  geom_line(size = 2) +
  aes(linetype = group_col) +
  theme(legend.title = element_text(size = 30),
        legend.position = 'top',
        legend.key.size = unit('1.5', 'cm'),
        axis.title.y = element_text(size = rel(2), angle = 90),
        axis.title.x = element_text(size = rel(2)),
        axis.text.x = element_text(size = 20),
        axis.text.y = element_text(size = 20)) + 
  scale_colour_manual("response_side", values = c("purple","orangered")) +
  scale_fill_manual("response_side", values = c("purple","orangered"),
                    guide = "legend") +
  scale_linetype_manual("response_side", values = c(2,1)) +
  guides(fill = guide_legend(override.aes = 
                               list(fill = c("purple","orangered"))))