Chapter 39 CCN figures
- Given that the brain results only includes 80 participants, I’m plotting the behavioral data with identical participants as well
- behavioral results
title: "CCN_figures"
author: "Heejung Jung"
date: "2023-04-06"
output: html_document39.1 behavioral outcome ratings ~ expectations * cue
Plot pain outcome rating as a function of expectation rating and cue {.unlisted .unnumbered}
39.2 behavioral demeaned (both)
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.## `geom_smooth()` using formula = 'y ~ x'
## behavioral only expectaiton deman
# maindata <- pvc %>%
# group_by(src_subject_id, session_id, param_run_num) %>%
# mutate(event04_actual_angle = as.numeric(event04_actual_angle)) %>%
# mutate(event02_expect_angle = as.numeric(event02_expect_angle)) %>%
# mutate(avg_outcome = mean(event04_actual_angle, na.rm = TRUE)) %>%
# mutate(demean_outcome = event04_actual_angle - avg_outcome) %>%
# mutate(avg_expect = mean(event02_expect_angle, na.rm = TRUE)) %>%
# mutate(demean_expect = event02_expect_angle - avg_expect)
sp <- plot_twovariable(
df = maindata,
iv1 = "demean_expect", iv2 = "event04_actual_angle",
group = "param_cue_type", subject ="src_subject_id",
xmin=-50, xmax=50, ymin=0,ymax=180,
xlab = "Expectation rating\n(subjectwise-demeaned)", ylab = "Outcome rating",
ggtitle="", color_scheme = c("high_cue" ="#941100","low_cue" = "#5D5C5C"),
alpha = .9, fit_lm = TRUE, lm_method = "lm", identity_line=FALSE, size=NULL)
# Add description ______________________________________________________________
sp +
theme(text = element_text(size = 15)) +theme(aspect.ratio=1) +
theme(axis.line = element_line(colour = "black"),
panel.background = element_blank(),
plot.subtitle = ggtext::element_textbox_simple(size= 11))## `geom_smooth()` using formula = 'y ~ x'
39.6 NPS: stim * cue
## NPS demeaned: stim*cue
# [ PLOT ] calculate mean and se _________________________
NPSmaindata <- data_screen %>%
group_by(sub) %>%
mutate(event04_actual_angle = as.numeric(event04_actual_angle)) %>%
mutate(event02_expect_angle = as.numeric(event02_expect_angle)) %>%
mutate(avg_outcome = mean(event04_actual_angle, na.rm = TRUE)) %>%
mutate(demean_outcome = event04_actual_angle - avg_outcome) %>%
mutate(avg_expect = mean(event02_expect_angle, na.rm = TRUE)) %>%
mutate(demean_expect = event02_expect_angle - avg_expect)
# ungroup() %>%
NPS.df <- NPSmaindata %>%
group_by(sub ) %>%
mutate(NPSpos = as.numeric(NPSpos)) %>%
mutate(avg_NPS = mean(NPSpos, na.rm = TRUE)) %>%
mutate(demean_NPS = NPSpos - avg_NPS)
# pvc <-simple_contrasts_beh(maindata)
LINEIV1 = "stim_ordered"
LINEIV2 = "cue_ordered"
MEAN = "mean_per_sub_norm_mean"
ERROR = "se"
dv_keyword = "actual"
dv = "demean_NPS"
subject = "sub"
model_iv1 = "stim_ordered"
model_iv2 = "cue_ordered"
taskname <- "pain"
NPSstimcue_subjectwise <- meanSummary(NPS.df,
c(subject, model_iv1, model_iv2), dv)
df_dropna <- NPSstimcue_subjectwise[!is.na(NPSstimcue_subjectwise[, "mean_per_sub"]), ]
NPSstimcue_groupwise <- summarySEwithin(
data = df_dropna,
measurevar = "mean_per_sub",
withinvars = c(model_iv1, model_iv2),
idvar = subject
)
NPSstimcue_groupwise$task <- taskname
DATA = as.data.frame(NPSstimcue_groupwise)
color = c( "#4575B4", "#D73027")
LINEIV1 = "stim_ordered"
LINEIV2 = "cue_ordered"
MEAN = "mean_per_sub_norm_mean"
ERROR = "ci"
dv_keyword = "actual"
p1 = plot_lineplot_twofactor(DATA,
LINEIV1, LINEIV2, MEAN, ERROR, color, ggtitle = 'pain', ylab = "NPSpos\n(subject/runwise mean-centered" )
p1 + theme(aspect.ratio=.9) +
theme(text = element_text(size = 15)) 
## NPS:ccue * expect (both demean)
