center variables

library(faux)
library(tidyverse)

data <- sim_design(within = list(T = c("T1", "T2", "T3", "T4", "T5")),
                   id = "ID")

processed_data <- data %>%
  gather(T, raw, T1:T5) %>% # put in long format
  group_by(ID) %>% # start doing calculations within groups
  mutate(Mean_T = mean(raw),
         Variance_T = var(raw),
         Centered = raw - Mean_T) %>%
  ungroup() %>% # stop doing calculations within groups
  # reshape data to wide format
  gather(score_type, val, c(raw, Centered)) %>% # make long
  unite(var, score_type, T) %>% # new col "var" = raw/centered + T cols
  spread(var, val) # make wide
  
  
## more variables (5w*2w design)
  
data <- sim_design(within = list(T = c("T1", "T2", "T3", "T4", "T5"),
                                 condition = c("A", "B")),
                   id = "ID")

processed_data <- data %>%
  gather(var, raw, T1_A:T5_B) %>% # put in long format
  separate(var, c("time", "condition")) %>%
  group_by(ID, condition) %>% # start doing calculations within groups
  mutate(Mean_T = mean(raw),
         Variance_T = var(raw),
         Centered = raw - Mean_T) %>%
  ungroup() %>% # stop doing calculations within groups
  select(-raw) %>% # remove raw values
  spread(time, Centered) %>% # spread to 1 row per ID/condition
  gather(var, val, Mean_T:T5) %>% # gather back to long
  unite(var, var, condition) %>% # merge condition into var label
  spread(var, val) # spread back out

If you don't need the raw scores anymore, you can replace

gather(score_type, val, c(raw, Centered)) %>% # make long
unite(var, score_type, T) %>% # new col "var" = raw/centered + T cols
spread(var, val) # make wide

with

select(-raw) %>% # keep relevant columns
spread(T, Centered) # make wide

This works great! The last Q for the ww dataset is how to spread back into ww?

spread(time, Centered)

still has condition in the long format?

Thanks!