JCPP2018_alluvial_3.R

# convert back to wide for alluvial
  datW <-
  datL %>%
  # long to wide
    select(ID, w1group, time, depress, dep16) %>%
    gather(key = variable, value = value, -ID, -w1group, -time) %>%
    unite(variableT, variable, time, sep=".") %>%
    spread(variableT, value) %>%
  # alluvial prep
    filter(complete.cases(.)) %>%
    group_by(dep16.1, dep16.2, dep16.3, dep16.4) %>%
    summarise(n = n()) %>%
    ungroup() %>%
    mutate_at(vars(-n), funs(factor(., levels=c(0, 1), labels=c("not depressed", 
                                                           "depressed"))))
# alluvial diagram   
  library(alluvial)
  alluvial(datW[,1:4], freq=datW$n,
           col = ifelse(datW$dep16.4 == "depressed", "#ff0000", "#D3D3D3"),
           axis_labels = c("Year 1", "Year 2", "Year 3", "Year 4"),
           cex = 0.7)