Code

The following packages were used to generate this table:

library(papaja)
library(tidyverse)
library(metafor)
library(knitr)
library(kableExtra)
library(here)

The files needed for this table are available at osf.io/mzfu9 in the Individual Study Output folder.

First we load the individual study analysis objects.

study.names = c("EAS", "HRS", "LBC", "LBLS", "MAP", "MAS", "MIDUS", "NAS", "OATS", "ROS", "SLS", "WLS")
lapply(here(paste0("mortality/study output/", study.names, "_survival_output.Rdata")), load, .GlobalEnv)

meta.data.time <- data.frame()
n <- 0

for(i in study.names){
  n <- n+1
  x <- get(paste0(i, "_survival_output"))
  meta.data.time[n, "study"] <- i
  meta.data.time[n, "coef"] <- x$time$model2$coef["z.neur:z.con", "coef"]
  meta.data.time[n, "se"] <- x$time$model2$coef["z.neur:z.con", "se(coef)"]
  meta.data.time[n, "n"] <- x$time$model2$ntotal
  meta.data.time[n, "n_died"] <- x$descriptives$died.tab["1"]
  meta.data.time[n, "personality_q"] <- x$metadata$personality_q
}

# set personality questionnare information.
# We divide questionnaires into five categories:
# NEO-PI-R (baseline), NEO-FFI, BFI, IPIP and MIDI.
# The Normative Aging Study (NAS) was the only to use the Goldberg adjectives; this study was excluded from personality moderations
# similarly, the EAS was the only one to use the IPIP, and was similarly excluded

neo_pi_r = c("LBLS", "SLS", "OATS", "MAS")
neo_ffi = c("ILSE", "ROS", "MAP", "LBC")
ipip = c("EAS")

meta.data.time$personality_q[meta.data.time$study %in% neo_pi_r] = "NEO-PI-R"
meta.data.time$personality_q[meta.data.time$study %in% neo_ffi] = "NEO-FFI"
meta.data.time$personality_q[meta.data.time$study %in% ipip] = "IPIP"
meta.data.time$personality_q = gsub("goldberg", "", meta.data.time$personality_q)
meta.data.time$personality_q = gsub("IPIP", "", meta.data.time$personality_q)

meta.data.time$personality_q = factor(meta.data.time$personality_q)
meta.data.time$personality_q = relevel(meta.data.time$personality_q,
                                        ref = "NEO-PI-R")

meta.data.time$study = gsub("LBC", "LBC1936", meta.data.time$study)

mod.results.time <- rma(yi = coef, 
                    sei = se, 
                    ni = n,  
                    measure = "RR",
                    slab = study, 
                    mods = ~personality_q,
                    data = meta.data.time)

coef(summary(mod.results.time)) %>%
  mutate(pval = printp(pval),
         var = c("Intercept (NEO-PI-R)", "IPIP or Goldberg", "BFI", "MIDI", "NEO-FFI")) %>%
  dplyr::select(ncol(.), 1:(ncol(.)-1)) %>%
  kable(., booktabs = TRUE, escape = FALSE, digits = 2,
        col.names = c(" ", "Estimate", "SE", "Z", "p", "CI lower", "CI upper"), 
        row.names = F) %>%
  kable_styling()