This document contains information on survival in the studies used in this coordinated analysis. Specifically, we count the number of participants who survived and who died, the surival time for those who died, and the survival time for those who lived.

Surival Time (in months)
Sample N Percent of full sample Mean SD Min Max
EAS
full 574 48.56 30.59 2.00 133.00
died 128 22.30 51.15 29.39 2.00 122.00
HRS
full 19211 64.03 28.05 1.00 109.57
died 3066 15.96 45.11 25.90 1.00 104.53
LBC1936
full 962 133.75 31.34 2.10 170.80
died 218 22.66 90.59 40.03 2.10 161.13
LBLS
full 898 170.23 42.21 12.00 228.00
died 131 14.59 113.40 41.15 12.00 204.00
MAP
full 653 115.12 35.81 15.44 166.74
died 268 41.04 95.99 31.43 15.44 160.69
MAS
full 879 71.74 23.06 0.00 101.04
died 180 20.48 52.84 24.91 3.84 95.52
MIDUS
full 6245 228.74 50.14 1.00 253.50
died 1069 17.12 135.32 64.20 1.00 245.13
NAS
full 992 228.98 83.88 21.60 322.80
died 659 66.43 186.95 72.98 21.60 313.20
OATS
full 534 48.93 28.99 0.00 114.87
died 56 10.49 63.76 28.53 4.11 114.87
ROS
full 1394 126.29 81.32 1.05 288.00
died 792 56.81 120.75 70.73 1.05 287.70
SLS
full 1649 140.72 61.37 1.67 194.23
died 444 26.93 64.47 46.14 1.67 189.90
WLS
full 10711 250.15 47.99 3.00 268.00
died 1777 16.59 160.42 65.05 3.00 264.00

Code

The following packages were used to generate this table:

library(papaja)
library(tidyverse)
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)

Next we extract the relevant statistics for each study.

survival.df = data.frame(study = study.names)

survival.df$full = lapply(X = paste0(study.names, "_survival_output"), 
                          FUN = function(x) get(x)$descriptives$survival_full)
survival.df$died = lapply(X = paste0(study.names, "_survival_output"), 
                          FUN = function(x) get(x)$descriptives$survival_died)

survival.df = survival.df %>%
  gather(key = "sample", value = "value", -study) %>%
  unnest() %>%
  group_by(study) %>%
  mutate(percent = case_when(sample == "died" ~ n/max(n)*100)) %>%
  dplyr::select(study, sample, n, percent, mean, sd, min, max) %>%
  arrange(study)  %>%
  ungroup()

We identify the rows for each variable.

rows.EAS = which(survival.df$study == "EAS"); rows.EAS = c(min(rows.EAS), max(rows.EAS))
rows.HRS = which(survival.df$study == "HRS"); rows.HRS = c(min(rows.HRS), max(rows.HRS))
rows.LBC = which(survival.df$study == "LBC"); rows.LBC = c(min(rows.LBC), max(rows.LBC))
rows.LBLS = which(survival.df$study == "LBLS"); rows.LBLS = c(min(rows.LBLS), max(rows.LBLS))
rows.MAP = which(survival.df$study == "MAP"); rows.MAP = c(min(rows.MAP), max(rows.MAP))
rows.MAS = which(survival.df$study == "MAS"); rows.MAS = c(min(rows.MAS), max(rows.MAS))
rows.MIDUS = which(survival.df$study == "MIDUS"); rows.MIDUS = c(min(rows.MIDUS), max(rows.MIDUS))
rows.NAS = which(survival.df$study == "NAS"); rows.NAS = c(min(rows.NAS), max(rows.NAS))
rows.OATS = which(survival.df$study == "OATS"); rows.OATS = c(min(rows.OATS), max(rows.OATS))
rows.ROS = which(survival.df$study == "ROS"); rows.ROS = c(min(rows.ROS), max(rows.ROS))
rows.SLS = which(survival.df$study == "SLS"); rows.SLS = c(min(rows.SLS), max(rows.SLS))
rows.WLS = which(survival.df$study == "WLS"); rows.WLS = c(min(rows.WLS), max(rows.WLS))
survival.df %>%
  dplyr::select(-study) %>%
  kable(., booktabs = TRUE, escape = F, digits = 2, format = "html", 
        col.names = c("Sample", "N", "Percent of full sample",
                      "Mean", "SD", "Min", "Max")) %>%
  kable_styling(full_width = T, latex_options = c("repeat_header")) %>%
  add_header_above(c(" "=3, "Surival Time (in months)" = 4)) %>%
  group_rows("EAS", rows.EAS[1], rows.EAS[2]) %>%
  group_rows("HRS", rows.HRS[1], rows.HRS[2]) %>%
  group_rows("LBC1936", rows.LBC[1], rows.LBC[2]) %>%
  group_rows("LBLS", rows.LBLS[1], rows.LBLS[2]) %>%
  group_rows("MAP", rows.MAP[1], rows.MAP[2]) %>%
  group_rows("MAS", rows.MAS[1], rows.MAS[2]) %>%
  group_rows("MIDUS", rows.MIDUS[1], rows.MIDUS[2]) %>%
  group_rows("NAS", rows.NAS[1], rows.NAS[2]) %>%
  group_rows("OATS", rows.OATS[1], rows.OATS[2]) %>%
  group_rows("ROS", rows.ROS[1], rows.ROS[2]) %>%
  group_rows("SLS", rows.SLS[1], rows.SLS[2]) %>%
  group_rows("WLS", rows.WLS[1], rows.WLS[2])