Libraries

library(haven);
library(sas7bdat);
library(plyr);
library(dplyr);
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:plyr':
## 
##     arrange, count, desc, failwith, id, mutate, rename, summarise,
##     summarize
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(tidyr);
library(haven);
library(survival);
library(car);
## Loading required package: carData
## 
## Attaching package: 'car'
## The following object is masked from 'package:dplyr':
## 
##     recode
library(muhaz);
library(survminer);
## Loading required package: ggplot2
## Loading required package: ggpubr
## 
## Attaching package: 'ggpubr'
## The following object is masked from 'package:plyr':
## 
##     mutate
library(ggplot2)

Loading PM2.5 data

PM2010 = read.csv("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/pm25TX2010.csv");
PM2011 = read.csv("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/pm25TX2011.csv");
PM2012 = read.csv("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/pm25TX2012.csv");
PM2013 = read.csv("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/pm25TX2013.csv");
PM2014 = read.csv("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/pm25TX2014.csv");
PM2015 = read.csv("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/pm25TX2015.csv");

Loading Mortality Data

Mor2010 <- read_sas("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/death2010.sas7bdat");
Mor2011 <- read_sas("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/death2011.sas7bdat");
Mor2012 <- read_sas("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/death2012.sas7bdat");
Mor2013 <- read_sas("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/death2013.sas7bdat");
Mor2014 <- read_sas("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/death2014.sas7bdat");
Mor2015 <- read_sas("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/death2015.sas7bdat");

Merging PM2.5 and mortality data into one of each and removing the initial data

PM25ALL <- rbind(PM2010,PM2011,PM2012,PM2013,PM2014,PM2015);
MorALL <- rbind(Mor2010,Mor2011,Mor2012,Mor2013,Mor2014,Mor2015);
rm(PM2010,PM2011,PM2012,PM2013,PM2014,PM2015,Mor2010,Mor2011,Mor2012,Mor2013,Mor2014,Mor2015)

Loading a county / county number list in order to merge the data

County = read.csv("C:/Users/tobik/OneDrive/Documents/Air Pollution Research/data/TXCounties.csv")

Adding to County to Fips codes in mortality data in order to merge the data sets (the county name may be redundant now, but that was a good way to check if it worked correctly)

MorALL$RESIDCOUNTY_CODE <- as.numeric(MorALL$RESIDCOUNTY_CODE);
County$ï..Number <- as.numeric(County$ï..Number);
MorALL <- merge(MorALL, County, by.x = "RESIDCOUNTY_CODE", by.y = "ï..Number", all.x = TRUE, all.y = FALSE)

Recoding dates (strptime did not work on all dates, so, I had to take it apart as string and recombine it so I can merge the data)

PM25ALL$NewDateM <- substr(PM25ALL$Date, start = 1, stop = 2);
PM25ALL$NewDateD <- substr(PM25ALL$Date, start = 4, stop = 5);
PM25ALL$NewDateY <- substr(PM25ALL$Date, start = 7, stop = 10);
PM25ALL$Date <- paste(PM25ALL$NewDateY,PM25ALL$NewDateM,PM25ALL$NewDateD, sep = "")

Creating averages per county for fine dust emissions per day

PM25ALL <- PM25ALL %>%
    dplyr::group_by(Date, COUNTY_CODE) %>% 
    dplyr::mutate(
                  PM25Aver = mean(Daily.Mean.PM2.5.Concentration)) %>% 
  dplyr::ungroup()

Merging mortality data with PM2.5 averages

PM25Sub <- PM25ALL[,c(1,17,18,24)]
FromDustToDust <- merge(x = MorALL, y = PM25Sub, by.x = c("DATEOFDEATH","Fips"), by.y = c("Date","COUNTY_CODE"), all.x = TRUE)

Removing some lines due to missing data

FromDustToDust <- subset(FromDustToDust, complete.cases (PM25Aver,AGE))
FromDustToDust <- subset(FromDustToDust, AGE < 999)

Creating Dummy Variable for premature death (below 65 = 1; 65Plus = 0)

FromDustToDust$AGE <- as.numeric(FromDustToDust$AGE)

FromDustToDust$PrematureDeath <- as.numeric(FromDustToDust$AGE<65)
FromDustToDust$One <- 1 #dummy variable for survfit

This is for testing purposes if database reduction is needed #{r} FDTD<- FromDustToDust %>% select(AGE,SEX,PM25Aver,PrematureDeath) # Variables:

Event Variable: Death before the age of 65 (condition: 1 for premature death; 0 for reaching age 65)

Duration of time variable: Since this is a dichotomous outcome of either the event not occurring or occurring only once, there are no time variables.

Cumulative Hazard: The cumulative hazard is the hazard since there is only one time it is measured.

Analysis:

Kaplan-Meier survival analysis of the outcome

fit1 <- survfit(formula =  Surv(AGE,One) ~ SEX, data  = FromDustToDust);

fit1<-glm(PrematureDeath~PM25Aver, data = FromDustToDust, na.action = na.omit, family = binomial)

summary(fit1)
## Call: survfit(formula = Surv(AGE, One) ~ SEX, data = FromDustToDust)
## 
##                 SEX=1 
##  time  n.risk n.event survival  std.err lower 95% CI upper 95% CI
##     1 1432422    7454 9.95e-01 6.01e-05     9.95e-01     9.95e-01
##     2 1424968    5121 9.91e-01 7.79e-05     9.91e-01     9.91e-01
##     3 1419847    3361 9.89e-01 8.76e-05     9.89e-01     9.89e-01
##     4 1416486    2480 9.87e-01 9.41e-05     9.87e-01     9.87e-01
##     5 1414006    2010 9.86e-01 9.91e-05     9.86e-01     9.86e-01
##     6 1411996    1534 9.85e-01 1.03e-04     9.84e-01     9.85e-01
##     7 1410462    1211 9.84e-01 1.05e-04     9.84e-01     9.84e-01
##     8 1409251    1210 9.83e-01 1.08e-04     9.83e-01     9.83e-01
##     9 1408041    1093 9.82e-01 1.10e-04     9.82e-01     9.82e-01
##    10 1406948    1175 9.81e-01 1.13e-04     9.81e-01     9.82e-01
##    11 1405773    1090 9.81e-01 1.15e-04     9.80e-01     9.81e-01
##    12 1404683     829 9.80e-01 1.17e-04     9.80e-01     9.80e-01
##    13 1403854     834 9.79e-01 1.18e-04     9.79e-01     9.80e-01
##    14 1403020    1006 9.79e-01 1.20e-04     9.79e-01     9.79e-01
##    15 1402014    1372 9.78e-01 1.23e-04     9.78e-01     9.78e-01
##    16 1400642    1875 9.77e-01 1.27e-04     9.76e-01     9.77e-01
##    17 1398767    2410 9.75e-01 1.31e-04     9.75e-01     9.75e-01
##    18 1396357    3309 9.73e-01 1.37e-04     9.72e-01     9.73e-01
##    19 1393048    3836 9.70e-01 1.43e-04     9.70e-01     9.70e-01
##    20 1389212    4390 9.67e-01 1.50e-04     9.66e-01     9.67e-01
##    21 1384822    4562 9.64e-01 1.57e-04     9.63e-01     9.64e-01
##    22 1380260    5169 9.60e-01 1.64e-04     9.60e-01     9.60e-01
##    23 1375091    4686 9.57e-01 1.70e-04     9.56e-01     9.57e-01
##    24 1370405    5022 9.53e-01 1.76e-04     9.53e-01     9.54e-01
##    25 1365383    4859 9.50e-01 1.82e-04     9.49e-01     9.50e-01
##    26 1360524    4849 9.46e-01 1.88e-04     9.46e-01     9.47e-01
##    27 1355675    5000 9.43e-01 1.94e-04     9.43e-01     9.43e-01
##    28 1350675    4718 9.40e-01 1.99e-04     9.39e-01     9.40e-01
##    29 1345957    5122 9.36e-01 2.04e-04     9.36e-01     9.36e-01
##    30 1340835    5010 9.33e-01 2.10e-04     9.32e-01     9.33e-01
##    31 1335825    5110 9.29e-01 2.15e-04     9.29e-01     9.29e-01
##    32 1330715    5235 9.25e-01 2.20e-04     9.25e-01     9.26e-01
##    33 1325480    5377 9.22e-01 2.25e-04     9.21e-01     9.22e-01
##    34 1320103    5452 9.18e-01 2.30e-04     9.17e-01     9.18e-01
##    35 1314651    4952 9.14e-01 2.34e-04     9.14e-01     9.15e-01
##    36 1309699    5434 9.11e-01 2.38e-04     9.10e-01     9.11e-01
##    37 1304265    5415 9.07e-01 2.43e-04     9.06e-01     9.07e-01
##    38 1298850    5867 9.03e-01 2.48e-04     9.02e-01     9.03e-01
##    39 1292983    6433 8.98e-01 2.53e-04     8.98e-01     8.99e-01
##    40 1286550    6495 8.94e-01 2.58e-04     8.93e-01     8.94e-01
##    41 1280055    7215 8.89e-01 2.63e-04     8.88e-01     8.89e-01
##    42 1272840    7872 8.83e-01 2.68e-04     8.83e-01     8.84e-01
##    43 1264968    8411 8.77e-01 2.74e-04     8.77e-01     8.78e-01
##    44 1256557    8909 8.71e-01 2.80e-04     8.70e-01     8.72e-01
##    45 1247648    9228 8.65e-01 2.86e-04     8.64e-01     8.65e-01
##    46 1238420   10604 8.57e-01 2.92e-04     8.57e-01     8.58e-01
##    47 1227816   11630 8.49e-01 2.99e-04     8.48e-01     8.50e-01
##    48 1216186   12840 8.40e-01 3.06e-04     8.39e-01     8.41e-01
##    49 1203346   13801 8.30e-01 3.14e-04     8.30e-01     8.31e-01
##    50 1189545   15383 8.20e-01 3.21e-04     8.19e-01     8.20e-01
##    51 1174162   17385 8.08e-01 3.29e-04     8.07e-01     8.08e-01
##    52 1156777   18313 7.95e-01 3.37e-04     7.94e-01     7.95e-01
##    53 1138464   19966 7.81e-01 3.46e-04     7.80e-01     7.82e-01
##    54 1118498   20648 7.66e-01 3.54e-04     7.66e-01     7.67e-01
##    55 1097850   22067 7.51e-01 3.61e-04     7.50e-01     7.52e-01
##    56 1075783   23756 7.34e-01 3.69e-04     7.34e-01     7.35e-01
##    57 1052027   25015 7.17e-01 3.76e-04     7.16e-01     7.18e-01
##    58 1027012   24931 7.00e-01 3.83e-04     6.99e-01     7.00e-01
##    59 1002081   26072 6.81e-01 3.89e-04     6.81e-01     6.82e-01
##    60  976009   25770 6.63e-01 3.95e-04     6.63e-01     6.64e-01
##    61  950239   27261 6.44e-01 4.00e-04     6.44e-01     6.45e-01
##    62  922978   28226 6.25e-01 4.05e-04     6.24e-01     6.25e-01
##    63  894752   28393 6.05e-01 4.08e-04     6.04e-01     6.06e-01
##    64  866359   27883 5.85e-01 4.12e-04     5.85e-01     5.86e-01
##    65  838476   28306 5.66e-01 4.14e-04     5.65e-01     5.66e-01
##    66  810170   28155 5.46e-01 4.16e-04     5.45e-01     5.47e-01
##    67  782015   27980 5.26e-01 4.17e-04     5.26e-01     5.27e-01
##    68  754035   27858 5.07e-01 4.18e-04     5.06e-01     5.08e-01
##    69  726177   26505 4.88e-01 4.18e-04     4.88e-01     4.89e-01
##    70  699672   27795 4.69e-01 4.17e-04     4.68e-01     4.70e-01
##    71  671877   27875 4.50e-01 4.16e-04     4.49e-01     4.50e-01
##    72  644002   27724 4.30e-01 4.14e-04     4.29e-01     4.31e-01
##    73  616278   27596 4.11e-01 4.11e-04     4.10e-01     4.12e-01
##    74  588682   27417 3.92e-01 4.08e-04     3.91e-01     3.93e-01
##    75  561265   27507 3.73e-01 4.04e-04     3.72e-01     3.73e-01
##    76  533758   28909 3.52e-01 3.99e-04     3.52e-01     3.53e-01
##    77  504849   28963 3.32e-01 3.94e-04     3.31e-01     3.33e-01
##    78  475886   29693 3.11e-01 3.87e-04     3.11e-01     3.12e-01
##    79  446193   30544 2.90e-01 3.79e-04     2.89e-01     2.91e-01
##    80  415649   30862 2.69e-01 3.70e-04     2.68e-01     2.69e-01
##    81  384787   32131 2.46e-01 3.60e-04     2.45e-01     2.47e-01
##    82  352656   32022 2.24e-01 3.48e-04     2.23e-01     2.25e-01
##    83  320634   32176 2.01e-01 3.35e-04     2.01e-01     2.02e-01
##    84  288458   31578 1.79e-01 3.21e-04     1.79e-01     1.80e-01
##    85  256880   31277 1.57e-01 3.04e-04     1.57e-01     1.58e-01
##    86  225603   30240 1.36e-01 2.87e-04     1.36e-01     1.37e-01
##    87  195363   29145 1.16e-01 2.68e-04     1.16e-01     1.17e-01
##    88  166218   27801 9.66e-02 2.47e-04     9.61e-02     9.71e-02
##    89  138417   25775 7.86e-02 2.25e-04     7.82e-02     7.91e-02
##    90  112642   22970 6.26e-02 2.02e-04     6.22e-02     6.30e-02
##    91   89672   20306 4.84e-02 1.79e-04     4.81e-02     4.88e-02
##    92   69366   16889 3.66e-02 1.57e-04     3.63e-02     3.69e-02
##    93   52477   14139 2.68e-02 1.35e-04     2.65e-02     2.70e-02
##    94   38338   10683 1.93e-02 1.15e-04     1.91e-02     1.95e-02
##    95   27655    8248 1.35e-02 9.66e-05     1.34e-02     1.37e-02
##    96   19407    6214 9.21e-03 7.98e-05     9.06e-03     9.37e-03
##    97   13193    4525 6.05e-03 6.48e-05     5.93e-03     6.18e-03
##    98    8668    2759 4.13e-03 5.36e-05     4.02e-03     4.23e-03
##    99    5909    2216 2.58e-03 4.24e-05     2.50e-03     2.66e-03
##   100    3693    1506 1.53e-03 3.26e-05     1.46e-03     1.59e-03
##   101    2187     855 9.30e-04 2.55e-05     8.81e-04     9.81e-04
##   102    1332     620 4.97e-04 1.86e-05     4.62e-04     5.35e-04
##   103     712     318 2.75e-04 1.39e-05     2.49e-04     3.04e-04
##   104     394     154 1.68e-04 1.08e-05     1.48e-04     1.90e-04
##   105     240     109 9.15e-05 7.99e-06     7.71e-05     1.09e-04
##   106     131      48 5.79e-05 6.36e-06     4.67e-05     7.19e-05
##   107      83      37 3.21e-05 4.73e-06     2.41e-05     4.29e-05
##   108      46      12 2.37e-05 4.07e-06     1.70e-05     3.32e-05
##   109      34       4 2.09e-05 3.82e-06     1.46e-05     3.00e-05
##   110      30       6 1.68e-05 3.42e-06     1.12e-05     2.50e-05
##   111      24      12 8.38e-06 2.42e-06     4.76e-06     1.48e-05
##   112      12       9 2.09e-06 1.21e-06     6.75e-07     6.49e-06
##   116       3       3 0.00e+00      NaN           NA           NA
## 
##                 SEX=2 
##  time  n.risk n.event survival  std.err lower 95% CI upper 95% CI
##     1 1346449    5819 9.96e-01 5.65e-05     9.96e-01     9.96e-01
##     2 1340630    4052 9.93e-01 7.35e-05     9.93e-01     9.93e-01
##     3 1336578    2858 9.91e-01 8.34e-05     9.90e-01     9.91e-01
##     4 1333720    1870 9.89e-01 8.92e-05     9.89e-01     9.89e-01
##     5 1331850    1714 9.88e-01 9.43e-05     9.88e-01     9.88e-01
##     6 1330136    1374 9.87e-01 9.81e-05     9.87e-01     9.87e-01
##     7 1328762     874 9.86e-01 1.00e-04     9.86e-01     9.86e-01
##     8 1327888     913 9.86e-01 1.03e-04     9.85e-01     9.86e-01
##     9 1326975     821 9.85e-01 1.05e-04     9.85e-01     9.85e-01
##    10 1326154     827 9.84e-01 1.07e-04     9.84e-01     9.85e-01
##    11 1325327     701 9.84e-01 1.09e-04     9.84e-01     9.84e-01
##    12 1324626     646 9.83e-01 1.10e-04     9.83e-01     9.84e-01
##    13 1323980     743 9.83e-01 1.12e-04     9.83e-01     9.83e-01
##    14 1323237     648 9.82e-01 1.14e-04     9.82e-01     9.83e-01
##    15 1322589     860 9.82e-01 1.16e-04     9.81e-01     9.82e-01
##    16 1321729     905 9.81e-01 1.18e-04     9.81e-01     9.81e-01
##    17 1320824    1018 9.80e-01 1.20e-04     9.80e-01     9.80e-01
##    18 1319806    1241 9.79e-01 1.23e-04     9.79e-01     9.80e-01
##    19 1318565    1344 9.78e-01 1.26e-04     9.78e-01     9.79e-01
##    20 1317221    1595 9.77e-01 1.29e-04     9.77e-01     9.77e-01
##    21 1315626    1644 9.76e-01 1.32e-04     9.76e-01     9.76e-01
##    22 1313982    1709 9.75e-01 1.36e-04     9.74e-01     9.75e-01
##    23 1312273    1872 9.73e-01 1.39e-04     9.73e-01     9.74e-01
##    24 1310401    1912 9.72e-01 1.43e-04     9.72e-01     9.72e-01
##    25 1308489    1863 9.70e-01 1.46e-04     9.70e-01     9.71e-01
##    26 1306626    2019 9.69e-01 1.50e-04     9.69e-01     9.69e-01
##    27 1304607    2179 9.67e-01 1.53e-04     9.67e-01     9.68e-01
##    28 1302428    1987 9.66e-01 1.57e-04     9.66e-01     9.66e-01
##    29 1300441    2067 9.64e-01 1.60e-04     9.64e-01     9.65e-01
##    30 1298374    2280 9.63e-01 1.64e-04     9.62e-01     9.63e-01
##    31 1296094    2591 9.61e-01 1.68e-04     9.60e-01     9.61e-01
##    32 1293503    2720 9.59e-01 1.72e-04     9.58e-01     9.59e-01
##    33 1290783    2833 9.57e-01 1.76e-04     9.56e-01     9.57e-01
##    34 1287950    2866 9.54e-01 1.80e-04     9.54e-01     9.55e-01
##    35 1285084    3014 9.52e-01 1.84e-04     9.52e-01     9.53e-01
##    36 1282070    2955 9.50e-01 1.88e-04     9.50e-01     9.50e-01
##    37 1279115    3374 9.47e-01 1.92e-04     9.47e-01     9.48e-01
##    38 1275741    3544 9.45e-01 1.97e-04     9.44e-01     9.45e-01
##    39 1272197    4038 9.42e-01 2.02e-04     9.41e-01     9.42e-01
##    40 1268159    3920 9.39e-01 2.06e-04     9.39e-01     9.39e-01
##    41 1264239    4401 9.36e-01 2.11e-04     9.35e-01     9.36e-01
##    42 1259838    4846 9.32e-01 2.17e-04     9.32e-01     9.33e-01
##    43 1254992    5448 9.28e-01 2.23e-04     9.28e-01     9.28e-01
##    44 1249544    5423 9.24e-01 2.28e-04     9.24e-01     9.24e-01
##    45 1244121    5963 9.20e-01 2.34e-04     9.19e-01     9.20e-01
##    46 1238158    6568 9.15e-01 2.41e-04     9.14e-01     9.15e-01
##    47 1231590    7768 9.09e-01 2.48e-04     9.08e-01     9.09e-01
##    48 1223822    8200 9.03e-01 2.55e-04     9.02e-01     9.03e-01
##    49 1215622    9292 8.96e-01 2.63e-04     8.95e-01     8.96e-01
##    50 1206330   10333 8.88e-01 2.72e-04     8.88e-01     8.89e-01
##    51 1195997   11362 8.80e-01 2.80e-04     8.79e-01     8.80e-01
##    52 1184635   11343 8.71e-01 2.88e-04     8.71e-01     8.72e-01
##    53 1173292   12069 8.62e-01 2.97e-04     8.62e-01     8.63e-01
##    54 1161223   13132 8.53e-01 3.05e-04     8.52e-01     8.53e-01
##    55 1148091   13639 8.43e-01 3.14e-04     8.42e-01     8.43e-01
##    56 1134452   14837 8.32e-01 3.23e-04     8.31e-01     8.32e-01
##    57 1119615   15302 8.20e-01 3.31e-04     8.20e-01     8.21e-01
##    58 1104313   15936 8.08e-01 3.39e-04     8.08e-01     8.09e-01
##    59 1088377   16470 7.96e-01 3.47e-04     7.95e-01     7.97e-01
##    60 1071907   15916 7.84e-01 3.54e-04     7.84e-01     7.85e-01
##    61 1055991   16849 7.72e-01 3.62e-04     7.71e-01     7.72e-01
##    62 1039142   17995 7.58e-01 3.69e-04     7.58e-01     7.59e-01
##    63 1021147   19756 7.44e-01 3.76e-04     7.43e-01     7.44e-01
##    64 1001391   19772 7.29e-01 3.83e-04     7.28e-01     7.30e-01
##    65  981619   19870 7.14e-01 3.89e-04     7.14e-01     7.15e-01
##    66  961749   20162 6.99e-01 3.95e-04     6.99e-01     7.00e-01
##    67  941587   20857 6.84e-01 4.01e-04     6.83e-01     6.85e-01
##    68  920730   20556 6.69e-01 4.06e-04     6.68e-01     6.69e-01
##    69  900174   20800 6.53e-01 4.10e-04     6.52e-01     6.54e-01
##    70  879374   21666 6.37e-01 4.14e-04     6.36e-01     6.38e-01
##    71  857708   22069 6.21e-01 4.18e-04     6.20e-01     6.21e-01
##    72  835639   22477 6.04e-01 4.21e-04     6.03e-01     6.05e-01
##    73  813162   22636 5.87e-01 4.24e-04     5.86e-01     5.88e-01
##    74  790526   23672 5.70e-01 4.27e-04     5.69e-01     5.70e-01
##    75  766854   25141 5.51e-01 4.29e-04     5.50e-01     5.52e-01
##    76  741713   26591 5.31e-01 4.30e-04     5.30e-01     5.32e-01
##    77  715122   26539 5.11e-01 4.31e-04     5.11e-01     5.12e-01
##    78  688583   29211 4.90e-01 4.31e-04     4.89e-01     4.91e-01
##    79  659372   31410 4.66e-01 4.30e-04     4.66e-01     4.67e-01
##    80  627962   32278 4.42e-01 4.28e-04     4.42e-01     4.43e-01
##    81  595684   34345 4.17e-01 4.25e-04     4.16e-01     4.18e-01
##    82  561339   37065 3.89e-01 4.20e-04     3.89e-01     3.90e-01
##    83  524274   36849 3.62e-01 4.14e-04     3.61e-01     3.63e-01
##    84  487425   39370 3.33e-01 4.06e-04     3.32e-01     3.34e-01
##    85  448055   41651 3.02e-01 3.96e-04     3.01e-01     3.03e-01
##    86  406404   42279 2.70e-01 3.83e-04     2.70e-01     2.71e-01
##    87  364125   42673 2.39e-01 3.67e-04     2.38e-01     2.39e-01
##    88  321452   42489 2.07e-01 3.49e-04     2.07e-01     2.08e-01
##    89  278963   40867 1.77e-01 3.29e-04     1.76e-01     1.77e-01
##    90  238096   39437 1.48e-01 3.06e-04     1.47e-01     1.48e-01
##    91  198659   35857 1.21e-01 2.81e-04     1.20e-01     1.21e-01
##    92  162802   31796 9.73e-02 2.55e-04     9.68e-02     9.78e-02
##    93  131006   27803 7.66e-02 2.29e-04     7.62e-02     7.71e-02
##    94  103203   22806 5.97e-02 2.04e-04     5.93e-02     6.01e-02
##    95   80397   19373 4.53e-02 1.79e-04     4.50e-02     4.57e-02
##    96   61024   16214 3.33e-02 1.55e-04     3.30e-02     3.36e-02
##    97   44810   12747 2.38e-02 1.31e-04     2.36e-02     2.41e-02
##    98   32063    9475 1.68e-02 1.11e-04     1.66e-02     1.70e-02
##    99   22588    6859 1.17e-02 9.26e-05     1.15e-02     1.19e-02
##   100   15729    5525 7.58e-03 7.47e-05     7.43e-03     7.73e-03
##   101   10204    3628 4.88e-03 6.01e-05     4.77e-03     5.00e-03
##   102    6576    2294 3.18e-03 4.85e-05     3.09e-03     3.28e-03
##   103    4282    1676 1.94e-03 3.79e-05     1.86e-03     2.01e-03
##   104    2606    1044 1.16e-03 2.93e-05     1.10e-03     1.22e-03
##   105    1562     721 6.25e-04 2.15e-05     5.84e-04     6.68e-04
##   106     841     333 3.77e-04 1.67e-05     3.46e-04     4.12e-04
##   107     508     250 1.92e-04 1.19e-05     1.70e-04     2.16e-04
##   108     258     142 8.62e-05 8.00e-06     7.18e-05     1.03e-04
##   109     116      72 3.27e-05 4.93e-06     2.43e-05     4.39e-05
##   110      44      25 1.41e-05 3.24e-06     9.00e-06     2.21e-05
##   111      19       3 1.19e-05 2.97e-06     7.28e-06     1.94e-05
##   112      16       6 7.43e-06 2.35e-06     4.00e-06     1.38e-05
##   113      10       9 7.43e-07 7.43e-07     1.05e-07     5.27e-06
##   114       1       1 0.00e+00      NaN           NA           NA

Plotting:

ggsurvplot(fit1)

The Grouping Variable is Sex (1 = male, 2 = female)

My hypothesis is that females have a higher survival probability than males.

The hypothesis seemed to be supported.