Good evening does someone know how to add p_values in this table for all the ages?
There is a general p_value but I would like adding a p_value to each age category.
Thank you again for your help.
library(reprex)
#> Warning: package 'reprex' was built under R version 3.6.3
library(readr)
library(tidyverse)
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library(dplyr)
library(tibble)
library(psych)
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#> Attaching package: 'psych'
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#> %+%, alpha
library(flextable)
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library(Gmisc)
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library(Hmisc)
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#> format.pval, units
library(kableExtra)
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library(knitr)
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library(prettydoc)
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library(gtsummary)
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library(eeptools)
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library(rstudioapi)
#> Warning: package 'rstudioapi' was built under R version 3.6.3
library(htmlTable)
de <- read_csv("C:/Users/juanp/Desktop/de.csv")
#> Warning: Missing column names filled in: 'X1' [1]
#> Parsed with column specification:
#> cols(
#> X1 = col_double(),
#> status = col_character(),
#> lockdown_date = col_character(),
#> Age_category = col_character(),
#> SEX = col_character()
#> )
de
#> # A tibble: 12 x 5
#> X1 status lockdown_date Age_category SEX
#> <dbl> <chr> <chr> <chr> <chr>
#> 1 1 Discharged a~ Before lockdown (February 28 to Mar~ (50 to 59 yea~ M
#> 2 2 e After lockdown(March 17 to March 26~ (50 to 59 yea~ F
#> 3 3 Discharged a~ After lockdown(March 17 to March 26~ [18 to 40 yea~ M
#> 4 4 Discharged a~ After lockdown(March 17 to March 26~ Above 80 years F
#> 5 5 dead After lockdown(March 17 to March 26~ [18 to 40 yea~ F
#> 6 6 Discharged a~ After lockdown(March 17 to March 26~ (50 to 59 yea~ F
#> 7 7 Discharged a~ After lockdown(March 17 to March 26~ [18 to 40 yea~ F
#> 8 8 Discharged a~ After lockdown(March 17 to March 26~ (50 to 59 yea~ F
#> 9 9 alive After lockdown(March 17 to March 26~ (60 to 69 yea~ M
#> 10 10 Discharged a~ After lockdown(March 17 to March 26~ Under 18 years M
#> 11 11 Discharged a~ After lockdown(March 17 to March 26~ (60 to 69 yea~ M
#> 12 12 Discharged a~ After lockdown(March 17 to March 26~ (60 to 69 yea~ F
tbl_summary(de,
by=status)%>%
add_p()%>%
add_overall()
|
Characteristic |
Overall, N = 12 |
alive, N = 11 |
dead, N = 11 |
Discharged alive, N = 91 |
e, N = 11 |
p-value2 |
|---|---|---|---|---|---|---|
|
X1 |
6.50 (3.75, 9.25) |
9.00 (9.00, 9.00) |
5.00 (5.00, 5.00) |
7.00 (4.00, 10.00) |
2.00 (2.00, 2.00) |
0.5 |
|
lockdown_date |
|
|||||
|
After lockdown(March 17 to March 26, 2020) |
11 (92%) |
1 (100%) |
1 (100%) |
8 (89%) |
1 (100%) |
|
|
Before lockdown (February 28 to March 16, 2020 |
1 (8.3%) |
0 (0%) |
0 (0%) |
1 (11%) |
0 (0%) |
|
|
Age_category |
|
|||||
|
(50 to 59 years] |
4 (33%) |
0 (0%) |
0 (0%) |
3 (33%) |
1 (100%) |
|
|
(60 to 69 years] |
3 (25%) |
1 (100%) |
0 (0%) |
2 (22%) |
0 (0%) |
|
|
[18 to 40 years) |
3 (25%) |
0 (0%) |
1 (100%) |
2 (22%) |
0 (0%) |
|
|
Above 80 years |
1 (8.3%) |
0 (0%) |
0 (0%) |
1 (11%) |
0 (0%) |
|
|
Under 18 years |
1 (8.3%) |
0 (0%) |
0 (0%) |
1 (11%) |
0 (0%) |
|
|
SEX |
|
|||||
|
F |
7 (58%) |
0 (0%) |
1 (100%) |
5 (56%) |
1 (100%) |
|
|
M |
5 (42%) |
1 (100%) |
0 (0%) |
4 (44%) |
0 (0%) |
|
|
1 Statistics presented: median (IQR); n (%) 2 Statistical tests performed: Kruskal-Wallis test; Fisher’s exact test |
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Created on 2020-05-17 by the reprex package (v0.3.0)