#===================================== MODEL 1 ================================ tblgen <- function ( data ) { x <-
data %>%
select ( y_usa , renin_std ) %>%
glm (
y_usa ~ renin_std ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = renin_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select ( y_usa , R1_Renin_cat ) %>%
glm (
y_usa ~ R1_Renin_cat ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Renin_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_1_1 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select ( y_usa , aldosterone_std , ) %>%
glm (
y_usa ~ aldosterone_std ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = aldosterone_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select ( y_usa , R1_Aldosterone_cat ) %>%
glm (
y_usa ~ R1_Aldosterone_cat ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Aldosterone_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_2_1 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select ( y_usa , arr_std ) %>%
glm (
y_usa ~ arr_std ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select ( y_usa , arr_cat ) %>%
glm (
y_usa ~ arr_cat ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_3_1 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) #================================= MODEL 2 ===================================== x <- data %>%
select ( y_usa , renin_std , R1_Age , R1_Sex ) %>%
glm (
y_usa ~ renin_std + R1_Age + R1_Sex ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = renin_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select ( y_usa , R1_Renin_cat , R1_Age , R1_Sex ) %>%
glm (
y_usa ~ R1_Renin_cat + R1_Age + R1_Sex ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Renin_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_1_2 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select ( y_usa , aldosterone_std , R1_Age , R1_Sex ) %>%
glm (
y_usa ~ aldosterone_std + R1_Age + R1_Sex ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = aldosterone_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select ( y_usa , R1_Aldosterone_cat , R1_Age , R1_Sex ) %>%
glm (
y_usa ~ R1_Aldosterone_cat + R1_Age + R1_Sex ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Aldosterone_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_2_2 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select ( y_usa , arr_std , R1_Age , R1_Sex ) %>%
glm (
y_usa ~ arr_std + R1_Age + R1_Sex ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select ( y_usa , arr_cat , R1_Age , R1_Sex ) %>%
glm (
y_usa ~ arr_cat + R1_Age + R1_Sex ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_3_2 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) #=============================== MODEL 3 ====================================== x <- data %>%
select (
y_usa , renin_std ,
R1_Age , R1_Sex ,
educ , R1_Smoking ) %>%
glm (
y_usa ~ renin_std + R1_Age + R1_Sex + educ + R1_Smoking ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = renin_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select (
y_usa , R1_Renin_cat ,
R1_Age , R1_Sex ,
educ , R1_Smoking ) %>%
glm (
y_usa ~ R1_Renin_cat + R1_Age + R1_Sex + educ + R1_Smoking ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Renin_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_1_3 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select (
y_usa , aldosterone_std ,
R1_Age , R1_Sex ,
educ , R1_Smoking ) %>%
glm (
y_usa ~ aldosterone_std + R1_Age + R1_Sex + educ + R1_Smoking ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = aldosterone_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select (
y_usa , R1_Aldosterone_cat ,
R1_Age , R1_Sex ,
educ , R1_Smoking ) %>%
glm (
y_usa ~ R1_Aldosterone_cat + R1_Age + R1_Sex + educ + R1_Smoking ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Aldosterone_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_2_3 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select (
y_usa , arr_std ,
R1_Age , R1_Sex ,
educ , R1_Smoking ) %>%
glm (
y_usa ~ arr_std + R1_Age + R1_Sex + educ + R1_Smoking ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select (
y_usa , arr_cat ,
R1_Age , R1_Sex ,
educ , R1_Smoking ) %>%
glm (
y_usa ~ arr_cat + R1_Age + R1_Sex + educ + R1_Smoking ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_3_3 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) #=============================== MODEL 4 ====================================== x <- data %>%
select (
y_usa , renin_std ,
R1_Age , R1_Sex ,
educ , R1_Smoking ,
R1_BMI , R1_WHR , R1_Chol , R1_BPsys_mean , salt_eat , dura ,
R1_CKDEPI_eGFR_adj ) %>%
glm (
y_usa ~ renin_std + R1_Age + R1_Sex + educ +
R1_Smoking + R1_BMI + R1_WHR + R1_Chol +
R1_BPsys_mean + salt_eat + dura + R1_CKDEPI_eGFR_adj ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = renin_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select (
y_usa , R1_Renin_cat ,
R1_Age , R1_Sex ,
educ , R1_Smoking ,
R1_BMI , R1_WHR , R1_Chol , R1_BPsys_mean , salt_eat , dura ,
R1_CKDEPI_eGFR_adj ) %>%
glm (
y_usa ~ R1_Renin_cat + R1_Age + R1_Sex + educ +
R1_Smoking + R1_BMI + R1_WHR + R1_Chol +
R1_BPsys_mean + salt_eat + dura + R1_CKDEPI_eGFR_adj ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Renin_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_1_4 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select (
y_usa , aldosterone_std ,
R1_Age , R1_Sex ,
educ , R1_Smoking ,
R1_BMI , R1_WHR , R1_Chol , R1_BPsys_mean , salt_eat , dura ,
R1_CKDEPI_eGFR_adj ) %>%
glm (
y_usa ~ aldosterone_std + R1_Age + R1_Sex + educ +
R1_Smoking + R1_BMI + R1_WHR + R1_Chol +
R1_BPsys_mean + salt_eat + dura + R1_CKDEPI_eGFR_adj ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = aldosterone_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select (
y_usa , R1_Aldosterone_cat ,
R1_Age , R1_Sex ,
educ , R1_Smoking ,
R1_BMI , R1_WHR , R1_Chol , R1_BPsys_mean , salt_eat , dura ,
R1_CKDEPI_eGFR_adj ) %>%
glm (
y_usa ~ R1_Aldosterone_cat + R1_Age + R1_Sex + educ +
R1_Smoking + R1_BMI + R1_WHR + R1_Chol +
R1_BPsys_mean + salt_eat + dura + R1_CKDEPI_eGFR_adj ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = R1_Aldosterone_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_2_4 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) x <- data %>%
select (
y_usa , arr_std ,
R1_Age , R1_Sex ,
educ , R1_Smoking ,
R1_BMI , R1_WHR , R1_Chol , R1_BPsys_mean , salt_eat , dura ,
R1_CKDEPI_eGFR_adj ) %>%
glm (
y_usa ~ arr_std + R1_Age + R1_Sex + educ +
R1_Smoking + R1_BMI + R1_WHR + R1_Chol +
R1_BPsys_mean + salt_eat + dura + R1_CKDEPI_eGFR_adj ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_std ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
y <- data %>%
select (
y_usa , arr_cat ,
R1_Age , R1_Sex ,
educ , R1_Smoking ,
R1_BMI , R1_WHR , R1_Chol , R1_BPsys_mean , salt_eat , dura ,
R1_CKDEPI_eGFR_adj ) %>%
glm (
y_usa ~ arr_cat + R1_Age + R1_Sex + educ +
R1_Smoking + R1_BMI + R1_WHR + R1_Chol +
R1_BPsys_mean + salt_eat + dura + R1_CKDEPI_eGFR_adj ,
family = poisson ( link = "log" ) ,
data = .
) %>%
gtsummary :: tbl_regression (
exponentiate= TRUE ,
include = arr_cat ,
pvalue_fun = function ( x ) gtsummary :: style_pvalue ( x , digits = 3 )
)
tbl_3_4 <- gtsummary :: tbl_stack ( tbls = list ( x ,y ) ) #======================== MERGE TABLE PARTS ================================== abc = c ( "Model 1" , "Model 2" , "Model 3" , "Model 4" ) tbl_1 <- gtsummary :: tbl_merge (
tbls = list ( tbl_1_1 , tbl_1_2 , tbl_1_3 , tbl_1_4 ) ,
tab_spanner = abc )
tbl_2 <- gtsummary :: tbl_merge (
tbls = list ( tbl_2_1 , tbl_2_2 , tbl_2_3 , tbl_2_4 ) ,
tab_spanner = abc )
tbl_3 <- gtsummary :: tbl_merge (
tbls = list ( tbl_3_1 , tbl_3_2 , tbl_3_3 , tbl_3_4 ) ,
tab_spanner = abc )
gtsummary :: tbl_stack ( tbls = list ( tbl_1 , tbl_2 , tbl_3 ) ,
group_header = c ( "Renin" , "Aldosterone" , "Aldosterone-Renin Ratio" ) )
}