Comments (11)
emmanuels777
commented on July 29, 2024
1
Hi Ewen. A Clean shorter solution for html bold formatting of significant p-values in kable tables.
threshold = 0.05 # Threshold for P-value formatting
r %>%
summary_factorlist(dependent, explanatory, cont = "median",
column = TRUE,
fit_id = TRUE)%>%
ff_merge(
coxphuni(r, dependent, explanatory) %>%
fit2df(estimate_suffix=" Univariate"),
last_merge = TRUE
) %>%
# Tidy-up
# Bold formatting of p-values
mutate_all(~cell_spec(.x, "html",bold = (as.numeric(stri_sub(.x, from=-6, to=-2)) < threshold )))%>%
# Table Labelling
rename(" R " = label) %>%
rename(" " = levels) -> t
Regards,
from finalfit.
testgit-healthyr
commented on July 29, 2024
Hi, thanks for this.
I find kableExtra quite difficult to get to work with Word. I'd be interested in any working code you have.
Yes the default formatting removes a column heading which mutate() has started complaining about.
This can avoided by including add_dependent_label = FALSE. If a dependent label is desired it can be added in as per below (the reason this is here is if you are doing multiple tables and lose track of the outcome measure between tables).
Remember, the finalfit columns are characters, so any conditional logic will have to be string-based. Again see below.
You can force numeric outputs, but this is really for passing to plots rather than for a final formatted tables, finalfit(..., condense = FALSE).
I'm interested in how you get on, so please post back any results.
explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor", "nodes")
dependent = 'mort_5yr'
colon_s %>%
finalfit(dependent, explanatory, add_dependent_label = FALSE) %>%
mutate(
`OR (multivariable)` = cell_spec(`OR (multivariable)`, "latex",
bold = if_else(stringr::str_detect(`OR (multivariable)`, "<0.0"), TRUE, FALSE))
) %>%
dependent_label(colon_s, dependent)
from finalfit.
commented on July 29, 2024
Hi Ewen
Thanks for your response. Really helpful.
This worked for me:
summary_factorlist(dependent, explanatory, p=1, add_dependent_label=FALSE, cont = "median", total_col = TRUE, condense=TRUE) %>% mutate(p = cell_spec(p, "html", bold = if_else(p<0.05, TRUE, FALSE))) %>% kable(format = "html", escape = F, row.names = FALSE, linesep = "")%>% kable_styling(full_width = F, font_size = 12, bootstrap_options = c("condensed")) -> table1
For Word I solved it with copy and paste.
from finalfit.
commented on July 29, 2024
I realize that if you include "metrics", the string solution is impossible.
Sot this is how I partially solved it.
%>%
finalfit(dependent, explanatory, explanatory_multi, digits = c(2,2,2), add_dependent_label = FALSE) %>%
mutate(
HR (univariable) = cell_spec(HR (univariable), "html", bold = if_else(stringr::str_detect(HR (univariable), "<0.0"), TRUE, FALSE)),
HR (multivariable) = cell_spec(HR (multivariable), "html", bold = if_else(stringr::str_detect(HR (multivariable), "<0.0"), TRUE, FALSE))
) %>%
kable(format = "html", escape = F, row.names = FALSE, linesep = "")%>%
kable_styling(full_width = F, font_size = 12, bootstrap_options = c("condensed")) -> table4
totest %>%
finalfit(dependent, explanatory, explanatory_multi, digits = c(2,2,2), add_dependent_label = FALSE, metrics = TRUE) -> table4.1
table4
kable(table4.1[[2]], row.names = FALSE, linesep = "") %>%
kable_styling(full_width = F, font_size = 12, bootstrap_options = c("condensed"))
from finalfit.
commented on July 29, 2024
This is not elegant but works:
%>%
finalfit(dependent, explanatory, explanatory_multi, digits = c(2,2,2), add_dependent_label = FALSE) %>%
mutate(
`HR (univariable)` = cell_spec(`HR (univariable)`, "html", bold = if_else(stringr::str_detect(`HR (univariable)`, "<0.0")|stringr::str_detect(`HR (univariable)`, "0.01") |
stringr::str_detect(`HR (univariable)`, "0.02")|stringr::str_detect(`HR (univariable)`, "0.02")|
stringr::str_detect(`HR (univariable)`, "0.03")|stringr::str_detect(`HR (univariable)`, "0.04")
, TRUE, FALSE)),
`HR (multivariable)` = cell_spec(`HR (multivariable)`, "html", bold = if_else(stringr::str_detect(`HR (multivariable)`, "<0.0")|stringr::str_detect(`HR (multivariable)`, "0.01") |
stringr::str_detect(`HR (multivariable)`, "0.02")|stringr::str_detect(`HR (multivariable)`, "0.02")|
stringr::str_detect(`HR (multivariable)`, "0.03")|stringr::str_detect(`HR (multivariable)`, "0.04")
, TRUE, FALSE))
) %>%
kable(format = "html", escape = F, row.names = FALSE, linesep = "")%>%
kable_styling(full_width = F, font_size = 12, bootstrap_options = c("condensed")) ->
from finalfit.
testgit-healthyr
commented on July 29, 2024
What about this?
(I should say that I don't really agree with highlighting on the basis of a p-value :) )
colon_s %>%
finalfit(dependent, explanatory, digits = c(2,2,2), add_dependent_label = FALSE) %>%
bind_cols(colon_s %>%
finalfit(dependent, explanatory, digits = c(2,2,2),
add_dependent_label = FALSE, condense = FALSE) %>%
select(p.x, p.y)
) %>%
mutate(
`HR (univariable)` = cell_spec(`HR (univariable)`, "html", bold = if_else(p.x < 0.05, TRUE, FALSE)),
`HR (multivariable)` = cell_spec(`HR (multivariable)`, "html", bold = if_else(p.y < 0.05, TRUE, FALSE)),
) %>%
select(-c(p.x, p.y)) %>%
kable(format = "html", escape = F, row.names = FALSE, linesep = "")%>%
kable_styling(full_width = F, font_size = 12, bootstrap_options = c("condensed"))
from finalfit.
commented on July 29, 2024
Nice solution, based on numeric outputs.
I agree with you in the non - highlighting of the p-value, but sometimes is very useful when you have a large number of variables.
Regards,
from finalfit.
ewenharrison
commented on July 29, 2024
I wonder if this generic approach deals with all/most circumstances?
explanatory = c("age", "nodes", "sex.factor", "obstruct.factor", "perfor.factor")
dependent = "Surv(time, status)"
dependent = "mort_5yr"
threshold = 0.05
table = colon_s %>%
finalfit(dependent, explanatory, digits = c(2,2,3), add_dependent_label = FALSE)
table %>%
select(matches("OR|HR|Coefficient"))%>%
purrr::map2_df(colon_s %>%
finalfit(dependent, explanatory, condense = FALSE) %>%
select(starts_with("p")),
~ if_else(.y < threshold, cell_spec(.x, "html", bold = TRUE), .x, .x)
) %>%
bind_cols(table %>% select(-matches("OR|HR|Coefficient")), .) %>%
kable(format = "html", escape = F, row.names = FALSE, linesep = "")%>%
kable_styling(full_width = F, font_size = 12, bootstrap_options = c("condensed"))
from finalfit.
commented on July 29, 2024
Hi
The last solution gives this error
Error in $<-.data.frame(tmp, "all", value = 1L) : replacement has 1 row, data has 0
from finalfit.
testgit-healthyr
commented on July 29, 2024
Sorry, I can't replicate that error.
from finalfit.
emmanuels777
commented on July 29, 2024
Hi Ewen.
Problem solved with your last solution.
Thanks a lot!!
from finalfit.
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