Why the number is not integer?

[xiasijian]

my code:

`res_os <- TableSubgroupMultiCox(

formula = Surv(LRFS, LRFS_status) ~ group,

var_subgroups = c("age","gender"),
data = df
)`

[jinseob2kim]

This is KM estimate incidence(%) at time_eventrate(default: 3 * 365)

[xiasijian]

Thanks a lot, it is a very good package for doctor. how can I get the patient number of each group when using subgroup cox regression?

[jinseob2kim]

Count is N

[xiasijian]

thanks, But it is not the number of "group=low" and "group=high"

[sl-eeper]

Hi, I recently updated this option.

lung %>%
  mutate(
    status = as.integer(status == 1),
    sex = factor(sex),
    kk = factor(as.integer(pat.karno >= 70)),
    kk1 = factor(as.integer(pat.karno >= 60))
  ) -> lung

lung.label <- mk.lev(lung)

lung.label <- lung.label %>%
  mutate(
    val_label = case_when(
      variable == "sex" & level == "1" ~ "Male",
      variable == "sex" & level == "2" ~ "Female",
      variable == "kk" & level == "0" ~ "No",
      variable == "kk" & level == "1" ~ "Yes",
      variable == "kk1" & level == "0" ~ "No",
      variable == "kk1" & level == "1" ~ "Yes",
      TRUE ~ val_label
    )
  )
TableSubgroupMultiCox(Surv(time, status) ~ sex, 
                      var_subgroups = c("kk", "kk1"), 
                      data = lung, 
                      time_eventrate = 100, 
                      line = TRUE, 
                      cluster = "inst", 
                      strata = "inst", 
                      weights = "age", 
                      event = FALSE, 
                      count_by = "sex", 
                      labeldata = lung.label)

Result will look like:

Variable	Count	Count(sex=Male)	Count(sex=Female)	Percent	Point Estimate	Lower	Upper	sex=1	sex=2	P value	P for interaction
sex	227	138	90	100	1.66	1.09	2.53	0	1.2	0.019
1
2	kk									0.562
3	No	38	22	16	193294637.42	27228158.02	1372212428.98	0	0	<0.001
4	Yes	186	114	73	1.44	0.95	2.18	0	1.5	0.084
5
6	kk1									<0.001
7	No	8	4	4				0	0
8	Yes	216	132	85	1.55	1	2.41	0	1.3	0.049

You can use the Count = 'variable' option to display counts by each variable. Additionally, by adding the Event = TRUE option, you can obtain the raw event rate values (which are not Kaplan-Meier estimates).

[xiasijian]

Thanks a lot!

…

---Original--- From: "Hyungwoo ***@***.***&gt; Date: Mon, Dec 9, 2024 12:58 PM To: ***@***.***&gt;; Cc: "Sijian ***@***.******@***.***&gt;; Subject: Re: [jinseob2kim/jstable] Why the number is not integer? (Issue #61) Hi, I recently updated this option. lung %&gt;% mutate( status = as.integer(status == 1), sex = factor(sex), kk = factor(as.integer(pat.karno &gt;= 70)), kk1 = factor(as.integer(pat.karno &gt;= 60)) ) -&gt; lung lung.label <- mk.lev(lung) lung.label <- lung.label %&gt;% mutate( val_label = case_when( variable == "sex" &amp; level == "1" ~ "Male", variable == "sex" &amp; level == "2" ~ "Female", variable == "kk" &amp; level == "0" ~ "No", variable == "kk" &amp; level == "1" ~ "Yes", variable == "kk1" &amp; level == "0" ~ "No", variable == "kk1" &amp; level == "1" ~ "Yes", TRUE ~ val_label ) ) TableSubgroupMultiCox(Surv(time, status) ~ sex, var_subgroups = c("kk", "kk1"), data = lung, time_eventrate = 100, line = TRUE, cluster = "inst", strata = "inst", weights = "age", event = FALSE, count_by = "sex", labeldata = lung.label) Result will look like: Variable Count Count(sex=Male) Count(sex=Female) Percent Point Estimate Lower Upper sex=1 sex=2 P value P for interaction sex 227 138 90 100 1.66 1.09 2.53 0 1.2 0.019 1 2 kk 0.562 3 No 38 22 16 193294637.42 27228158.02 1372212428.98 0 0 <0.001 4 Yes 186 114 73 1.44 0.95 2.18 0 1.5 0.084 5 6 kk1 <0.001 7 No 8 4 4 0 0 8 Yes 216 132 85 1.55 1 2.41 0 1.3 0.049 You can use the Count = 'variable' option to display counts by each variable. Additionally, by adding the Event = TRUE option, you can obtain the raw event rate values (which are not Kaplan-Meier estimates). — Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you authored the thread.Message ID: ***@***.***&gt;