TableSubgroupMultiCox | R Documentation |
Multiple sub-group analysis table for Cox/svycox model.
TableSubgroupMultiCox(
formula,
var_subgroups = NULL,
var_cov = NULL,
data,
time_eventrate = 3 * 365,
decimal.hr = 2,
decimal.percent = 1,
decimal.pvalue = 3,
line = F,
cluster = NULL,
strata = NULL,
weights = NULL
)
formula |
formula with survival analysis. |
var_subgroups |
Multiple sub-group variables for analysis, Default: NULL |
var_cov |
Variables for additional adjust, Default: NULL |
data |
Data or svydesign in survey package. |
time_eventrate |
Time for kaplan-meier based event rate calculation, Default = 365 * 3 |
decimal.hr |
Decimal for hazard ratio, Default: 2 |
decimal.percent |
Decimal for percent, Default: 1 |
decimal.pvalue |
Decimal for pvalue, Default: 3 |
line |
Include new-line between sub-group variables, Default: F |
cluster |
Cluster variable for coxph, Default: NULL |
strata |
Strata variable for coxph, Default: NULL |
weights |
Weights variable for coxph, Default: NULL |
This result is used to make forestplot.
Multiple sub-group analysis table.
map
bind
library(survival)
library(dplyr)
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
TableSubgroupMultiCox(Surv(time, status) ~ sex,
var_subgroups = c("kk", "kk1"),
data = lung, time_eventrate = 100, line = TRUE
)
## survey design
library(survey)
data.design <- svydesign(id = ~1, data = lung)
TableSubgroupMultiCox(Surv(time, status) ~ sex,
var_subgroups = c("kk", "kk1"),
data = data.design, time_eventrate = 100
)
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