print.gformula_survival | R Documentation |
Print and summary method for objects of class "gformula_survival", "gformula_continuous_eof", or "gformula_binary_eof".
## S3 method for class 'gformula_survival'
print(
x,
all_times = FALSE,
coefficients = FALSE,
stderrs = FALSE,
rmses = FALSE,
hazardratio = FALSE,
fits = FALSE,
...
)
## S3 method for class 'gformula_continuous_eof'
print(
x,
coefficients = FALSE,
stderrs = FALSE,
rmses = FALSE,
fits = FALSE,
...
)
## S3 method for class 'gformula_binary_eof'
print(
x,
coefficients = FALSE,
stderrs = FALSE,
rmses = FALSE,
fits = FALSE,
...
)
## S3 method for class 'gformula'
summary(object, ...)
## S3 method for class 'summary.gformula'
print(
x,
all_times = TRUE,
coefficients = FALSE,
stderrs = FALSE,
rmses = FALSE,
hazardratio = FALSE,
fits = TRUE,
...
)
x |
Object of class "gformula_survival", "gformula_continuous_eof", "gformula_binary_eof", or "summary.gformula" (for |
all_times |
Logical scalar indicating whether to print the results for all time points. This argument is only applicable to objects of class "gformula_survival". If this argument is set to |
coefficients |
Logical scalar indicating whether to print the model coefficients. The default is |
stderrs |
Logical scalar indicating whether to print the standard error of the model coefficients. The default is |
rmses |
Logical scalar indicating whether to print the model root mean square errors (RMSEs). The default is |
hazardratio |
Logical scalar indicating whether to print the hazard ratio between two interventions (if computed). If bootstrapping was used, 95% confidence intervals will be given. This argument is only applicable to objects of class "gformula_survival". The default is |
fits |
Logical scalar indicating whether to print summaries of the fitted models for the time-varying covariates, outcome, and competing event (if applicable). This argument is only effective if the argument |
... |
Other arguments. |
object |
Object of class "gformula" (for |
No value is returned for the print
functions. The summary
function returns the object passed to it and adds the class "summary.gformula" to it.
gformula
## Estimating the effect of static treatment strategies on risk of a
## failure event
id <- 'id'
time_points <- 7
time_name <- 't0'
covnames <- c('L1', 'L2', 'A')
outcome_name <- 'Y'
outcome_type <- 'survival'
covtypes <- c('binary', 'bounded normal', 'binary')
histories <- c(lagged, lagavg)
histvars <- list(c('A', 'L1', 'L2'), c('L1', 'L2'))
covparams <- list(covmodels = c(L1 ~ lag1_A + lag_cumavg1_L1 + lag_cumavg1_L2 +
L3 + t0,
L2 ~ lag1_A + L1 + lag_cumavg1_L1 +
lag_cumavg1_L2 + L3 + t0,
A ~ lag1_A + L1 + L2 + lag_cumavg1_L1 +
lag_cumavg1_L2 + L3 + t0))
ymodel <- Y ~ A + L1 + L2 + L3 + lag1_A + lag1_L1 + lag1_L2 + t0
intervention1.A <- list(static, rep(0, time_points))
intervention2.A <- list(static, rep(1, time_points))
int_descript <- c('Never treat', 'Always treat')
nsimul <- 10000
gform_basic <- gformula(obs_data = basicdata_nocomp, id = id,
time_points = time_points,
time_name = time_name, covnames = covnames,
outcome_name = outcome_name,
outcome_type = outcome_type, covtypes = covtypes,
covparams = covparams, ymodel = ymodel,
intervention1.A = intervention1.A,
intervention2.A = intervention2.A,
int_descript = int_descript,
histories = histories, histvars = histvars,
basecovs = c('L3'), nsimul = nsimul,
seed = 1234)
summary(gform_basic)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.