print.gformula_survival: Print and summary methods for "gformula" objects
In CausalInference/gfoRmula: Parametric G-Formula

print.gformula_survival

R Documentation

Print and summary methods for "gformula" objects

Description

Print and summary method for objects of class "gformula_survival", "gformula_continuous_eof", or "gformula_binary_eof".

Usage

## 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,
  ...
)

Arguments

`x`	Object of class "gformula_survival", "gformula_continuous_eof", "gformula_binary_eof", or "summary.gformula" (for `print`).
`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 `FALSE`, the results are only shown for the final time point. The default is `FALSE` for `print` and `TRUE` for `summary`.
`coefficients`	Logical scalar indicating whether to print the model coefficients. The default is `FALSE`.
`stderrs`	Logical scalar indicating whether to print the standard error of the model coefficients. The default is `FALSE`.
`rmses`	Logical scalar indicating whether to print the model root mean square errors (RMSEs). The default is `FALSE`.
`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 `FALSE`.
`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 `model_fits` was set to `TRUE` in `gformula`. The default is `FALSE` for `print` and `TRUE` for `summary`.
`...`	Other arguments.
`object`	Object of class "gformula" (for `summary`).

Value

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.

Examples

## 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)

CausalInference/gfoRmula documentation built on Oct. 1, 2024, 8:36 p.m.