summary.CIMTx_ATE_sa: Summarize a CIMTx_ATE_sa object

In CIMTx: Causal Inference for Multiple Treatments with a Binary Outcome

Summarize a CIMTx_ATE_sa object

Description

Summarize a CIMTx_ATE_sa object

Usage

## S3 method for class 'CIMTx_ATE_sa'
summary(object, ...)

Arguments

object	a CIMTx_ATE_sa object obtained with sa function.
...	further arguments passed to or from other methods.

Value

a data frame containing the estimation, standard error, lower and upper 95% CI for the causal estimand in terms of RD.

References

Hadley Wickham (2019). stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.4.0. URL:https://CRAN.R-project.org/package=stringr

Examples

lp_w_all <-
  c(
    ".4*x1 + .1*x2  - 1.1*x4 + 1.1*x5", # w = 1
    ".2 * x1 + .2 * x2  - 1.2 * x4 - 1.3 * x5"
  ) # w = 2
nlp_w_all <-
  c(
    "-.5*x1*x4  - .1*x2*x5", # w = 1
    "-.3*x1*x4 + .2*x2*x5"
  ) # w = 2
lp_y_all <- rep(".2*x1 + .3*x2 - .1*x3 - 1.1*x4 - 1.2*x5", 3)
nlp_y_all <- rep(".7*x1*x1  - .1*x2*x3", 3)
X_all <- c(
  "rnorm(0, 0.5)", # x1
  "rbeta(2, .4)", # x2
  "runif(0, 0.5)", # x3
  "rweibull(1,2)", # x4
  "rbinom(1, .4)" # x5
)
set.seed(1111)
data <- data_sim(
  sample_size = 100,
  n_trt = 3,
  x = X_all,
  lp_y = lp_y_all,
  nlp_y = nlp_y_all,
  align = FALSE,
  lp_w = lp_w_all,
  nlp_w = nlp_w_all,
  tau = c(0.5, -0.5, 0.5),
  delta = c(0.5, 0.5),
  psi = 2
)
c_grid <- c(
  "runif(-0.6, 0)", # c(1,2)
  "runif(0, 0.6)", # c(2,1)
  "runif(-0.6, 0)", # c(2,3)
  "seq(-0.6, 0, by = 0.3)", # c(1,3)
  "seq(0, 0.6, by = 0.3)", # c(3,1)
  "runif(0, 0.6)" # c(3,2)
)
sensitivity_analysis_parallel_ATE_result <-
  sa(
    m1 = 1,
    x = data$covariates,
    y = data$y,
    w = data$w,
    prior_c_function = c_grid,
    nCores = 1,
    estimand = "ATE",
  )
summary(sensitivity_analysis_parallel_ATE_result)

CIMTx documentation built on June 24, 2022, 9:07 a.m.