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Summary function to generate result table from bayesmsm

Source: R/summary_bayesmsm.R
summary_bayesmsm.Rd

This function generates a ready to use result table that contents the estimated APO and ATE and their 95% credible intervals

Usage

summary_bayesmsm(model)

Arguments

model

A model object from bayesmsm

Value

A summary table of the results from bayesmsm.

Examples

# 1) Specify simple treatment‐assignment models
amodel <- list(
  c("(Intercept)" =  0, "L1_1" =  0.5, "L2_1" = -0.5),
  c("(Intercept)" =  0, "L1_2" =  0.5, "L2_2" = -0.5, "A_prev" = 0.3)
)
# 2) Specify a continuous‐outcome model
ymodel <- c("(Intercept)" = 0,
            "A1"         = 0.2,
            "A2"         = 0.3,
            "L1_2"       = 0.1,
            "L2_2"       = -0.1)
# 3) Simulate without right‐censoring
testdata <- simData(
  n                = 200,
  n_visits         = 2,
  covariate_counts = c(2, 2),
  amodel           = amodel,
  ymodel           = ymodel,
  y_type           = "continuous",
  right_censor     = FALSE,
  seed             = 123)
model <- bayesmsm(ymodel = Y ~ A1 + A2,
                  nvisit = 2,
                  reference = c(rep(0,2)),
                  comparator = c(rep(1,2)),
                  treatment_effect_type = "sq",
                  family = "binomial",
                  data = testdata,
                  wmean = rep(1,200),
                  nboot = 10,
                  optim_method = "BFGS",
                  seed = 890123,
                  parallel = FALSE)
summary_bayesmsm(model)
#>                     mean sd          2.5%         97.5%
#> Reference  -9.637275e+00  0 -9.637275e+00 -9.637275e+00
#> Comparator  6.736958e+00  0  6.736958e+00  6.736958e+00
#> RD          9.987499e-01  0  9.987499e-01  9.987499e-01
#> RR          1.530837e+04  0  1.530837e+04  1.530837e+04
#> OR          1.291931e+07  0  1.291931e+07  1.291931e+07