Print Method for Pool Objects

Displays a formatted summary of a pooled analysis object from rbmi::pool(). Uses cli formatting to show rounded estimates, confidence intervals, parameter labels, method information, number of imputations, and confidence level.

Usage

# S3 method for class 'pool'
print(x, digits = 2, ...)

Arguments

x

An object of class pool, typically obtained from rbmi::pool().

digits

Integer. Number of decimal places for rounding estimates, standard errors, and confidence interval bounds. Default is 2.

...

Additional arguments (currently unused).

Value

Invisibly returns the original pool object x (for pipe chaining).

Details

This method overrides rbmi::print.pool() to provide enhanced, formatted console output using the cli package. The override produces a "Registered S3 method overwritten" message at package load time, which is expected and harmless (same pattern as print.analysis()).

The output includes:

• A header with parameter and visit counts

• Metadata: pooling method, number of imputations, confidence level

• A compact results table with key columns: parameter, visit, est, lci, uci, pval

See also

• tidy_pool_obj() for full tidy tibble output

• summary.pool() for visit-level breakdown with significance flags

• rbmi::pool() to create pool objects

Examples

# \donttest{
library(rbmi)
library(rbmiUtils)
data("ADMI")

ADMI$TRT <- factor(ADMI$TRT, levels = c("Placebo", "Drug A"))
ADMI$USUBJID <- factor(ADMI$USUBJID)
ADMI$AVISIT <- factor(ADMI$AVISIT)

vars <- set_vars(
  subjid = "USUBJID", visit = "AVISIT", group = "TRT",
  outcome = "CHG", covariates = c("BASE", "STRATA", "REGION")
)
method <- method_bayes(n_samples = 20, control = control_bayes(warmup = 20))

ana_obj <- analyse_mi_data(ADMI, vars, method, fun = ancova)
#> Warning: Data contains 100 imputations but method expects 20. Using first 20
#> imputations.
pool_obj <- pool(ana_obj)
print(pool_obj)
#> 
#> Pool Object
#> -----------
#> Number of Results Combined: 20
#> Method: rubin
#> Confidence Level: 0.95
#> Alternative: two.sided
#> 
#> Results:
#> 
#>   ========================================================
#>       parameter      est     se     lci     uci     pval  
#>   --------------------------------------------------------
#>      trt_Week 24    -2.181  0.182  -2.539  -1.823  <0.001 
#>    lsm_ref_Week 24  0.086   0.132  -0.173  0.344   0.514  
#>    lsm_alt_Week 24  -2.096  0.126  -2.344  -1.847  <0.001 
#>      trt_Week 48    -3.794  0.256  -4.297  -3.29   <0.001 
#>    lsm_ref_Week 48  0.036   0.186  -0.33   0.403   0.846  
#>    lsm_alt_Week 48  -3.758  0.177  -4.106  -3.409  <0.001 
#>   --------------------------------------------------------
#> 
# }