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GMR Table with Confidence Intervals (pkpt11)

Source: R/t_pkpt.R
t_pkpt11_gmr.Rd

Computes geometric mean ratios (GMR) with 90% confidence intervals for selected PK parameters, comparing each treatment arm to a reference arm.

Usage

t_pkpt11_gmr(
  data,
  ref_arm = NULL,
  ci_level = 0.9,
  list_vars = c("PPCAT"),
  strat_var = "TRT01A",
  param_var = "PARAM",
  value_var = "AVAL"
)

Arguments

data

A CDISC ADPP data frame.

ref_arm

Character string identifying the reference treatment arm in strat_var. If NULL (default), the first arm in sorted order is used.

ci_level

Confidence level for the geometric mean ratio CI. Default: 0.90.

list_vars

Character vector of columns used to split output into separate tables. Default: c("PPCAT"). AVISIT is a conditional ADPP column that is typically absent from export_cdisc()$adpp; it is silently skipped when not present so there is no need to remove it manually, but adding it only helps when your ADPP actually contains visit information.

strat_var

Single treatment-arm column that defines the comparison axis (each arm is compared against ref_arm). Default: "TRT01A". Unlike the summary tables, this must be a single column.

param_var

Column containing parameter names shown as rows. Default: "PARAM".

value_var

Column containing the numeric analysis value. Default: "AVAL".

Value

Named list of data frames, one per combination of list_vars. Each data frame has columns: strat_var, param_var, n_ref, n_trt, GMR, CI_lower, CI_upper.

Details

The confidence interval is computed on the log scale using a two-sample t-test approach: exp(log_ratio +/- t * SE) where SE is derived from the pooled within-group standard deviations on the log scale.

Examples

if (FALSE) { # \dontrun{
adpp <- export_cdisc(res_nca)$adpp
tables <- t_pkpt11_gmr(adpp, ref_arm = "Placebo")
} # }