tally_study: Calculate group-level summaries based solely on raw data...
In wfforrest/maeve: Modeling Accessories Enabling Visualization of Experiments

Description Usage Arguments Value Author(s) References Examples

Calculate group-level summaries based solely on raw data (i.e., that do not require any modeling).

tally_study(
  study_data_frame,
  group_name = maeve_options("group_name"),
  subject_ID = maeve_options("subject_ID"),
  x_name = maeve_options("x_name"),
  endpoint_name = maeve_options("endpoint_name"),
  reference = levels(study_data_frame[, group_name])[1],
  response = c("none", "PR", "EOS_CR", "PR_or_EOS_CR")[1],
  EOS_CR_minval = maeve_options("EOS_CR_minval"),
  PR_threshold = maeve_options("PR_threshold"),
  additive_offset = 0.5,
  na.rm = TRUE
)

`study_data_frame`	a well-prepared data.frame with the study data and appropriate columns.
`group_name`	character name of treatment regimen factor
`subject_ID`	character identifier for individual within a group.
`x_name`	character name of independent variable (usually time or concentration).
`endpoint_name`	character name of dependent variable (e.g., tumor volume, body weight).
`reference`	character name of designated reference group. Must be a level from the factor named by group_name.
`response`	character name of by-group count summary.
`EOS_CR_minval`	numeric passed to internal function to decide what constitutes a "complete response" for the the End-Of-Study Complete Response (EOS_CR) value on the original, untransformed response scale.
`PR_threshold`	numeric passed to internal function to decide what constitutes a "partial response" for the PR value. Fractional reduction is computed by-ID, from an ID-specific baseline value on the original, untransformed scale.
`additive_offset`	numeric value to add to each count in a 2 x 2 table before computing log odds ratio. Default gives the Haldane-Ascombe-Gart correction of adding 0.5 to every count.
`na.rm`	logical whether to remove NA values when computing summaries.