Start #119

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: brms.mmrm
 Title: Bayesian MMRMs using 'brms'
-Version: 1.0.1.9006
+Version: 1.0.1.9007
 Authors@R: c(
   person(
     given = c("William", "Michael"),

NEWS.md

@@ -1,4 +1,4 @@
-# brms.mmrm 1.0.1.9006 (development)
+# brms.mmrm 1.0.1.9007 (development)
 
 * Add `brm_marginal_grid()`.
 * Show posterior samples of `sigma` in `brm_marginal_draws()` and `brm_marginal_summaries()`.
@@ -10,6 +10,7 @@
 * Take defaults `data` and `formula` from the above in `brm_marginal_draws()`.
 * Set the default value of `effect_size` to `attr(formula, "brm_allow_effect_size")`.
 * Remove defaults from some arguments to `brm_data()` and document examples.
+* Deprecate the `role` argument of `brm_data()` in favor of `reference_time` (#119).
 
 # brms.mmrm 1.0.1
 

R/brm_archetype_successive_cells.R

@@ -25,7 +25,7 @@
 #'
 #'   For group A, `beta_1` is the time 1 intercept, `beta_2` represents
 #'   time 2 minus time 1, and `beta_3` represents time 3 minus time 2.
-#'   `beta_4`, `beta_5`, and `beta_6` represent the analogous roles.
+#'   `beta_4`, `beta_5`, and `beta_6` behave analogously for group B.
 #' @section Nuisance variables:
 #'   In the presence of covariate adjustment, functions like
 #'   [brm_archetype_successive_cells()] convert nuisance factors into binary

R/brm_data.R

@@ -29,9 +29,6 @@
 #'   Example possibilities from clinical trial datasets include
 #'   `"CHG"` and `"AVAL"`.
 #'   The `outcome` column in the data should be a numeric vector.
-#' @param role Character of length 1. Either `"response"` if `outcome`
-#'   is the raw response variable (e.g. AVAL) or `"change"` if `outcome`
-#'   is change from baseline (e.g. CHG).
 #' @param baseline Character of length 1,
 #'   name of the baseline response variable (for example, `"BASE"`
 #'   in many clinical trial datasets).
@@ -91,17 +88,22 @@
 #'   model matrix that `brms` derives from the formula from `brm_formula()`.
 #' @param reference_time Atomic value of length 1 or `NULL`,
 #'   level of the `time` column to indicate the baseline time point.
-#'   This value must be `NULL` if the outcome
-#'   variable is already change from baseline. If the outcome
-#'   is raw response, then `reference_time` may or may not be `NULL`.
-#'   [brm_marginal_draws()] and downstream functions calculate posterior
-#'   inference on change from baseline if and only if
-#'   `reference_time` is not `NULL`.
+#'   Leave as `NULL` if there is no baseline or baseline is not included
+#'   in `data[[time]]`.
+#'
+#'   If `reference_time` is not `NULL`, then [brm_marginal_draws()] will
+#'   calculate change from baseline, and it will calculate treatment
+#'   differences as differences between change-from-baseline values.
+#'   If `reference_time` is not `NULL`, then [brm_marginal_draws()] will
+#'   not calculate change from baseline, and it will calculate treatment
+#'   differences as differences between response values.
 #'
 #'   Note: `reference_time` only applies to the post-processing that happens
 #'   in functions like [brm_marginal_draws()] downstream of the model.
 #'   It does not control the fixed effect mapping in the
 #'   model matrix that `brms` derives from the formula from `brm_formula()`.
+#' @param role Deprecated as unnecessary on 2024-07-11 (version 1.0.1.9007).
+#'   Use `reference_time` to supply a baseline time point value if it exists.
 #' @param level_baseline Deprecated on 2024-01-11 (version 0.2.0.9002).
 #'   Use `reference_time` instead.
 #' @param level_control Deprecated on 2024-01-11 (version 0.2.0.9002).
@@ -114,7 +116,6 @@
 #' brm_data(
 #'   data = data,
 #'   outcome = "col_response",
-#'   role = "response",
 #'   group = "col_group",
 #'   time = "col_time",
 #'   patient = "col_patient",
@@ -124,7 +125,6 @@
 brm_data <- function(
   data,
   outcome,
-  role = "change",
   baseline = NULL,
   group,
   subgroup = NULL,
@@ -135,10 +135,18 @@ brm_data <- function(
   reference_group,
   reference_subgroup = NULL,
   reference_time = NULL,
+  role = NULL,
   level_baseline = NULL,
   level_control = NULL
 ) {
   assert(is.data.frame(data), message = "data arg must be a data frame.")
+  if (!is.null(role)) {
+    brm_deprecate(
+      "The 'role' argument was deprecated as unnecessary on 2024-07-11 ",
+      "(version 1.0.1.9007). Use reference_time to specify a baseline ",
+      "time value if it exists."
+    )
+  }
   if (!is.null(level_control)) {
     brm_deprecate(
       "level_control was deprecated on 2024-01-11 (version 0.2.0.9002). ",
@@ -158,7 +166,6 @@ brm_data <- function(
   out <- brm_data_new(
     data = data,
     brm_outcome = as.character(outcome),
-    brm_role = as.character(role),
     brm_baseline = baseline,
     brm_group = as.character(group),
     brm_subgroup = subgroup,
@@ -177,7 +184,6 @@ brm_data <- function(
 brm_data_new <- function(
   data,
   brm_outcome = NULL,
-  brm_role = NULL,
   brm_baseline = NULL,
   brm_group = NULL,
   brm_subgroup = NULL,
@@ -193,7 +199,6 @@ brm_data_new <- function(
   structure(
     out,
     brm_outcome = brm_outcome,
-    brm_role = brm_role,
     brm_baseline = brm_baseline,
     brm_group = brm_group,
     brm_subgroup = brm_subgroup,
@@ -220,7 +225,6 @@ brm_data_validate <- function(data) {
 #' @export
 brm_data_validate.default <- function(data) {
   outcome <- attr(data, "brm_outcome")
-  role <- attr(data, "brm_role")
   baseline <- attr(data, "brm_baseline")
   group <- attr(data, "brm_group")
   subgroup <- attr(data, "brm_subgroup")
@@ -237,7 +241,6 @@ brm_data_validate.default <- function(data) {
     message = "please use brm_data() to preprocess your data"
   )
   assert_chr(outcome, "outcome of data must be a nonempty character string")
-  assert_chr(role, "role of data must be a nonempty character string")
   assert_chr(
     baseline %|||% "x",
     "baseline must NULL or a nonempty character string"
@@ -266,10 +269,6 @@ brm_data_validate.default <- function(data) {
       "in the data"
     )
   )
-  assert(
-    role %in% c("response", "change"),
-    message = "role must be either \"response\" or \"change\""
-  )
   assert_col(outcome, data)
   assert_col(baseline, data)
   assert_col(group, data)
@@ -369,12 +368,6 @@ brm_data_validate.default <- function(data) {
       )
     )
   }
-  if (role == "change") {
-    assert(
-      is.null(reference_time),
-      message = "reference_time must be NULL if role is \"change\"."
-    )
-  }
 }
 
 brm_data_fill <- function(data) {

R/brm_data_change.R

@@ -14,7 +14,8 @@
 #'   change from baseline will be missing if either the post-baseline response
 #'   is missing or the baseline response is missing.
 #' @param data A classed `tibble` (e.g. from [brm_data()]) with raw response
-#'   as the outcome variable (role = `"response"` in [brm_data()]).
+#'   as the outcome variable and no baseline time point stored in the
+#'   attributes.
 #' @param name_change Character of length 1, name of the new outcome column
 #'   for change from baseline.
 #' @param name_baseline Character of length 1, name of the new column for
@@ -24,21 +25,18 @@
 #' data <- brm_data(
 #'   data = dplyr::rename(brm_simulate_simple()$data, y_values = response),
 #'   outcome = "y_values",
-#'   role = "response",
 #'   group = "group",
 #'   time = "time",
 #'   patient = "patient",
 #'   reference_group = "group_1",
 #'   reference_time = "time_1"
 #' )
 #' data
-#' attr(data, "brm_role")
 #' attr(data, "brm_outcome")
 #' attr(data, "brm_baseline")
 #' attr(data, "brm_reference_time")
 #' changed <- brm_data_change(data = data, name_change = "delta")
 #' changed
-#' attr(changed, "brm_role")
 #' attr(changed, "brm_outcome")
 #' attr(changed, "brm_baseline")
 #' attr(data, "brm_reference_time")
@@ -55,11 +53,10 @@ brm_data_change <- function(
     )
   )
   assert(
-    attr(data, "brm_role") == "response",
+    !is.null(attr(data, "brm_reference_time")),
     message = paste(
-      "outcome variable must be raw response",
-      "(not change from baseline)",
-      "in the data supplied to brm_data_change()."
+      "In brm_data_change(), a baseline time point needs to exist.",
+      "It needs to have already been specified through brm_data()."
     )
   )
   assert_chr(name_change)
@@ -101,7 +98,6 @@ brm_data_change <- function(
   brm_data(
     data = out,
     outcome = name_change,
-    role = "change",
     baseline = name_baseline,
     group = attr(data, "brm_group"),
     subgroup = attr(data, "brm_subgroup"),

R/brm_formula.R

@@ -187,7 +187,6 @@
 #' data <- brm_data(
 #'   data = brm_simulate_simple()$data,
 #'   outcome = "response",
-#'   role = "response",
 #'   group = "group",
 #'   time = "time",
 #'   patient = "patient",
@@ -371,7 +370,6 @@ brm_formula.default <- function(
   brm_formula_validate_correlation(correlation)
   brm_formula_sigma_validate(sigma)
   name_outcome <- attr(data, "brm_outcome")
-  name_role <- attr(data, "brm_role")
   name_baseline <- attr(data, "brm_baseline")
   name_group <- attr(data, "brm_group")
   name_subgroup <- attr(data, "brm_subgroup")

R/brm_formula_sigma.R

@@ -76,7 +76,6 @@
 #' data <- brm_data(
 #'   data = brm_simulate_simple()$data,
 #'   outcome = "response",
-#'   role = "response",
 #'   group = "group",
 #'   time = "time",
 #'   patient = "patient",
@@ -150,7 +149,6 @@ brm_formula_sigma <- function(
     baseline_time ||
     covariates
   allow_effect_size <- !exclude_effect_size
-  name_role <- attr(data, "brm_role")
   name_baseline <- attr(data, "brm_baseline")
   name_group <- attr(data, "brm_group")
   name_subgroup <- attr(data, "brm_subgroup")

R/brm_marginal_data.R

@@ -34,7 +34,6 @@
 #' data <- brm_data(
 #'   data = brm_simulate_simple()$data,
 #'   outcome = "response",
-#'   role = "response",
 #'   group = "group",
 #'   time = "time",
 #'   patient = "patient",

R/brm_marginal_draws.R

@@ -2,6 +2,16 @@
 #' @export
 #' @family marginals
 #' @description Get marginal posterior draws from a fitted MMRM.
+#' @section Baseline:
+#'   The returned values from [brm_marginal_draws()]
+#'   depend on whether a baseline time point
+#'   was declared through the `reference_time` argument of [brm_data()].
+#'   If `reference_time` was not `NULL`, then [brm_marginal_draws()] will
+#'   calculate change from baseline, and it will calculate treatment
+#'   differences as differences between change-from-baseline values.
+#'   If `reference_time` was not `NULL`, then [brm_marginal_draws()] will
+#'   not calculate change from baseline, and it will calculate treatment
+#'   differences as differences between response values.
 #' @inheritSection brm_data Separation string
 #' @return A named list of tibbles of MCMC draws of the marginal posterior
 #'   distribution of each treatment group and time point. These marginals
@@ -19,15 +29,21 @@
 #'     not `NULL` (i.e. if a baseline value for the time variable
 #'     was identified).
 #'   * `difference_group`: treatment effect:
-#'     the `difference_time` at each active group minus the `difference_time`
-#'     at the control group (`reference_group`).
-#'     If `reference_time` was `NULL` in [brm_data()] (i.e. no baseline
-#'     time point), then treatment group
-#'     is instead the difference between `response` at each active group minus
-#'     the `response` at the control group.
+#'     These samples depend on the values of `reference_group` and
+#'     `reference_time` which were originally declared in [brm_data()].
+#'     `reference_group` is the control group, and `reference_time`
+#'     is baseline. If baseline was originally given (via `reference_time`
+#'     in [brm_data()]),
+#'     then `difference_time` is the change-from-baseline value of
+#'     each active group minus that of the control group.
+#'     Otherwise, if baseline is omitted (i.e. `reference_time = NULL`
+#'     (default) in [brm_data()]), then `difference_time` is the
+#'     raw response at each active group minus that of the control group.
 #'   * `difference_subgroup`: subgroup differences: the `difference_group`
 #'     at each subgroup level minus the `difference_group` at the subgroup
-#'     reference level (`reference_subgroup`).
+#'     reference level (`reference_subgroup`). Only reported if a subgroup
+#'     analysis was specified through the appropriate arguments to
+#'     [brm_data()] and [brm_formula()].
 #'   * `effect`: effect size, defined as the treatment difference
 #'     divided by the residual standard deviation. Omitted if
 #'     the `effect_size` argument is `FALSE` or if the
@@ -71,7 +87,6 @@
 #' data <- brm_data(
 #'   data = brm_simulate_simple()$data,
 #'   outcome = "response",
-#'   role = "response",
 #'   group = "group",
 #'   time = "time",
 #'   patient = "patient",
@@ -143,7 +158,6 @@ brm_marginal_draws <- function(
   brm_data_validate(data)
   brm_formula_validate(formula)
   brm_model_validate(model)
-  role <- attr(data, "brm_role")
   base <- attr(data, "brm_base")
   group <- attr(data, "brm_group")
   subgroup <- attr(data, "brm_subgroup")
@@ -161,7 +175,7 @@ brm_marginal_draws <- function(
   reference_subgroup <- attr(data, "brm_reference_subgroup")
   reference_time <- attr(data, "brm_reference_time")
   has_subgroup <- brm_has_subgroup(data = data, formula = formula)
-  has_baseline <- identical(role, "response") && !is.null(reference_time)
+  has_baseline <- !is.null(reference_time)
   if (effect_size && !attr(formula, "brm_allow_effect_size")) {
     effect_size <- FALSE
     brm_warn(
@@ -197,7 +211,7 @@ brm_marginal_draws <- function(
   draws_response <- tibble::as_tibble(as.matrix(draws_beta) %*% t(transform))
   draws_response <- dplyr::bind_cols(draws_response, index_mcmc)
   draws_response <- posterior::as_draws_df(draws_response)
-  if (has_baseline) { # baseline
+  if (has_baseline) { # baseline exists, subgroup exists
     if (has_subgroup) {
       draws_difference_time <- subtract_reference_time_subroup(
         draws = draws_response,
@@ -220,7 +234,7 @@ brm_marginal_draws <- function(
         levels_time = setdiff(levels_time, reference_time),
         reference_subgroup = reference_subgroup
       )
-    } else { # role is "response", no subgroup
+    } else { # baseline exists, no subgroup
       draws_difference_time <- subtract_reference_time(
         draws = draws_response,
         levels_group = levels_group,
@@ -234,7 +248,7 @@ brm_marginal_draws <- function(
         reference_group = reference_group
       )
     }
-  } else { # baseline does not exist
+  } else { # baseline does not exist, subgroup exists
     if (has_subgroup) {
       draws_difference_group <- subtract_reference_group_subgroup(
         draws = draws_response,
@@ -250,7 +264,7 @@ brm_marginal_draws <- function(
         levels_time = levels_time,
         reference_subgroup = reference_subgroup
       )
-    } else { # role is "change", no subgroup
+    } else { # baseline does not exist, no subgroup
       draws_difference_group <- subtract_reference_group(
         draws = draws_response,
         levels_group = levels_group,