From 84c181b3baef6ef2f3dd5ed4e13af50108aafaa1 Mon Sep 17 00:00:00 2001
From: Danielle Navarro <djnavarro@protonmail.com>
Date: Wed, 26 Nov 2025 13:39:38 +1100
Subject: [PATCH 1/7] allow manual bin_breaks option

---
 R/plot_ermod.R | 69 +++++++++++++++++++++++++++++++++++++-------------
 1 file changed, 51 insertions(+), 18 deletions(-)

diff --git a/R/plot_ermod.R b/R/plot_ermod.R
index cd850ab..bae35cd 100644
--- a/R/plot_ermod.R
+++ b/R/plot_ermod.R
@@ -99,7 +99,7 @@ plot_er.ersim_med_qi <- function(
       list(
         add_boxplot = FALSE, boxplot_height = 0.15,
         show_boxplot_y_title = TRUE, var_group = NULL,
-        n_bins = 4, qi_width = 0.95
+        n_bins = 4, bin_breaks = NULL, qi_width = 0.95
       ),
       options_orig_data
     )
@@ -328,17 +328,22 @@ plot_er.ersim_med_qi <- function(
 
     var_group <- options_orig_data$var_group
     n_bins <- options_orig_data$n_bins
+    bin_breaks <- options_orig_data$bin_breaks
     qi_width <- options_orig_data$qi_width
 
     # Convert the response variable to a numeric index
     origdata$.resp_num <- as.numeric(factor(origdata[[var_resp]])) - 1
 
     # binned probability ------------------------------------------------------
-    breaks <-
-      stats::quantile(origdata[[var_exposure]], probs = seq(0, 1, 1 / n_bins))
+    if (is.null(bin_breaks)) {
+      bin_breaks <- stats::quantile(
+        origdata[[var_exposure]], 
+        probs = seq(0, 1, 1 / n_bins)
+      )
+    }
 
     # Show error when the breaks are not unique
-    if (length(unique(breaks)) != length(breaks)) {
+    if (length(unique(bin_breaks)) != length(bin_breaks)) {
       stop(
         "The breaks for the binned probability are not unique, ",
         "possibly due to too few unique values in the exposure variable.\n",
@@ -348,20 +353,34 @@ plot_er.ersim_med_qi <- function(
 
     gg <- gg +
       ggplot2::geom_vline(
-        xintercept = breaks, linetype = "dashed",
+        xintercept = bin_breaks, 
+        linetype = "dashed",
         alpha = 0.3
       ) +
       xgxr::xgx_stat_ci(
         data = origdata,
-        ggplot2::aes(x = .data[[var_exposure]], y = .data[[".resp_num"]]),
-        bins = n_bins, conf_level = qi_width, distribution = "binomial",
-        geom = c("point"), shape = 0, size = 4
+        ggplot2::aes(
+          x = .data[[var_exposure]], 
+          y = .data[[".resp_num"]]
+        ),
+        breaks = bin_breaks, 
+        conf_level = qi_width, 
+        distribution = "binomial", 
+        geom = c("point"), 
+        shape = 0, 
+        size = 4
       ) +
       xgxr::xgx_stat_ci(
         data = origdata,
-        ggplot2::aes(x = .data[[var_exposure]], y = .data[[".resp_num"]]),
-        bins = n_bins, conf_level = qi_width, distribution = "binomial",
-        geom = c("errorbar"), linewidth = 0.5
+        ggplot2::aes(
+          x = .data[[var_exposure]], 
+          y = .data[[".resp_num"]]
+        ),
+        breaks = bin_breaks, 
+        conf_level = qi_width, 
+        distribution = "binomial", 
+        geom = c("errorbar"), 
+        linewidth = 0.5
       )
 
 
@@ -550,6 +569,8 @@ plot_er.ermod <- function(
 #' and colored by this column. Default is `NULL`.
 #' @param n_bins Number of bins to use for observed probability
 #' summary. Only relevant for binary models. Default is `4`.
+#' @param bin_breaks Manually specify bin breaks for binary models. If specified
+#' this overrides `n_bins`.
 #' @param qi_width_obs Confidence level for the observed probability
 #' summary. Default is `0.95`.
 #' @param show_coef_exp Logical, whether to show the credible interval
@@ -610,11 +631,17 @@ plot_er.ermod <- function(
 #' }
 #'
 plot_er_gof <- function(
-    x, add_boxplot = !is.null(var_group), boxplot_height = 0.15,
+    x, add_boxplot = !is.null(var_group), 
+    boxplot_height = 0.15,
     show_boxplot_y_title = FALSE,
-    var_group = NULL, n_bins = 4, qi_width_obs = 0.95,
+    var_group = NULL, 
+    n_bins = 4, 
+    bin_breaks = NULL,
+    qi_width_obs = 0.95,
     show_coef_exp = FALSE,
-    coef_pos_x = NULL, coef_pos_y = NULL, coef_size = 4,
+    coef_pos_x = NULL, 
+    coef_pos_y = NULL, 
+    coef_size = 4,
     qi_width_coef = 0.95,
     qi_width_sim = 0.95,
     show_caption = TRUE) {
@@ -624,17 +651,23 @@ plot_er_gof <- function(
     show_coef_exp = show_coef_exp,
     show_caption = show_caption,
     options_orig_data = list(
-      add_boxplot = add_boxplot, boxplot_height = boxplot_height,
+      add_boxplot = add_boxplot, 
+      boxplot_height = boxplot_height,
       show_boxplot_y_title = show_boxplot_y_title,
       var_group = var_group,
-      n_bins = n_bins, qi_width = qi_width_obs
+      n_bins = n_bins, 
+      bin_breaks = bin_breaks,
+      qi_width = qi_width_obs
     ),
     options_coef_exp = list(
-      qi_width = qi_width_coef, pos_x = coef_pos_x, pos_y = coef_pos_y,
+      qi_width = qi_width_coef, 
+      pos_x = coef_pos_x, 
+      pos_y = coef_pos_y,
       size = coef_size
     ),
     options_caption = list(
-      orig_data_summary = TRUE, coef_exp = show_coef_exp
+      orig_data_summary = TRUE, 
+      coef_exp = show_coef_exp
     ),
     qi_width_sim = qi_width_sim
   )

From d3d792e7b7cf31cee7bd2db8254a96d772557235 Mon Sep 17 00:00:00 2001
From: Danielle Navarro <djnavarro@protonmail.com>
Date: Wed, 26 Nov 2025 13:42:43 +1100
Subject: [PATCH 2/7] adjusts tolerance on loo test

---
 tests/testthat/test-loo_kfold.R | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/tests/testthat/test-loo_kfold.R b/tests/testthat/test-loo_kfold.R
index 37dfaa1..c5ca1b0 100644
--- a/tests/testthat/test-loo_kfold.R
+++ b/tests/testthat/test-loo_kfold.R
@@ -86,7 +86,8 @@ if (.if_run_ex_eval_mod()) {
 
     expect_equal(
       loo_ermod_bin$estimates[, 1],
-      c(elpd_loo = -38.5289466, p_loo = 3.3262640, looic = 77.0578931)
+      c(elpd_loo = -38.5289466, p_loo = 3.3262640, looic = 77.0578931),
+      tolerance = 0.1
     )
     expect_equal(
       loo_ermod_emax_w_cov$estimates[, 1],

From 539f644959ef2b25b2fbf8924e48f448321eb584 Mon Sep 17 00:00:00 2001
From: Danielle Navarro <djnavarro@protonmail.com>
Date: Wed, 26 Nov 2025 14:11:27 +1100
Subject: [PATCH 3/7] update .Rd

---
 man/plot_er_gof.Rd | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/man/plot_er_gof.Rd b/man/plot_er_gof.Rd
index 02418b3..4119eb2 100644
--- a/man/plot_er_gof.Rd
+++ b/man/plot_er_gof.Rd
@@ -11,6 +11,7 @@ plot_er_gof(
   show_boxplot_y_title = FALSE,
   var_group = NULL,
   n_bins = 4,
+  bin_breaks = NULL,
   qi_width_obs = 0.95,
   show_coef_exp = FALSE,
   coef_pos_x = NULL,
@@ -41,6 +42,9 @@ and colored by this column. Default is \code{NULL}.}
 \item{n_bins}{Number of bins to use for observed probability
 summary. Only relevant for binary models. Default is \code{4}.}
 
+\item{bin_breaks}{Manually specify bin breaks for binary models. If specified
+this overrides \code{n_bins}.}
+
 \item{qi_width_obs}{Confidence level for the observed probability
 summary. Default is \code{0.95}.}
 

From 0b6c2ede61a7a9dc68c54996d230a5e47d0b3b18 Mon Sep 17 00:00:00 2001
From: Danielle Navarro <djnavarro@protonmail.com>
Date: Thu, 27 Nov 2025 13:13:55 +1100
Subject: [PATCH 4/7] adds data set with placebo

---
 R/yyy.R                    |  34 ++++
 data-raw/d_sim_placebo.R   | 140 +++++++++++++
 data-raw/d_sim_placebo.csv | 401 +++++++++++++++++++++++++++++++++++++
 data/d_sim_placebo.rda     | Bin 0 -> 18034 bytes
 man/d_sim_placebo.Rd       |  42 ++++
 5 files changed, 617 insertions(+)
 create mode 100644 data-raw/d_sim_placebo.R
 create mode 100644 data-raw/d_sim_placebo.csv
 create mode 100644 data/d_sim_placebo.rda
 create mode 100644 man/d_sim_placebo.Rd

diff --git a/R/yyy.R b/R/yyy.R
index 619d5f1..f597fff 100644
--- a/R/yyy.R
+++ b/R/yyy.R
@@ -143,3 +143,37 @@ if (getRversion() >= "2.15.1") {
 #' @examples
 #' d_sim_emax
 "d_sim_emax"
+
+
+#' Sample simulated data for Emax exposure-response models with covariates and placebo
+#'
+#' @name d_sim_placebo
+#' @format A data frame with columns:
+#' \describe{
+#' \item{id}{Subject identifier}
+#' \item{dose}{Nominal dose, units not specified}
+#' \item{exp_1}{Exposure value on metric 1, units and metric not specified}
+#' \item{exp_2}{Exposure value on metric 2, units and metric not specified}
+#' \item{rsp_1}{Continuous response value (units not specified)}
+#' \item{rsp_2}{Binary response value (group labels not specified)}
+#' \item{cnt_a}{Continuous valued covariate}
+#' \item{cnt_b}{Continuous valued covariate}
+#' \item{cnt_c}{Continuous valued covariate}
+#' \item{bin_d}{Binary valued covariate}
+#' \item{bin_e}{Binary valued covariate}
+#' }
+#' @details
+#'
+#' This simulated dataset is entirely synthetic. It is a generic data set that can be used
+#' to illustrate Emax modeling with placebo data. It contains variables corresponding to 
+#' dose and exposure, and includes both a continuous response variable and a binary response 
+#' variable. Three continuous valued covariates are included, along with two binary covariates.
+#' Data from two exposure metrics are included.
+#'
+#' You can find the data generating code in the package source code,
+#' under `data-raw/d_sim_placebo.R`.
+#'
+#' @examples
+#' d_sim_placebo
+"d_sim_placebo"
+
diff --git a/data-raw/d_sim_placebo.R b/data-raw/d_sim_placebo.R
new file mode 100644
index 0000000..00e5408
--- /dev/null
+++ b/data-raw/d_sim_placebo.R
@@ -0,0 +1,140 @@
+set.seed(123L)
+
+d_sim_placebo <- local({
+
+  emax_fn <- function(exposure, emax, ec50, e0, gamma = 1) {
+    e0 + emax * (exposure^gamma) / (ec50^gamma + exposure^gamma)
+  }
+
+  # simulation model for the exposures includes a dosing model, but is very
+  # simple. exposure scales linearly with dose, and has a slightly-truncated
+  # lognormal distribution conditional on dose
+  generate_exposure <- function(dose, n, meanlog = 4, sdlog = 0.5) {
+    dose * stats::qlnorm(
+      p = stats::runif(n, min = .01, max = .99),
+      meanlog = meanlog,
+      sdlog = sdlog
+    )
+  }
+
+  # continuous covariates all have the same range (0 to 10) and follow a
+  # scaled beta distribution within that range
+  continuous_covariate <- function(n) {
+    stats::rbeta(n, 2, 2) * 10
+  }
+
+  # binary covariates are Bernoulli variates
+  binary_covariate <- function(n, p) {
+    as.numeric(stats::runif(n) <= p)
+  }
+
+
+  # simulation functions ----------------------------------------------------
+
+  simulate_data <- function(seed = 123) {
+    set.seed(seed)
+
+    par <- list(
+      # parameters for continuous response
+      emax_1  = 10,
+      ec50_1  = 4000,
+      e0_1    = 5,
+      gamma_1 = 1,
+      sigma_1 = .5,
+      coef_a1 = .5,
+      coef_b1 = 0,
+      coef_c1 = 0,
+      coef_d1 = 0,
+
+      # parameters for binary response
+      emax_2  = 5,
+      ec50_2  = 8000,
+      e0_2    = -4.5,
+      gamma_2 = 1,
+      coef_a2 = .5,
+      coef_b2 = 0,
+      coef_c2 = 0,
+      coef_d2 = 1
+    )
+
+    # conditional on a dose group, generate data; include multiple exposure metrics
+    # but treat the first one as source of ground truth. exposures are strongly
+    # correlated but on the same scale
+    make_dose_data <- function(dose, n, par) {
+      tibble::tibble(
+        dose = dose,
+        exposure_1 = generate_exposure(dose, n = n),
+        exposure_2 = 0.7 * exposure_1 + 0.3 * generate_exposure(dose, n = n),
+
+        # add continuous and binary covariates
+        cnt_a = continuous_covariate(n = n),
+        cnt_b = continuous_covariate(n = n),
+        cnt_c = continuous_covariate(n = n),
+        bin_d = binary_covariate(n = n, p = .5),
+        bin_e = binary_covariate(n = n, p = .7),
+
+        # response 1 is continuous
+        response_1 = emax_fn(
+          exposure_1,
+          emax = par$emax_1,
+          ec50 = par$ec50_1,
+          e0 = par$e0_1,
+          gamma = par$gamma_1
+        ) +
+          par$coef_a1 * cnt_a +
+          par$coef_b1 * cnt_b +
+          par$coef_c1 * cnt_c +
+          par$coef_d1 * bin_d +
+          stats::rnorm(n, 0, par$sigma_1),
+
+        # response 2 is binary; start with the predictor
+        bin_pred = emax_fn(
+          exposure_1,
+          emax = par$emax_2,
+          ec50 = par$ec50_2,
+          e0 = par$e0_2,
+          gamma = par$gamma_2
+        ) +
+          par$coef_a2 * cnt_a +
+          par$coef_b2 * cnt_b +
+          par$coef_c2 * cnt_c +
+          par$coef_d2 * bin_d,
+
+        # convert
+        bin_prob = 1 / (1 + exp(-bin_pred)),
+        response_2 = as.numeric(stats::runif(n) < bin_prob)
+      ) |>
+        dplyr::select(-bin_pred, -bin_prob) # remove intermediate variables
+    }
+
+    # create data set assuming three dosing groups and placebo
+    dat <- dplyr::bind_rows(
+      make_dose_data(dose = 0, n = 100, par = par),
+      make_dose_data(dose = 100, n = 100, par = par),
+      make_dose_data(dose = 200, n = 100, par = par),
+      make_dose_data(dose = 300, n = 100, par = par)
+    )
+
+    return(dat)
+  }
+
+  # generate data -----------------------------------------------------------
+
+  d_sim_placebo <- simulate_data()
+  d_sim_placebo <- d_sim_placebo |> 
+    dplyr::mutate(id = dplyr::row_number()) |> 
+    dplyr::relocate(response_1, response_2, .after = exposure_2) |> 
+    dplyr::relocate(id, 1) |> 
+    dplyr::rename(
+      exp_1 = exposure_1, 
+      exp_2 = exposure_2,
+      rsp_1 = response_1,
+      rsp_2 = response_2
+    )
+
+  d_sim_placebo
+})
+
+readr::write_csv(d_sim_placebo, "data-raw/d_sim_placebo.csv")
+usethis::use_data(d_sim_placebo, overwrite = TRUE)
+
diff --git a/data-raw/d_sim_placebo.csv b/data-raw/d_sim_placebo.csv
new file mode 100644
index 0000000..a5b76b5
--- /dev/null
+++ b/data-raw/d_sim_placebo.csv
@@ -0,0 +1,401 @@
+id,dose,exp_1,exp_2,rsp_1,rsp_2,cnt_a,cnt_b,cnt_c,bin_d,bin_e
+1,0,0,0,6.489196214645731,0,3.057604138550052,6.5048262145977995,5.928022604062216,0,1
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diff --git a/data/d_sim_placebo.rda b/data/d_sim_placebo.rda
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diff --git a/man/d_sim_placebo.Rd b/man/d_sim_placebo.Rd
new file mode 100644
index 0000000..720a3ca
--- /dev/null
+++ b/man/d_sim_placebo.Rd
@@ -0,0 +1,42 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/yyy.R
+\docType{data}
+\name{d_sim_placebo}
+\alias{d_sim_placebo}
+\title{Sample simulated data for Emax exposure-response models with covariates and placebo}
+\format{
+A data frame with columns:
+\describe{
+\item{id}{Subject identifier}
+\item{dose}{Nominal dose, units not specified}
+\item{exp_1}{Exposure value on metric 1, units and metric not specified}
+\item{exp_2}{Exposure value on metric 2, units and metric not specified}
+\item{rsp_1}{Continuous response value (units not specified)}
+\item{rsp_2}{Binary response value (group labels not specified)}
+\item{cnt_a}{Continuous valued covariate}
+\item{cnt_b}{Continuous valued covariate}
+\item{cnt_c}{Continuous valued covariate}
+\item{bin_d}{Binary valued covariate}
+\item{bin_e}{Binary valued covariate}
+}
+}
+\usage{
+d_sim_placebo
+}
+\description{
+Sample simulated data for Emax exposure-response models with covariates and placebo
+}
+\details{
+This simulated dataset is entirely synthetic. It is a generic data set that can be used
+to illustrate Emax modeling with placebo data. It contains variables corresponding to
+dose and exposure, and includes both a continuous response variable and a binary response
+variable. Three continuous valued covariates are included, along with two binary covariates.
+Data from two exposure metrics are included.
+
+You can find the data generating code in the package source code,
+under \code{data-raw/d_sim_placebo.R}.
+}
+\examples{
+d_sim_placebo
+}
+\keyword{datasets}

From a21252fe5cfdc4c146f246472aad28113b109326 Mon Sep 17 00:00:00 2001
From: Danielle Navarro <djnavarro@protonmail.com>
Date: Thu, 27 Nov 2025 14:04:41 +1100
Subject: [PATCH 5/7] include placebo data in pkgdown site

---
 _pkgdown.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/_pkgdown.yml b/_pkgdown.yml
index d68c3a5..7b2f97a 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -73,6 +73,7 @@ reference:
   - d_sim_binom_cov
   - d_sim_lin
   - d_sim_emax
+  - d_sim_placebo
 - title: S3 methods
   contents:
   - ermod_method

From 52c271efb89926b3d8a184bf2e302e6be670409b Mon Sep 17 00:00:00 2001
From: Danielle Navarro <djnavarro@protonmail.com>
Date: Thu, 27 Nov 2025 14:08:16 +1100
Subject: [PATCH 6/7] linter fixeds

---
 R/plot_ermod.R           | 46 ++++++++++++++++++++--------------------
 R/yyy.R                  |  5 ++---
 data-raw/d_sim_placebo.R | 11 +++++-----
 3 files changed, 30 insertions(+), 32 deletions(-)

diff --git a/R/plot_ermod.R b/R/plot_ermod.R
index bae35cd..9a56a84 100644
--- a/R/plot_ermod.R
+++ b/R/plot_ermod.R
@@ -337,7 +337,7 @@ plot_er.ersim_med_qi <- function(
     # binned probability ------------------------------------------------------
     if (is.null(bin_breaks)) {
       bin_breaks <- stats::quantile(
-        origdata[[var_exposure]], 
+        origdata[[var_exposure]],
         probs = seq(0, 1, 1 / n_bins)
       )
     }
@@ -353,33 +353,33 @@ plot_er.ersim_med_qi <- function(
 
     gg <- gg +
       ggplot2::geom_vline(
-        xintercept = bin_breaks, 
+        xintercept = bin_breaks,
         linetype = "dashed",
         alpha = 0.3
       ) +
       xgxr::xgx_stat_ci(
         data = origdata,
         ggplot2::aes(
-          x = .data[[var_exposure]], 
+          x = .data[[var_exposure]],
           y = .data[[".resp_num"]]
         ),
-        breaks = bin_breaks, 
-        conf_level = qi_width, 
-        distribution = "binomial", 
-        geom = c("point"), 
-        shape = 0, 
+        breaks = bin_breaks,
+        conf_level = qi_width,
+        distribution = "binomial",
+        geom = c("point"),
+        shape = 0,
         size = 4
       ) +
       xgxr::xgx_stat_ci(
         data = origdata,
         ggplot2::aes(
-          x = .data[[var_exposure]], 
+          x = .data[[var_exposure]],
           y = .data[[".resp_num"]]
         ),
-        breaks = bin_breaks, 
-        conf_level = qi_width, 
-        distribution = "binomial", 
-        geom = c("errorbar"), 
+        breaks = bin_breaks,
+        conf_level = qi_width,
+        distribution = "binomial",
+        geom = c("errorbar"),
         linewidth = 0.5
       )
 
@@ -631,16 +631,16 @@ plot_er.ermod <- function(
 #' }
 #'
 plot_er_gof <- function(
-    x, add_boxplot = !is.null(var_group), 
+    x, add_boxplot = !is.null(var_group),
     boxplot_height = 0.15,
     show_boxplot_y_title = FALSE,
-    var_group = NULL, 
-    n_bins = 4, 
+    var_group = NULL,
+    n_bins = 4,
     bin_breaks = NULL,
     qi_width_obs = 0.95,
     show_coef_exp = FALSE,
-    coef_pos_x = NULL, 
-    coef_pos_y = NULL, 
+    coef_pos_x = NULL,
+    coef_pos_y = NULL,
     coef_size = 4,
     qi_width_coef = 0.95,
     qi_width_sim = 0.95,
@@ -651,22 +651,22 @@ plot_er_gof <- function(
     show_coef_exp = show_coef_exp,
     show_caption = show_caption,
     options_orig_data = list(
-      add_boxplot = add_boxplot, 
+      add_boxplot = add_boxplot,
       boxplot_height = boxplot_height,
       show_boxplot_y_title = show_boxplot_y_title,
       var_group = var_group,
-      n_bins = n_bins, 
+      n_bins = n_bins,
       bin_breaks = bin_breaks,
       qi_width = qi_width_obs
     ),
     options_coef_exp = list(
-      qi_width = qi_width_coef, 
-      pos_x = coef_pos_x, 
+      qi_width = qi_width_coef,
+      pos_x = coef_pos_x,
       pos_y = coef_pos_y,
       size = coef_size
     ),
     options_caption = list(
-      orig_data_summary = TRUE, 
+      orig_data_summary = TRUE,
       coef_exp = show_coef_exp
     ),
     qi_width_sim = qi_width_sim
diff --git a/R/yyy.R b/R/yyy.R
index f597fff..e77e1bc 100644
--- a/R/yyy.R
+++ b/R/yyy.R
@@ -165,8 +165,8 @@ if (getRversion() >= "2.15.1") {
 #' @details
 #'
 #' This simulated dataset is entirely synthetic. It is a generic data set that can be used
-#' to illustrate Emax modeling with placebo data. It contains variables corresponding to 
-#' dose and exposure, and includes both a continuous response variable and a binary response 
+#' to illustrate Emax modeling with placebo data. It contains variables corresponding to
+#' dose and exposure, and includes both a continuous response variable and a binary response
 #' variable. Three continuous valued covariates are included, along with two binary covariates.
 #' Data from two exposure metrics are included.
 #'
@@ -176,4 +176,3 @@ if (getRversion() >= "2.15.1") {
 #' @examples
 #' d_sim_placebo
 "d_sim_placebo"
-
diff --git a/data-raw/d_sim_placebo.R b/data-raw/d_sim_placebo.R
index 00e5408..7ef2b7d 100644
--- a/data-raw/d_sim_placebo.R
+++ b/data-raw/d_sim_placebo.R
@@ -121,12 +121,12 @@ d_sim_placebo <- local({
   # generate data -----------------------------------------------------------
 
   d_sim_placebo <- simulate_data()
-  d_sim_placebo <- d_sim_placebo |> 
-    dplyr::mutate(id = dplyr::row_number()) |> 
-    dplyr::relocate(response_1, response_2, .after = exposure_2) |> 
-    dplyr::relocate(id, 1) |> 
+  d_sim_placebo <- d_sim_placebo |>
+    dplyr::mutate(id = dplyr::row_number()) |>
+    dplyr::relocate(response_1, response_2, .after = exposure_2) |>
+    dplyr::relocate(id, 1) |>
     dplyr::rename(
-      exp_1 = exposure_1, 
+      exp_1 = exposure_1,
       exp_2 = exposure_2,
       rsp_1 = response_1,
       rsp_2 = response_2
@@ -137,4 +137,3 @@ d_sim_placebo <- local({
 
 readr::write_csv(d_sim_placebo, "data-raw/d_sim_placebo.csv")
 usethis::use_data(d_sim_placebo, overwrite = TRUE)
-

From 0cbb2bbc4b0a113be821c0cf9338e64f040d2d3d Mon Sep 17 00:00:00 2001
From: Danielle Navarro <djnavarro@protonmail.com>
Date: Thu, 27 Nov 2025 18:51:32 +1100
Subject: [PATCH 7/7] dummy commit to trigger gha

---
 R/plot_ermod.R | 1 -
 1 file changed, 1 deletion(-)

diff --git a/R/plot_ermod.R b/R/plot_ermod.R
index 9a56a84..255c805 100644
--- a/R/plot_ermod.R
+++ b/R/plot_ermod.R
@@ -306,7 +306,6 @@ plot_er.ersim_med_qi <- function(
   return(caption)
 }
 
-
 .plot_er_binary <- function(
     gg, x, origdata, show_orig_data, options_orig_data) {
   var_resp <- extract_var_resp(x)