Merge remote-tracking branch 'origin/main' into 402-individual-loo

Genentech · Aug 20, 2024 · 8bba385 · 8bba385
2 parents 5d62acf + 31c82a1
commit 8bba385
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Showing 15 changed files with 428 additions and 18 deletions.
diff --git a/R/LongitudinalClaretBruno.R b/R/LongitudinalClaretBruno.R
@@ -39,6 +39,8 @@ NULL
 #' @param sigma (`Prior`)\cr for the variance of the longitudinal values.
 #'
 #' @param centred (`logical`)\cr whether to use the centred parameterization.
+#' @param scaled_variance (`logical`)\cr whether the variance should be scaled by the expected value
+#' (see the "Statistical Specifications" vignette for more details)
 #'
 #' @export
 LongitudinalClaretBruno <- function(
@@ -55,11 +57,13 @@ LongitudinalClaretBruno <- function(
 
     sigma = prior_lognormal(log(0.1), 0.5),
 
+    scaled_variance = TRUE,
     centred = FALSE
 ) {
 
     sf_model <- StanModule(decorated_render(
         .x = read_stan("lm-claret-bruno/model.stan"),
+        scaled_variance = scaled_variance,
         centred = centred
     ))
 

diff --git a/R/LongitudinalGSF.R b/R/LongitudinalGSF.R
@@ -42,6 +42,8 @@ NULL
 #' @param sigma (`Prior`)\cr for the variance of the longitudinal values `sigma`.
 #'
 #' @param centred (`logical`)\cr whether to use the centred parameterization.
+#' @param scaled_variance (`logical`)\cr whether the variance should be scaled by the expected value
+#' (see the "Statistical Specifications" vignette for more details)
 #'
 #' @importFrom stats qlogis
 #' @export
@@ -59,12 +61,14 @@ LongitudinalGSF <- function(
 
     sigma = prior_lognormal(log(0.1), 1),
 
+    scaled_variance = TRUE,
     centred = FALSE
 ) {
 
     gsf_model <- StanModule(decorated_render(
         .x = read_stan("lm-gsf/model.stan"),
-        centred = centred
+        centred = centred,
+        scaled_variance = scaled_variance
     ))
 
     # Apply constraints

diff --git a/R/SimLongitudinalClaretBruno.R b/R/SimLongitudinalClaretBruno.R
@@ -23,6 +23,9 @@ NULL
 #' @param link_identity (`number`)\cr the link coefficient for the SLD Identity contribution.
 #' @param link_growth (`number`)\cr the link coefficient for the growth parameter contribution.
 #'
+#' @param scaled_variance (`logical`)\cr whether the variance should be scaled by the expected value
+#' (see the "Statistical Specifications" vignette for more details)
+#'
 #' @slot sigma (`numeric`)\cr See arguments.
 #'
 #' @slot mu_b (`numeric`)\cr See arguments.
@@ -40,6 +43,8 @@ NULL
 #' @slot link_identity (`numeric`)\cr See arguments.
 #' @slot link_growth (`numeric`)\cr See arguments.
 #'
+#' @slot scaled_variance (`logical`)\cr See arguments.
+#'
 #' @family SimLongitudinal
 #' @name SimLongitudinalClaretBruno-class
 #' @exportClass SimLongitudinalClaretBruno
@@ -59,7 +64,8 @@ NULL
         link_dsld = "numeric",
         link_ttg = "numeric",
         link_identity = "numeric",
-        link_growth = "numeric"
+        link_growth = "numeric",
+        scaled_variance = "logical"
     )
 )
 
@@ -79,7 +85,8 @@ SimLongitudinalClaretBruno <- function(
     link_dsld = 0,
     link_ttg = 0,
     link_identity = 0,
-    link_growth = 0
+    link_growth = 0,
+    scaled_variance = TRUE
 ) {
 
     if (length(omega_b) == 1) omega_b <- rep(omega_b, length(mu_b))
@@ -101,7 +108,8 @@ SimLongitudinalClaretBruno <- function(
         link_dsld = link_dsld,
         link_ttg = link_ttg,
         link_identity = link_identity,
-        link_growth = link_growth
+        link_growth = link_growth,
+        scaled_variance = scaled_variance
     )
 }
 
@@ -158,7 +166,8 @@ sampleObservations.SimLongitudinalClaretBruno <- function(object, times_df) {
         dplyr::mutate(mu_sld = clbr_sld(.data$time, .data$ind_b, .data$ind_g, .data$ind_c, .data$ind_p)) |>
         dplyr::mutate(dsld = clbr_dsld(.data$time, .data$ind_b, .data$ind_g, .data$ind_c, .data$ind_p)) |>
         dplyr::mutate(ttg = clbr_ttg(.data$time, .data$ind_b, .data$ind_g, .data$ind_c, .data$ind_p)) |>
-        dplyr::mutate(sld = stats::rnorm(dplyr::n(), .data$mu_sld, .data$mu_sld * object@sigma)) |>
+        dplyr::mutate(sld_sd = ifelse(object@scaled_variance, .data$mu_sld * object@sigma, object@sigma)) |>
+        dplyr::mutate(sld = stats::rnorm(dplyr::n(), .data$mu_sld, .data$sld_sd)) |>
         dplyr::mutate(
             log_haz_link =
                 (object@link_dsld * .data$dsld) +

diff --git a/R/SimLongitudinalGSF.R b/R/SimLongitudinalGSF.R
@@ -22,6 +22,8 @@ NULL
 #' @param link_identity (`number`)\cr the link coefficient for the SLD Identity contribution.
 #' @param link_growth (`number`)\cr the link coefficient for the log-growth parameter contribution.
 #' @param link_shrinkage (`number`)\cr the link coefficient for the log-shrinkage parameter contribution.
+#' @param scaled_variance (`logical`)\cr whether the variance should be scaled by the expected value
+#' (see the "Statistical Specifications" vignette for more details)
 #'
 #' @slot sigma (`numeric`)\cr See arguments.
 #' @slot mu_s (`numeric`)\cr See arguments.
@@ -37,6 +39,7 @@ NULL
 #' @slot link_identity (`numeric`)\cr See arguments.
 #' @slot link_growth (`numeric`)\cr See arguments.
 #' @slot link_shrinkage (`numeric`)\cr See arguments.
+#' @slot scaled_variance (`numeric`)\cr See arguments.
 #' @family SimLongitudinal
 #' @name SimLongitudinalGSF-class
 #' @exportClass SimLongitudinalGSF
@@ -57,7 +60,8 @@ NULL
         link_ttg = "numeric",
         link_identity = "numeric",
         link_growth = "numeric",
-        link_shrinkage = "numeric"
+        link_shrinkage = "numeric",
+        scaled_variance = "logical"
     )
 )
 
@@ -78,7 +82,8 @@ SimLongitudinalGSF <- function(
     link_ttg = 0,
     link_identity = 0,
     link_growth = 0,
-    link_shrinkage = 0
+    link_shrinkage = 0,
+    scaled_variance = TRUE
 ) {
 
     if (length(omega_b) == 1) omega_b <- rep(omega_b, length(mu_b))
@@ -101,7 +106,8 @@ SimLongitudinalGSF <- function(
         link_ttg = link_ttg,
         link_identity = link_identity,
         link_growth = link_growth,
-        link_shrinkage = link_shrinkage
+        link_shrinkage = link_shrinkage,
+        scaled_variance = scaled_variance
     )
 }
 
@@ -161,7 +167,8 @@ sampleObservations.SimLongitudinalGSF <- function(object, times_df) {
         dplyr::mutate(mu_sld = gsf_sld(.data$time, .data$psi_b, .data$psi_s, .data$psi_g, .data$psi_phi)) |>
         dplyr::mutate(dsld = gsf_dsld(.data$time, .data$psi_b, .data$psi_s, .data$psi_g, .data$psi_phi)) |>
         dplyr::mutate(ttg = gsf_ttg(.data$time, .data$psi_b, .data$psi_s, .data$psi_g, .data$psi_phi)) |>
-        dplyr::mutate(sld = stats::rnorm(dplyr::n(), .data$mu_sld, .data$mu_sld * object@sigma)) |>
+        dplyr::mutate(sld_sd = ifelse(object@scaled_variance, .data$mu_sld * object@sigma, object@sigma)) |>
+        dplyr::mutate(sld = stats::rnorm(dplyr::n(), .data$mu_sld, .data$sld_sd)) |>
         dplyr::mutate(
             log_haz_link =
                 (object@link_dsld * .data$dsld) +

diff --git a/inst/stan/lm-claret-bruno/model.stan b/inst/stan/lm-claret-bruno/model.stan
@@ -72,13 +72,21 @@ transformed parameters{
     long_obvs_log_lik[subject_tumour_index_obs] = vect_normal_log_dens(
         tumour_value[subject_tumour_index_obs],
         Ypred[subject_tumour_index_obs],
-        Ypred[subject_tumour_index_obs] * lm_clbr_sigma
+        {%- if scaled_variance -%}
+            Ypred[subject_tumour_index_obs] * lm_clbr_sigma
+        {% else %}
+            rep_vector(lm_clbr_sigma, n_tumour_obs)
+        {%- endif -%}
     );
     if (n_tumour_cens > 0 ) {
         long_obvs_log_lik[subject_tumour_index_cens] = vect_normal_log_cum(
             tumour_value_lloq,
             Ypred[subject_tumour_index_cens],
-            Ypred[subject_tumour_index_cens] * lm_clbr_sigma
+            {%- if scaled_variance -%}
+                Ypred[subject_tumour_index_cens] * lm_clbr_sigma
+            {% else %}
+                rep_vector(lm_clbr_sigma, n_tumour_cens)
+            {%- endif -%} 
         );
     }
 }

diff --git a/inst/stan/lm-gsf/model.stan b/inst/stan/lm-gsf/model.stan
@@ -76,13 +76,21 @@ transformed parameters{
     long_obvs_log_lik[subject_tumour_index_obs] = vect_normal_log_dens(
         tumour_value[subject_tumour_index_obs],
         Ypred[subject_tumour_index_obs],
-        Ypred[subject_tumour_index_obs] * lm_gsf_sigma
+        {%- if scaled_variance -%}
+            Ypred[subject_tumour_index_obs] * lm_gsf_sigma
+        {% else %}
+            rep_vector(lm_gsf_sigma, n_tumour_obs)
+        {%- endif -%}
     );
     if (n_tumour_cens > 0 ) {
         long_obvs_log_lik[subject_tumour_index_cens] = vect_normal_log_cum(
             tumour_value_lloq,
             Ypred[subject_tumour_index_cens],
-            Ypred[subject_tumour_index_cens] * lm_gsf_sigma
+            {%- if scaled_variance -%}
+                Ypred[subject_tumour_index_cens] * lm_gsf_sigma
+            {% else %}
+                rep_vector(lm_gsf_sigma, n_tumour_cens)
+            {%- endif -%} 
         );
     }
 }

diff --git a/man/LongitudinalClaretBruno-class.Rd b/man/LongitudinalClaretBruno-class.Rd
diff --git a/man/LongitudinalGSF-class.Rd b/man/LongitudinalGSF-class.Rd
diff --git a/man/SimLongitudinalClaretBruno-class.Rd b/man/SimLongitudinalClaretBruno-class.Rd
diff --git a/man/SimLongitudinalGSF-class.Rd b/man/SimLongitudinalGSF-class.Rd