Finished Simulation Rework

NAMESPACE

@@ -100,7 +100,6 @@ S3method(summary,Quantities)
 S3method(summary,SurvivalQuantities)
 S3method(write_stan,JointModel)
 export(.JointModelSamples)
-export(.SimLongitudinalSteinFojo)
 export(DataJoint)
 export(DataLongitudinal)
 export(DataSubject)
@@ -141,9 +140,6 @@ export(brierScore)
 export(compileStanModel)
 export(enableLink)
 export(generateQuantities)
-export(gsf_dsld)
-export(gsf_sld)
-export(gsf_ttg)
 export(initialValues)
 export(linkDSLD)
 export(linkIdentity)
@@ -167,9 +163,6 @@ export(prior_uniform)
 export(sampleObservations)
 export(sampleStanModel)
 export(sampleSubjects)
-export(sf_dsld)
-export(sf_sld)
-export(sf_ttg)
 export(show)
 export(write_stan)
 exportClasses(DataJoint)

R/DataJoint.R

@@ -132,7 +132,7 @@ setValidity(
 #'
 #' @description
 #' Coerces a data object into a `list` of data components required
-#' for fitting a [`JointModel`]. See the vignette (TODO) for more details.
+#' for fitting a [`JointModel`]. See the "Extending jmpost" vignette for more details.
 #'
 #' @name as_stan_list.DataObject
 #' @family as_stan_list

R/SimJointData.R

@@ -1,29 +1,12 @@
-# TODO - DOCS
-
-#' @exportClass SimJointData
-.SimJointData <- setClass(
-    "SimJointData",
-    slots = list(
-        longitudinal = "data.frame",
-        survival = "data.frame"
-    )
-)
-
-
-
-
 #' Simulating Joint Longitudinal and Time-to-Event Data
 #'
 #' @param design (`list`)\cr a list of [`SimGroup`] objects. See details.
-#' @param times (`numeric`)\cr time grid, e.g. specifying the days after randomization.
-#' @param lambda_cen (`number`)\cr rate of the exponential censoring distribution.
-#' @param beta_cont (`number`)\cr coefficient for the continuous covariate.
-#' @param beta_cat (`numeric`)\cr coefficients for the categorical covariate levels.
-#' @param longitudinal (`function`)\cr function of `lm_base` generating the longitudinal model outcomes.
-#' @param survival (`function`)\cr function of `lm_base` generating the survival model outcomes.
+#' @param longitudinal ([`SimLongitudinal`])\cr object specifying how to simulate the longitudinal data
+#' @param survival ([`SimSurvival`])\cr object specifying how to simulate the survival data
 #' @param .silent (`flag`)\cr whether to suppress info messages
-#' @param .debug (`flag`)\cr whether to enter debug mode such that the function
-#'   would only return a subset of columns.
+#'
+#' @slot longitudinal (`data.frame`)\cr the simulated longitudinal data.
+#' @slot survival (`data.frame`)\cr the simulated survival data.
 #'
 #' @details
 #'
@@ -38,7 +21,20 @@
 #' )
 #' ```
 #'
-#' @returns List with simulated `lm` (longitudinal) and `os` (survival) data sets.
+#' @name SimJointData-class
+#' @exportClass SimJointData
+.SimJointData <- setClass(
+    "SimJointData",
+    slots = list(
+        longitudinal = "data.frame",
+        survival = "data.frame"
+    )
+)
+
+
+
+
+#' @rdname SimJointData-class
 #' @export
 SimJointData <- function(
     design = list(
@@ -47,8 +43,7 @@ SimJointData <- function(
     ),
     longitudinal,
     survival,
-    .silent = FALSE,
-    .debug = FALSE
+    .silent = FALSE
 ) {
 
     assert(

R/SimLongitudinal.R

@@ -1,5 +1,13 @@
-# TODO - docs
 
+#' Abstract Simulation Class for Longitudinal Data
+#'
+#' @param times (`numeric`) the times to generate observations at.
+#'
+#' @description
+#' This class exists to be extended by other classes that simulate longitudinal data.
+#' It is not intended to be used directly.
+#' @name SimLongitudinal-class
+#' @family SimLongitudinal
 #' @exportClass SimLongitudinal
 .SimLongitudinal <- setClass(
     "SimLongitudinal",
@@ -8,6 +16,7 @@
     )
 )
 
+#' @rdname SimLongitudinal-class
 #' @export
 SimLongitudinal <- function(times = seq(0, 100, 50)) {
     .SimLongitudinal(times = times)

R/SimLongitudinalGSF.R

@@ -1,9 +1,7 @@
 
-
-# TODO - Docs
-
-#' Construct a Simulation Function for Longitudinal Data from GSF Model
+#' Simulate Longitudinal Data from a  GSF Model
 #'
+#' @param times (`numeric`)\cr the times to generate observations at.
 #' @param sigma (`number`)\cr the variance of the longitudinal values.
 #' @param mu_s (`numeric`)\cr the mean shrinkage rates for the two treatment arms.
 #' @param mu_g (`numeric`)\cr the mean growth rates for the two treatment arms.
@@ -17,9 +15,20 @@
 #' @param link_ttg (`number`)\cr the link coefficient for the time-to-growth contribution.
 #' @param link_identity (`number`)\cr the link coefficient for the SLD Identity contribution.
 #'
-#' @returns A function with argument `lm_base` that can be used to simulate
-#'   longitudinal data from the corresponding GSF model.
-#'
+#' @slot sigma (`numeric`)\cr See arguments.
+#' @slot mu_s (`numeric`)\cr See arguments.
+#' @slot mu_g (`numeric`)\cr See arguments.
+#' @slot mu_b (`numeric`)\cr See arguments.
+#' @slot omega_b (`numeric`)\cr See arguments.
+#' @slot omega_s (`numeric`)\cr See arguments.
+#' @slot omega_g (`numeric`)\cr See arguments.
+#' @slot a_phi (`numeric`)\cr See arguments.
+#' @slot b_phi (`numeric`)\cr See arguments.
+#' @slot link_dsld (`numeric`)\cr See arguments.
+#' @slot link_ttg (`numeric`)\cr See arguments.
+#' @slot link_identity (`numeric`)\cr See arguments.
+#' @family SimLongitudinal
+#' @name SimLongitudinalGSF-class
 #' @exportClass SimLongitudinalGSF
 .SimLongitudinalGSF <- setClass(
     "SimLongitudinalGSF",
@@ -40,6 +49,7 @@
     )
 )
 
+#' @rdname SimLongitudinalGSF-class
 #' @export
 SimLongitudinalGSF <- function(
     times = c(-100, -50, 0, 50, 100, 150, 250, 350, 450, 550) / 365,
@@ -100,6 +110,7 @@ setValidity(
 )
 
 
+#' @rdname sampleObservations
 #' @export
 sampleObservations.SimLongitudinalGSF <- function(object, times_df) {
     times_df |>
@@ -116,23 +127,26 @@ sampleObservations.SimLongitudinalGSF <- function(object, times_df) {
 }
 
 
+#' @rdname sampleSubjects
 #' @export
 sampleSubjects.SimLongitudinalGSF <- function(object, subjects_df) {
     assert_that(
-        length(subjects_df$study) == length(object@mu_b),
-        length(subjects_df$arm) == length(object@mu_s),
         is.factor(subjects_df$study),
-        is.factor(subjects_df$arm)
+        is.factor(subjects_df$arm),
+        length(levels(subjects_df$study)) == length(object@mu_b),
+        length(levels(subjects_df$arm)) == length(object@mu_s)
     )
 
-    subjects_df |>
+    res <- subjects_df |>
         dplyr::distinct(.data$pt, .data$arm, .data$study) |>
         dplyr::mutate(study_idx = as.numeric(.data$study)) |>
         dplyr::mutate(arm_idx = as.numeric(.data$arm)) |>
         dplyr::mutate(psi_b = stats::rlnorm(dplyr::n(), log(object@mu_b[.data$study_idx]), object@omega_b)) |>
         dplyr::mutate(psi_s = stats::rlnorm(dplyr::n(), log(object@mu_s[.data$arm_idx]), object@omega_s)) |>
         dplyr::mutate(psi_g = stats::rlnorm(dplyr::n(), log(object@mu_g[.data$arm_idx]), object@omega_g)) |>
         dplyr::mutate(psi_phi = stats::rbeta(dplyr::n(), object@a_phi[.data$arm_idx], object@b_phi[.data$arm_idx]))
+
+    res[, c("pt", "arm", "study", "psi_b", "psi_s", "psi_g", "psi_phi")]
 }
 
 
@@ -149,21 +163,15 @@ sampleSubjects.SimLongitudinalGSF <- function(object, subjects_df) {
 #' @param phi (`number`)\cr shrinkage proportion.
 #'
 #' @returns The function results.
-#' @export
-#' @keywords internal
 #'
-#' @examples
-#' gsf_sld(1:10, 20, 0.3, 0.6, 0.2)
+#' @keywords internal
 gsf_sld <- function(time, b, s, g, phi) {
     phi <- dplyr::if_else(time >= 0, phi, 0)
     b * (phi * exp(-s * time) + (1 - phi) * exp(g * time))
 }
 
 
 #' @rdname gsf_sld
-#' @export
-#' @examples
-#' gsf_ttg(1:10, 20, 0.3, 0.6, 0.2)
 gsf_ttg <- function(time, b, s, g, phi) {
     t1 <- (log(s * phi / (g * (1 - phi))) / (g + s))
     t1[t1 <= 0] <- 0
@@ -172,9 +180,6 @@ gsf_ttg <- function(time, b, s, g, phi) {
 
 
 #' @rdname gsf_sld
-#' @export
-#' @examples
-#' gsf_dsld(1:10, 20, 0.3, 0.6, 0.2)
 gsf_dsld <- function(time, b, s, g, phi) {
     phi <- dplyr::if_else(time >= 0, phi, 0)
     t1 <- (1 - phi) * g * exp(g * time)

R/SimLongitudinalRandomSlope.R

@@ -1,18 +1,23 @@
 
-
-# TODO - Docs
-
-#' Construct a Simulation Function for Longitudinal Data from Random Slope Model
+#' Simulate Longitudinal Data from a Random Slope Model
 #'
+#' @param times (`numeric`)\cr the times to generate observations at.
 #' @param intercept (`number`)\cr the mean baseline value for each study.
 #' @param slope_mu (`numeric`)\cr the population slope for each treatment arm.
 #' @param slope_sigma (`number`)\cr the random slope standard deviation.
 #' @param sigma (`number`)\cr the variance of the longitudinal values.
 #' @param link_dsld (`number`)\cr the link coefficient for the DSLD contribution.
 #' @param link_identity (`number`)\cr the link coefficient for the identity contribution.
 #'
-#' @returns A function with argument `lm_base` that can be used to simulate
-#'   longitudinal data from the corresponding random slope model.
+#' @slot intercept (`numeric`)\cr See arguments.
+#' @slot slope_mu (`numeric`)\cr See arguments.
+#' @slot slope_sigma (`numeric`)\cr See arguments.
+#' @slot sigma (`numeric`)\cr See arguments.
+#' @slot link_dsld (`numeric`)\cr See arguments.
+#' @slot link_identity (`numeric`)\cr See arguments.
+#'
+#' @family SimLongitudinal
+#' @name SimLongitudinalRandomSlope-class
 #' @exportClass SimLongitudinalRandomSlope
 .SimLongitudinalRandomSlope <- setClass(
     "SimLongitudinalRandomSlope",
@@ -27,6 +32,7 @@
     )
 )
 
+#' @rdname SimLongitudinalRandomSlope-class
 #' @export
 SimLongitudinalRandomSlope <- function(
     times = c(-100, -50, 0, 50, 100, 150, 250, 350, 450, 550),
@@ -48,6 +54,7 @@ SimLongitudinalRandomSlope <- function(
     )
 }
 
+#' @rdname sampleObservations
 #' @export
 sampleObservations.SimLongitudinalRandomSlope <- function(object, times_df) {
     times_df |>
@@ -61,7 +68,7 @@ sampleObservations.SimLongitudinalRandomSlope <- function(object, times_df) {
         )
 }
 
-
+#' @rdname sampleSubjects
 #' @export
 sampleSubjects.SimLongitudinalRandomSlope <- function(object, subjects_df) {
     assert_that(