diff --git a/NAMESPACE b/NAMESPACE
index d7dad8b..d5b46ca 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -3,7 +3,7 @@
 export(add_exposure_data)
 export(biokinetics)
 export(biokinetics_priors)
-export(convert_log_scale_inverse)
+export(convert_log2_scale_inverse)
 importFrom(R6,R6Class)
 importFrom(data.table,":=")
 importFrom(data.table,.BY)
diff --git a/R/biokinetics.R b/R/biokinetics.R
index 16fdaa8..82295db 100644
--- a/R/biokinetics.R
+++ b/R/biokinetics.R
@@ -212,6 +212,7 @@ biokinetics <- R6::R6Class(
     #' @param priors Object of type \link[epikinetics]{biokinetics_priors}. Default biokinetics_priors().
     #' @param covariate_formula Formula specifying linear regression model. Note all variables in the formula
     #' will be treated as categorical variables. Default ~0.
+    #' @param preds_sd Standard deviation of predictor coefficients. Default 0.25.
     #' @param scale One of "log" or "natural". Default "natural". Is provided data on a log or a natural scale? If on a natural scale it
     #' will be converted to a log scale for model fitting.
     initialize = function(priors = biokinetics_priors(),
@@ -246,7 +247,7 @@ biokinetics <- R6::R6Class(
       validate_formula_vars(private$all_formula_vars, private$data)
       logger::log_info("Preparing data for stan")
       if (scale == "natural") {
-        private$data <- convert_log_scale(private$data, "value")
+        private$data <- convert_log2_scale(private$data, "value")
       }
       private$data[, `:=`(obs_id = seq_len(.N),
                           t_since_last_exp = as.integer(day - last_exp_day, units = "days"))]
@@ -269,6 +270,8 @@ biokinetics <- R6::R6Class(
     get_stan_data = function() {
       private$stan_input_data
     },
+    #' @description View the mapping of human readable covariate names to the model variable p.
+    #' @return A data.table mapping the model variable p to human readable covariates.
     get_covariate_lookup_table = function() {
       private$covariate_lookup_table
     },
@@ -390,10 +393,10 @@ biokinetics <- R6::R6Class(
       }
 
       if (summarise) {
-        dt_out <- convert_log_scale_inverse(
+        dt_out <- convert_log2_scale_inverse(
           dt_out, vars_to_transform = c("me", "lo", "hi"))
       } else {
-        dt_out <- convert_log_scale_inverse(
+        dt_out <- convert_log2_scale_inverse(
           dt_out, vars_to_transform = "mu")
       }
       dt_out
@@ -430,7 +433,7 @@ biokinetics <- R6::R6Class(
       dt_peak_switch <- private$recover_covariate_names(dt_peak_switch)
 
       if (private$scale == "natural") {
-        dt_peak_switch <- convert_log_scale_inverse(
+        dt_peak_switch <- convert_log2_scale_inverse(
           dt_peak_switch, vars_to_transform = c("mu_0", "mu_p", "mu_s"))
       }
 
@@ -491,11 +494,11 @@ biokinetics <- R6::R6Class(
       # Running the C++ code to simulate trajectories for each parameter sample
       # for each individual
       logger::log_info("Simulating individual trajectories")
-      dt_params_ind_traj <- data.table::setDT(biokinetics_simulate_trajectories(dt_params_ind))
+      dt_params_ind_traj <- biokinetics_simulate_trajectories(dt_params_ind)
 
       if (private$scale == "natural") {
-        dt_params_ind_traj <- convert_log_scale_inverse_cpp(
-          dt_params_ind_traj, vars_to_transform = "mu")
+        dt_params_ind_traj <- data.table::setDT(convert_log2_scale_inverse_cpp(
+          dt_params_ind_traj, vars_to_transform = "mu"))
       }
 
       # convert numeric pid to original pid
diff --git a/R/cpp11.R b/R/cpp11.R
index 2317c1c..5141cfe 100644
--- a/R/cpp11.R
+++ b/R/cpp11.R
@@ -1,7 +1,7 @@
 # Generated by cpp11: do not edit by hand
 
-convert_log_scale_inverse_cpp <- function(dt, vars_to_transform) {
-  .Call(`_epikinetics_convert_log_scale_inverse_cpp`, dt, vars_to_transform)
+convert_log2_scale_inverse_cpp <- function(dt, vars_to_transform) {
+  .Call(`_epikinetics_convert_log2_scale_inverse_cpp`, dt, vars_to_transform)
 }
 
 simulate_trajectories_cpp <- function(person_params) {
diff --git a/R/utils.R b/R/utils.R
index 576cfc2..1ee1a2e 100644
--- a/R/utils.R
+++ b/R/utils.R
@@ -1,4 +1,4 @@
-convert_log_scale <- function(
+convert_log2_scale <- function(
   dt_in, vars_to_transform = "titre",
   simplify_limits = TRUE) {
 
@@ -14,14 +14,14 @@ convert_log_scale <- function(
 
 #' @title Invert base 2 log scale conversion
 #'
-#' @description User provided data is converted to a base 2 log scale before model fitting. This
-#' function reverses that transformation. This function does not modify the provided data.table in-place,
-#' but returns a transformed copy.
+#' @description Natural scale data is converted to a base 2 log scale before model fitting. This
+#' function reverses that transformation and may be useful if working directly with fitted parameters.
+#' This function does not modify the provided data.table in-place, but returns a transformed copy.
 #' @return A data.table, identical to the input data but with specified columns transformed.
 #' @param dt_in data.table containing data to be transformed from base 2 log to natural scale.
 #' @param vars_to_transform Names of columns to apply the transformation to.
 #' @export
-convert_log_scale_inverse <- function(dt_in, vars_to_transform) {
+convert_log2_scale_inverse <- function(dt_in, vars_to_transform) {
   dt_out <- data.table::copy(dt_in)
   for (var in vars_to_transform) {
     # Reverse the log2 transformation and multiplication by 5.
diff --git a/man/biokinetics.Rd b/man/biokinetics.Rd
index 1de7305..5481497 100644
--- a/man/biokinetics.Rd
+++ b/man/biokinetics.Rd
@@ -50,6 +50,8 @@ for required columns: \code{vignette("data", package = "epikinetics")}.}
 \item{\code{covariate_formula}}{Formula specifying linear regression model. Note all variables in the formula
 will be treated as categorical variables. Default ~0.}
 
+\item{\code{preds_sd}}{Standard deviation of predictor coefficients. Default 0.25.}
+
 \item{\code{scale}}{One of "log" or "natural". Default "natural". Is provided data on a log or a natural scale? If on a natural scale it
 will be converted to a log scale for model fitting.}
 }
@@ -76,10 +78,14 @@ A list of arguments that will be passed to the stan model.
 \if{html}{\out{<a id="method-biokinetics-get_covariate_lookup_table"></a>}}
 \if{latex}{\out{\hypertarget{method-biokinetics-get_covariate_lookup_table}{}}}
 \subsection{Method \code{get_covariate_lookup_table()}}{
+View the mapping of human readable covariate names to the model variable p.
 \subsection{Usage}{
 \if{html}{\out{<div class="r">}}\preformatted{biokinetics$get_covariate_lookup_table()}\if{html}{\out{</div>}}
 }
 
+\subsection{Returns}{
+A data.table mapping the model variable p to human readable covariates.
+}
 }
 \if{html}{\out{<hr>}}
 \if{html}{\out{<a id="method-biokinetics-fit"></a>}}
diff --git a/man/convert_log_scale_inverse.Rd b/man/convert_log2_scale_inverse.Rd
similarity index 57%
rename from man/convert_log_scale_inverse.Rd
rename to man/convert_log2_scale_inverse.Rd
index d84c93a..f5409a2 100644
--- a/man/convert_log_scale_inverse.Rd
+++ b/man/convert_log2_scale_inverse.Rd
@@ -1,10 +1,10 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/utils.R
-\name{convert_log_scale_inverse}
-\alias{convert_log_scale_inverse}
+\name{convert_log2_scale_inverse}
+\alias{convert_log2_scale_inverse}
 \title{Invert base 2 log scale conversion}
 \usage{
-convert_log_scale_inverse(dt_in, vars_to_transform)
+convert_log2_scale_inverse(dt_in, vars_to_transform)
 }
 \arguments{
 \item{dt_in}{data.table containing data to be transformed from base 2 log to natural scale.}
@@ -15,7 +15,7 @@ convert_log_scale_inverse(dt_in, vars_to_transform)
 A data.table, identical to the input data but with specified columns transformed.
 }
 \description{
-User provided data is converted to a base 2 log scale before model fitting. This
-function reverses that transformation. This function does not modify the provided data.table in-place,
-but returns a transformed copy.
+Natural scale data is converted to a base 2 log scale before model fitting. This
+function reverses that transformation and may be useful if working directly with fitted parameters.
+This function does not modify the provided data.table in-place, but returns a transformed copy.
 }
diff --git a/src/convert_log_scale_inverse.cpp b/src/convert_log_scale_inverse.cpp
index 2abe7ba..77524e6 100644
--- a/src/convert_log_scale_inverse.cpp
+++ b/src/convert_log_scale_inverse.cpp
@@ -3,7 +3,7 @@
 using namespace cpp11;
 
 [[cpp11::register]]
-cpp11::data_frame convert_log_scale_inverse_cpp(cpp11::writable::list dt,
+cpp11::data_frame convert_log2_scale_inverse_cpp(cpp11::writable::list dt,
                                                 cpp11::strings vars_to_transform) {
 
   for (int i = 0; i < vars_to_transform.size(); i++) {
diff --git a/src/cpp11.cpp b/src/cpp11.cpp
index caad6d2..18c707b 100644
--- a/src/cpp11.cpp
+++ b/src/cpp11.cpp
@@ -6,10 +6,10 @@
 #include <R_ext/Visibility.h>
 
 // convert_log_scale_inverse.cpp
-cpp11::data_frame convert_log_scale_inverse_cpp(cpp11::writable::list dt, cpp11::strings vars_to_transform);
-extern "C" SEXP _epikinetics_convert_log_scale_inverse_cpp(SEXP dt, SEXP vars_to_transform) {
+cpp11::data_frame convert_log2_scale_inverse_cpp(cpp11::writable::list dt, cpp11::strings vars_to_transform);
+extern "C" SEXP _epikinetics_convert_log2_scale_inverse_cpp(SEXP dt, SEXP vars_to_transform) {
   BEGIN_CPP11
-    return cpp11::as_sexp(convert_log_scale_inverse_cpp(cpp11::as_cpp<cpp11::decay_t<cpp11::writable::list>>(dt), cpp11::as_cpp<cpp11::decay_t<cpp11::strings>>(vars_to_transform)));
+    return cpp11::as_sexp(convert_log2_scale_inverse_cpp(cpp11::as_cpp<cpp11::decay_t<cpp11::writable::list>>(dt), cpp11::as_cpp<cpp11::decay_t<cpp11::strings>>(vars_to_transform)));
   END_CPP11
 }
 // simulate_trajectories.cpp
@@ -22,8 +22,8 @@ extern "C" SEXP _epikinetics_simulate_trajectories_cpp(SEXP person_params) {
 
 extern "C" {
 static const R_CallMethodDef CallEntries[] = {
-    {"_epikinetics_convert_log_scale_inverse_cpp", (DL_FUNC) &_epikinetics_convert_log_scale_inverse_cpp, 2},
-    {"_epikinetics_simulate_trajectories_cpp",     (DL_FUNC) &_epikinetics_simulate_trajectories_cpp,     1},
+    {"_epikinetics_convert_log2_scale_inverse_cpp", (DL_FUNC) &_epikinetics_convert_log2_scale_inverse_cpp, 2},
+    {"_epikinetics_simulate_trajectories_cpp",      (DL_FUNC) &_epikinetics_simulate_trajectories_cpp,      1},
     {NULL, NULL, 0}
 };
 }
diff --git a/tests/testthat/test-convert-log-scale.R b/tests/testthat/test-convert-log-scale.R
index b6c378b..26715fb 100644
--- a/tests/testthat/test-convert-log-scale.R
+++ b/tests/testthat/test-convert-log-scale.R
@@ -1,14 +1,14 @@
 test_that("Can convert to and from log scale in R", {
   inputs <- data.table::fread(test_path("testdata", "testdata.csv"))
-  log_inputs <- convert_log_scale(inputs, "me", simplify_limits = FALSE)
-  unlog_inputs <- convert_log_scale_inverse(log_inputs, "me")
+  log_inputs <- convert_log2_scale(inputs, "me", simplify_limits = FALSE)
+  unlog_inputs <- convert_log2_scale_inverse(log_inputs, "me")
 
   expect_equal(inputs, unlog_inputs)
 })
 
 test_that("Can convert from log scale in R", {
   inputs <- data.table::fread(test_path("testdata", "testdata.csv"))
-  res <- convert_log_scale_inverse(
+  res <- convert_log2_scale_inverse(
     inputs, vars_to_transform = c("me", "lo"))
 
   expect_equal(res$me, 5 * 2^inputs$me)
@@ -19,7 +19,7 @@ test_that("Can convert from log scale in R", {
 
 test_that("Can convert from log scale in Cpp", {
   inputs <- data.table::fread(test_path("testdata", "testdata.csv"))
-  rescpp <- convert_log_scale_inverse_cpp(
+  rescpp <- convert_log2_scale_inverse_cpp(
     inputs, vars_to_transform = c("me", "lo"))
 
   expect_equal(rescpp$me, 5 * 2^(inputs$me))
diff --git a/tests/testthat/test-data.R b/tests/testthat/test-data.R
index 233f1cb..a9aa1a1 100644
--- a/tests/testthat/test-data.R
+++ b/tests/testthat/test-data.R
@@ -52,7 +52,7 @@ test_that("Natural scale data is converted to log scale for stan", {
   dat <- data.table::fread(system.file("delta_full.rds", package = "epikinetics"))
   mod <- biokinetics$new(data = dat)
   stan_data <- mod$get_stan_data()
-  expect_equivalent(stan_data$value, convert_log_scale(dat, "value")$value)
+  expect_equivalent(stan_data$value, convert_log2_scale(dat, "value")$value)
 })
 
 test_that("Log scale data is passed directly to stan", {
diff --git a/tests/testthat/test-simulate-individual-trajectories.R b/tests/testthat/test-simulate-individual-trajectories.R
index dec0046..507b877 100644
--- a/tests/testthat/test-simulate-individual-trajectories.R
+++ b/tests/testthat/test-simulate-individual-trajectories.R
@@ -81,3 +81,19 @@ test_that("Exposure dates are brought forward by time_shift days", {
   expect_equal(trajectories$mu, trajectories_shifted$mu)
   expect_true(all(as.numeric(difftime(trajectories$exposure_date, trajectories_shifted$exposure_date, units = "days")) == 75))
 })
+
+test_that("Natural scale data is returned on natural scale", {
+  mod <- biokinetics$new(file_path = system.file("delta_full.rds", package = "epikinetics"),
+                         covariate_formula = ~0 + infection_history, scale = "natural")
+  mod$fit()
+  trajectories <- mod$simulate_individual_trajectories(summarise = TRUE, n_draws = 10)
+  expect_false(all(trajectories$me < 10))
+})
+
+test_that("Log scale data is returned on log scale", {
+  mod <- biokinetics$new(file_path = system.file("delta_full.rds", package = "epikinetics"),
+                         covariate_formula = ~0 + infection_history, scale = "log")
+  mod$fit()
+  trajectories <- mod$simulate_individual_trajectories(summarise = TRUE, n_draws = 10)
+  expect_true(all(trajectories$me < 10))
+})
diff --git a/tests/testthat/test-simulate-population-trajectories.R b/tests/testthat/test-simulate-population-trajectories.R
index 246d392..73b7092 100644
--- a/tests/testthat/test-simulate-population-trajectories.R
+++ b/tests/testthat/test-simulate-population-trajectories.R
@@ -45,3 +45,19 @@ test_that("Only times up to t_max are returned", {
   trajectories <- mod$simulate_population_trajectories(summarise = TRUE, t_max = 10)
   expect_true(all(trajectories$t <= 10))
 })
+
+test_that("Natural scale data is returned on natural scale", {
+  mod <- biokinetics$new(file_path = system.file("delta_full.rds", package = "epikinetics"),
+                         covariate_formula = ~0 + infection_history, scale = "natural")
+  mod$fit()
+  trajectories <- mod$simulate_population_trajectories(summarise = TRUE, t_max = 10)
+  expect_false(all(trajectories$me < 10))
+})
+
+test_that("Log scale data is returned on log scale", {
+  mod <- biokinetics$new(file_path = system.file("delta_full.rds", package = "epikinetics"),
+                         covariate_formula = ~0 + infection_history, scale = "log")
+  mod$fit()
+  trajectories <- mod$simulate_population_trajectories(summarise = TRUE, t_max = 10)
+  expect_true(all(trajectories$me < 10))
+})