diff --git a/NEWS.md b/NEWS.md
index aa0f4736..f03a344b 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,6 +2,8 @@
 
 ## New features
 
+* Added default value for `antigen_isos` argument in `log_likelihood()` (#286)
+
 * Updated enteric fever example article with upgraded code and visualizations (#290)
 
 * Added template for reporting Issues 
diff --git a/R/llik.R b/R/log_likelihood.R
similarity index 70%
rename from R/llik.R
rename to R/log_likelihood.R
index 47b6c6d3..2022a83c 100644
--- a/R/llik.R
+++ b/R/log_likelihood.R
@@ -1,7 +1,9 @@
-#' Calculate log-likelihood
+#' @title Calculate log-likelihood
 #'
 #' @description
-#' Calculates the log-likelihood of a set of cross-sectional antibody response data, for a given incidence rate (`lambda`) value.
+#' Calculates the log-likelihood of a set of cross-sectional antibody response
+#' data, for a given incidence rate (`lambda`) value.
+#'
 #' `r lifecycle::badge("deprecated")`
 #'
 #' `llik()` was renamed to [log_likelihood()] to create a more
@@ -9,47 +11,45 @@
 #'
 #' @keywords internal
 #' @export
-
-llik <- function(
-    lambda,
-    pop_data,
-    antigen_isos,
-    curve_params,
-    noise_params,
-    verbose = FALSE,
-    ...) {
+llik <- function(...) {
   lifecycle::deprecate_warn("1.0.0", "llik()", "log_likelihood()")
-  log_likelihood(lambda,
-                 pop_data,
-                 antigen_isos,
-                 curve_params,
-                 noise_params,
-                 verbose)
+  log_likelihood(...)
 }
 
-#' Calculate log-likelihood
+#' @title Calculate log-likelihood
 #'
 #' @description
-#' Calculates the log-likelihood of a set of cross-sectional antibody response data, for a given incidence rate (`lambda`) value.
-#' @param pop_data a [data.frame()] with cross-sectional serology data per antibody and age, and additional columns
-#' @param antigen_isos Character vector listing one or more antigen isotypes. Values must match `pop_data`.
-#' @param curve_params a [data.frame()] containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
-#' - `antigen_iso`: a [character()] vector indicating antigen-isotype combinations
+#' Calculates the log-likelihood of a set of cross-sectional antibody response
+#' data, for a given incidence rate (`lambda`) value.
+#' @param pop_data a [data.frame()] with cross-sectional serology data
+#' by antibody and age, and additional columns
+#' @param antigen_isos Character vector listing one or more antigen isotypes.
+#' Values must match `pop_data`.
+#' @param curve_params a [data.frame()] containing MCMC samples of parameters
+#' from the Bayesian posterior distribution of a longitudinal decay curve model.
+#' The parameter columns must be named:
+#' - `antigen_iso`: a [character()] vector indicating antigen-isotype
+#' combinations
 #' - `iter`: an [integer()] vector indicating MCMC sampling iterations
 #' - `y0`: baseline antibody level at $t=0$ ($y(t=0)$)
 #' - `y1`: antibody peak level (ELISA units)
 #' - `t1`: duration of infection
-#' - `alpha`: antibody decay rate (1/days for the current longitudinal parameter sets)
+#' - `alpha`: antibody decay rate
+#' (1/days for the current longitudinal parameter sets)
 #' - `r`: shape factor of antibody decay
-#' @param noise_params a [data.frame()] (or [tibble::tibble()]) containing the following variables, specifying noise parameters for each antigen isotype:
-#' * `antigen_iso`: antigen isotype whose noise parameters are being specified on each row
+#' @param noise_params a [data.frame()] (or [tibble::tibble()])
+#' containing the following variables,
+#' specifying noise parameters for each antigen isotype:
+#' * `antigen_iso`: antigen isotype whose noise parameters are being specified
+#' on each row
 #' * `nu`: biological noise
 #' * `eps`: measurement noise
 #' * `y.low`: lower limit of detection for the current antigen isotype
 #' * `y.high`: upper limit of detection for the current antigen isotype
 #'
 #' @param verbose logical: if TRUE, print verbose log information to console
-#' @param ... additional arguments passed to other functions (not currently used).
+#' @param ... additional arguments passed to other functions
+#' (not currently used).
 #' @inheritParams f_dev
 #' @return the log-likelihood of the data with the current parameter values
 #' @export
@@ -84,19 +84,19 @@ llik <- function(
 log_likelihood <- function(
     lambda,
     pop_data,
-    antigen_isos,
     curve_params,
     noise_params,
+    antigen_isos = get_biomarker_levels(pop_data),
     verbose = FALSE,
     ...) {
   # Start with zero total
-  nllTotal <- 0
+  nll_total <- 0
 
   # Loop over antigen_isos
-  for (cur_antibody in antigen_isos)
-  {
+  for (cur_antibody in antigen_isos) {
     # the inputs can be lists, after `split(~antigen_ios)`
-    # this gives some speedups compared to running filter() every time .nll() is called
+    # this gives some speedups compared to running filter() every time .nll()
+    # is called
     if (!is.data.frame(pop_data)) {
       cur_data <- pop_data[[cur_antibody]]
       cur_curve_params <- curve_params[[cur_antibody]]
@@ -124,7 +124,7 @@ log_likelihood <- function(
       }
     }
 
-    nllSingle <-
+    nll_single <-
       f_dev(
         lambda = lambda,
         csdata = cur_data,
@@ -133,11 +133,12 @@ log_likelihood <- function(
       )
 
     # if (!is.na(nllSingle))  # not meaningful for vectorized f_dev()
-    {
-      nllTotal <- nllTotal + nllSingle # DEM note: summing log likelihoods represents an independence assumption for multiple Antibodies, given time since seroconversion
-    }
+    nll_total <- nll_total + nll_single
+    # note: summing log likelihoods represents an independence assumption
+    # for multiple Antibodies, given time since seroconversion
+
   }
 
   # Return total log-likelihood
-  return(-nllTotal)
+  return(-nll_total)
 }
diff --git a/man/dot-nll.Rd b/man/dot-nll.Rd
index 08ab530b..ba119ecf 100644
--- a/man/dot-nll.Rd
+++ b/man/dot-nll.Rd
@@ -12,21 +12,30 @@
 \item{...}{
   Arguments passed on to \code{\link[=log_likelihood]{log_likelihood}}
   \describe{
-    \item{\code{pop_data}}{a \code{\link[=data.frame]{data.frame()}} with cross-sectional serology data per antibody and age, and additional columns}
-    \item{\code{antigen_isos}}{Character vector listing one or more antigen isotypes. Values must match \code{pop_data}.}
-    \item{\code{curve_params}}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+    \item{\code{pop_data}}{a \code{\link[=data.frame]{data.frame()}} with cross-sectional serology data
+by antibody and age, and additional columns}
+    \item{\code{antigen_isos}}{Character vector listing one or more antigen isotypes.
+Values must match \code{pop_data}.}
+    \item{\code{curve_params}}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
-    \item{\code{noise_params}}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}}) containing the following variables, specifying noise parameters for each antigen isotype:
+    \item{\code{noise_params}}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}})
+containing the following variables,
+specifying noise parameters for each antigen isotype:
 \itemize{
-\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified on each row
+\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified
+on each row
 \item \code{nu}: biological noise
 \item \code{eps}: measurement noise
 \item \code{y.low}: lower limit of detection for the current antigen isotype
diff --git a/man/est.incidence.Rd b/man/est.incidence.Rd
index 58b19797..ce207ed6 100644
--- a/man/est.incidence.Rd
+++ b/man/est.incidence.Rd
@@ -21,20 +21,27 @@ est.incidence(
 \arguments{
 \item{pop_data}{a \link{data.frame} with cross-sectional serology data per antibody and age, and additional columns}
 
-\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
 
-\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}}) containing the following variables, specifying noise parameters for each antigen isotype:
+\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}})
+containing the following variables,
+specifying noise parameters for each antigen isotype:
 \itemize{
-\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified on each row
+\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified
+on each row
 \item \code{nu}: biological noise
 \item \code{eps}: measurement noise
 \item \code{y.low}: lower limit of detection for the current antigen isotype
diff --git a/man/est.incidence.by.Rd b/man/est.incidence.by.Rd
index 123a4b16..3111521c 100644
--- a/man/est.incidence.by.Rd
+++ b/man/est.incidence.by.Rd
@@ -23,20 +23,27 @@ est.incidence.by(
 \arguments{
 \item{pop_data}{a \link{data.frame} with cross-sectional serology data per antibody and age, and additional columns corresponding to each element of the \code{strata} input}
 
-\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
 
-\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}}) containing the following variables, specifying noise parameters for each antigen isotype:
+\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}})
+containing the following variables,
+specifying noise parameters for each antigen isotype:
 \itemize{
-\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified on each row
+\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified
+on each row
 \item \code{nu}: biological noise
 \item \code{eps}: measurement noise
 \item \code{y.low}: lower limit of detection for the current antigen isotype
diff --git a/man/graph.loglik.Rd b/man/graph.loglik.Rd
index f4b51a69..ca953c30 100644
--- a/man/graph.loglik.Rd
+++ b/man/graph.loglik.Rd
@@ -19,29 +19,38 @@ graph.loglik(
 )
 }
 \arguments{
-\item{pop_data}{a \code{\link[=data.frame]{data.frame()}} with cross-sectional serology data per antibody and age, and additional columns}
+\item{pop_data}{a \code{\link[=data.frame]{data.frame()}} with cross-sectional serology data
+by antibody and age, and additional columns}
 
-\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
 
-\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}}) containing the following variables, specifying noise parameters for each antigen isotype:
+\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}})
+containing the following variables,
+specifying noise parameters for each antigen isotype:
 \itemize{
-\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified on each row
+\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified
+on each row
 \item \code{nu}: biological noise
 \item \code{eps}: measurement noise
 \item \code{y.low}: lower limit of detection for the current antigen isotype
 \item \code{y.high}: upper limit of detection for the current antigen isotype
 }}
 
-\item{antigen_isos}{Character vector listing one or more antigen isotypes. Values must match \code{pop_data}.}
+\item{antigen_isos}{Character vector listing one or more antigen isotypes.
+Values must match \code{pop_data}.}
 
 \item{x}{sequence of lambda values to graph}
 
diff --git a/man/llik.Rd b/man/llik.Rd
index 38fa4961..4cf84bc8 100644
--- a/man/llik.Rd
+++ b/man/llik.Rd
@@ -1,21 +1,15 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/llik.R
+% Please edit documentation in R/log_likelihood.R
 \name{llik}
 \alias{llik}
 \title{Calculate log-likelihood}
 \usage{
-llik(
-  lambda,
-  pop_data,
-  antigen_isos,
-  curve_params,
-  noise_params,
-  verbose = FALSE,
-  ...
-)
+llik(...)
 }
 \description{
-Calculates the log-likelihood of a set of cross-sectional antibody response data, for a given incidence rate (\code{lambda}) value.
+Calculates the log-likelihood of a set of cross-sectional antibody response
+data, for a given incidence rate (\code{lambda}) value.
+
 \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}
 
 \code{llik()} was renamed to \code{\link[=log_likelihood]{log_likelihood()}} to create a more
diff --git a/man/log_likelihood.Rd b/man/log_likelihood.Rd
index ade719ab..7a9267e9 100644
--- a/man/log_likelihood.Rd
+++ b/man/log_likelihood.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/llik.R
+% Please edit documentation in R/log_likelihood.R
 \name{log_likelihood}
 \alias{log_likelihood}
 \title{Calculate log-likelihood}
@@ -7,9 +7,9 @@
 log_likelihood(
   lambda,
   pop_data,
-  antigen_isos,
   curve_params,
   noise_params,
+  antigen_isos = get_biomarker_levels(pop_data),
   verbose = FALSE,
   ...
 )
@@ -17,39 +17,50 @@ log_likelihood(
 \arguments{
 \item{lambda}{a \link{numeric} vector of incidence parameters, in events per person-year}
 
-\item{pop_data}{a \code{\link[=data.frame]{data.frame()}} with cross-sectional serology data per antibody and age, and additional columns}
+\item{pop_data}{a \code{\link[=data.frame]{data.frame()}} with cross-sectional serology data
+by antibody and age, and additional columns}
 
-\item{antigen_isos}{Character vector listing one or more antigen isotypes. Values must match \code{pop_data}.}
-
-\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
 
-\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}}) containing the following variables, specifying noise parameters for each antigen isotype:
+\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}})
+containing the following variables,
+specifying noise parameters for each antigen isotype:
 \itemize{
-\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified on each row
+\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified
+on each row
 \item \code{nu}: biological noise
 \item \code{eps}: measurement noise
 \item \code{y.low}: lower limit of detection for the current antigen isotype
 \item \code{y.high}: upper limit of detection for the current antigen isotype
 }}
 
+\item{antigen_isos}{Character vector listing one or more antigen isotypes.
+Values must match \code{pop_data}.}
+
 \item{verbose}{logical: if TRUE, print verbose log information to console}
 
-\item{...}{additional arguments passed to other functions (not currently used).}
+\item{...}{additional arguments passed to other functions
+(not currently used).}
 }
 \value{
 the log-likelihood of the data with the current parameter values
 }
 \description{
-Calculates the log-likelihood of a set of cross-sectional antibody response data, for a given incidence rate (\code{lambda}) value.
+Calculates the log-likelihood of a set of cross-sectional antibody response
+data, for a given incidence rate (\code{lambda}) value.
 }
 \examples{
 library(dplyr)
diff --git a/man/sim.cs.Rd b/man/sim.cs.Rd
index 74b2ccd0..01bae0a6 100644
--- a/man/sim.cs.Rd
+++ b/man/sim.cs.Rd
@@ -45,14 +45,18 @@ sim.cs(
 
 \item{add.noise}{a \code{\link[=logical]{logical()}} indicating whether to add biological and measurement noise}
 
-\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
 
diff --git a/man/sim.cs.multi.Rd b/man/sim.cs.multi.Rd
index 3f8cd593..fe2204cc 100644
--- a/man/sim.cs.multi.Rd
+++ b/man/sim.cs.multi.Rd
@@ -53,14 +53,18 @@ sim.cs.multi(
 \item \code{"long"} (one measurement per row) or
 \item \code{"wide"} (one serum sample per row)
 }}
-    \item{\code{curve_params}}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+    \item{\code{curve_params}}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
   }}
diff --git a/man/stratify_data.Rd b/man/stratify_data.Rd
index 7dacbcbb..fba7c6f0 100644
--- a/man/stratify_data.Rd
+++ b/man/stratify_data.Rd
@@ -15,20 +15,27 @@ stratify_data(
 )
 }
 \arguments{
-\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named:
+\item{curve_params}{a \code{\link[=data.frame]{data.frame()}} containing MCMC samples of parameters
+from the Bayesian posterior distribution of a longitudinal decay curve model.
+The parameter columns must be named:
 \itemize{
-\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype combinations
+\item \code{antigen_iso}: a \code{\link[=character]{character()}} vector indicating antigen-isotype
+combinations
 \item \code{iter}: an \code{\link[=integer]{integer()}} vector indicating MCMC sampling iterations
 \item \code{y0}: baseline antibody level at $t=0$ ($y(t=0)$)
 \item \code{y1}: antibody peak level (ELISA units)
 \item \code{t1}: duration of infection
-\item \code{alpha}: antibody decay rate (1/days for the current longitudinal parameter sets)
+\item \code{alpha}: antibody decay rate
+(1/days for the current longitudinal parameter sets)
 \item \code{r}: shape factor of antibody decay
 }}
 
-\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}}) containing the following variables, specifying noise parameters for each antigen isotype:
+\item{noise_params}{a \code{\link[=data.frame]{data.frame()}} (or \code{\link[tibble:tibble]{tibble::tibble()}})
+containing the following variables,
+specifying noise parameters for each antigen isotype:
 \itemize{
-\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified on each row
+\item \code{antigen_iso}: antigen isotype whose noise parameters are being specified
+on each row
 \item \code{nu}: biological noise
 \item \code{eps}: measurement noise
 \item \code{y.low}: lower limit of detection for the current antigen isotype
diff --git a/tests/testthat/_snaps/log_likelihood.md b/tests/testthat/_snaps/log_likelihood.md
new file mode 100644
index 00000000..4fd146e4
--- /dev/null
+++ b/tests/testthat/_snaps/log_likelihood.md
@@ -0,0 +1,4 @@
+# `log_likelihood()` gives consistent results
+
+    -9268.8238
+
diff --git a/tests/testthat/test-log_likelihood.R b/tests/testthat/test-log_likelihood.R
new file mode 100644
index 00000000..0a4e3d72
--- /dev/null
+++ b/tests/testthat/test-log_likelihood.R
@@ -0,0 +1,34 @@
+test_that("`log_likelihood()` gives consistent results", {
+  library(dplyr)
+  library(tibble)
+
+  # load in longitudinal parameters
+  dmcmc <- load_curve_params("https://osf.io/download/rtw5k")
+
+  xs_data <- "https://osf.io/download//n6cp3/" %>%
+    load_pop_data()
+
+  # Load noise params
+  cond <- tibble(
+    antigen_iso = c("HlyE_IgG", "HlyE_IgA"),
+    nu = c(0.5, 0.5),
+    # Biologic noise (nu)
+    eps = c(0, 0),
+    # M noise (eps)
+    y.low = c(1, 1),
+    # low cutoff (llod)
+    y.high = c(5e6, 5e6)
+  ) # high cutoff (y.high)
+
+  # Calculate log-likelihood
+  ll_AG <- log_likelihood( # nolint: object_name_linter
+    pop_data = xs_data,
+    curve_params = dmcmc,
+    noise_params = cond,
+    antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
+    lambda = 0.1
+  )
+
+  expect_snapshot_value(ll_AG)
+
+})