diff --git a/DESCRIPTION b/DESCRIPTION
index ea5d92de0..a46b14176 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: serodynamics
 Title: What the Package Does (One Line, Title Case)
-Version: 0.0.0.9047
+Version: 0.0.0.9048
 Authors@R: c(
     person("Peter", "Teunis", , "p.teunis@emory.edu", role = c("aut", "cph"),
            comment = "Author of the method and original code."),
diff --git a/NEWS.md b/NEWS.md
index 89199522a..c318d70f4 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,9 @@
 # serodynamics (development version)
 
+* Added standalone documentation page for the `sr_model` class, describing all
+  data columns and attributes including the upcoming `population_params`
+  attribute from PR #141.
+
 * Added dev container configuration for persistent, cached development environment
   that includes R, JAGS, and all dependencies preinstalled, making Copilot
   Workspace sessions much faster.
diff --git a/R/Run_Mod.R b/R/Run_Mod.R
index 25e75d601..c1ae89df0 100644
--- a/R/Run_Mod.R
+++ b/R/Run_Mod.R
@@ -26,7 +26,7 @@
 #' should be included as an element of the [list] object returned by `run_mod()`
 #' (see `Value` section below for details).
 #' Note: These objects can be large.
-#' @returns An `sr_model` class object: a subclass of [dplyr::tbl_df] that
+#' @returns An `sr_model` class object: a subclass of [tibble::tbl_df] that
 #' contains MCMC samples from the joint posterior distribution of the model
 #' parameters, conditional on the provided input `data`, 
 #' including the following:
diff --git a/R/nepal_sees_jags_output.R b/R/nepal_sees_jags_output.R
index fb75a06c7..2f23ad2a0 100644
--- a/R/nepal_sees_jags_output.R
+++ b/R/nepal_sees_jags_output.R
@@ -8,7 +8,8 @@
 #' which is the diagnosis type (typhoid or
 #' paratyphoid). Keeping only IDs `"newperson"`, `"sees_npl_1"`, `"sees_npl_2"`.
 #'
-#' @format An S3 object of class `sr_model`: A [dplyr::tbl_df] that contains the
+#' @format An S3 object of class `sr_model`:
+#' A [tibble::tbl_df] that contains the
 #'   posterior predictive distribution of the person-specific parameters for a
 #'   "new person" with no observed data (`Subject = "newperson"`) and posterior
 #'   distributions of the person-specific parameters for two arbitrarily-chosen
diff --git a/R/plot_predicted_curve.R b/R/plot_predicted_curve.R
index 3a0d46545..f1cb1bff1 100644
--- a/R/plot_predicted_curve.R
+++ b/R/plot_predicted_curve.R
@@ -12,7 +12,7 @@
 #' @param ids The participant IDs to plot; for example, `"sees_npl_128"`.
 #' @param antigen_iso  The antigen isotype to plot; for example, "HlyE_IgA" or 
 #' "HlyE_IgG".
-#' @param dataset (Optional) A [dplyr::tbl_df] with observed antibody response 
+#' @param dataset (Optional) A [tibble::tbl_df] with observed antibody response 
 #' data. 
 #' Must contain:
 #'   - `timeindays`
diff --git a/R/sr_model-class.R b/R/sr_model-class.R
new file mode 100644
index 000000000..508ad76ac
--- /dev/null
+++ b/R/sr_model-class.R
@@ -0,0 +1,113 @@
+#' `sr_model` class
+#'
+#' @description
+#' An S3 class representing the output of a Bayesian MCMC model
+#' fitted by [run_mod()]. The `sr_model` object is a subclass
+#' of [tibble::tbl_df] containing MCMC samples from the joint posterior
+#' distribution of host-specific antibody kinetic parameters,
+#' conditional on the provided input data.
+#'
+#' Each row represents one posterior draw for one parameter, one
+#' antigen-isotype combination, one subject, and one stratification level.
+#'
+#' @section Data columns:
+#'
+#' \describe{
+#'   \item{Iteration}{[integer] MCMC sampling iteration index.}
+#'   \item{Chain}{[integer] MCMC chain index (between 1 and the number of
+#'   chains specified in [run_mod()]).}
+#'   \item{Parameter}{[character] name of the antibody dynamic curve parameter.
+#'   One of:
+#'   \itemize{
+#'     \item `y0` -- baseline antibody concentration
+#'     \item `y1` -- peak antibody concentration
+#'     \item `t1` -- time to peak
+#'     \item `shape` -- shape parameter
+#'     \item `alpha` -- decay rate
+#'   }}
+#'   \item{Iso_type}{[character] antibody/antigen isotype combination being
+#'   evaluated (e.g., `"HlyE_IgA"`, `"HlyE_IgG"`).}
+#'   \item{Stratification}{[character] the level of the stratification variable
+#'   used when fitting the model, or `"None"` if no stratification was
+#'   specified.}
+#'   \item{Subject}{[character] identifier of the subject. Includes observed
+#'   subjects as well as `"newperson"`, which represents the posterior
+#'   predictive distribution for a hypothetical new individual with no observed
+#'   data.}
+#'   \item{value}{[numeric] posterior sample value of the parameter.}
+#' }
+#'
+#' @section Attributes:
+#'
+#' In addition to the standard [tibble::tbl_df] attributes (`names`,
+#' `row.names`, `class`), an `sr_model` object carries the following
+#' custom attributes:
+#'
+#' \describe{
+#'   \item{nChains}{[integer] number of MCMC chains run.}
+#'   \item{nParameters}{[integer] number of parameters estimated in the model.}
+#'   \item{nIterations}{[integer] total number of MCMC iterations specified.}
+#'   \item{nBurnin}{[integer] number of burn-in iterations discarded before
+#'   sampling.}
+#'   \item{nThin}{[integer] thinning interval (ratio of total iterations to
+#'   retained samples, i.e., `niter / nmc`).}
+#'   \item{population_params}{(optional) a [tibble::tbl_df] of modeled
+#'   population-level parameters, included when `with_pop_params = TRUE` in
+#'   [run_mod()]. Indexed by `Iteration`, `Chain`, `Parameter`, `Iso_type`,
+#'   and `Stratification`. Contains the following population parameters:
+#'   \itemize{
+#'     \item `mu.par` -- the population means of the host-specific model
+#'     parameters (on logarithmic scales).
+#'     \item `prec.par` -- the population precision matrix of the
+#'     hyperparameters (with diagonal elements equal to inverse variances).
+#'     \item `prec.logy` -- a vector of population precisions (inverse
+#'     variances), one per antigen/isotype combination.
+#'   }}
+#'   \item{priors}{a [list] summarizing the input priors used in the model,
+#'   with the following elements:
+#'   \itemize{
+#'     \item `mu_hyp_param` -- prior means for y0, y1, t1, shape, and alpha.
+#'     \item `prec_hyp_param` -- precision hyperparameters (inverse variances).
+#'     \item `omega_param` -- Wishart hyperprior diagonal entries.
+#'     \item `wishdf` -- degrees of freedom for the Wishart distribution.
+#'     \item `prec_logy_hyp_param` -- log-scale precision hyperparameters.
+#'   }}
+#'   \item{fitted_residuals}{a [data.frame] containing fitted values and
+#'   residuals for all observations, with columns:
+#'   \itemize{
+#'     \item `Subject` -- subject identifier.
+#'     \item `Iso_type` -- antigen-isotype combination.
+#'     \item `t` -- time since infection.
+#'     \item `fitted` -- fitted value calculated from posterior parameter
+#'     estimates.
+#'     \item `residual` -- residual (observed minus fitted).
+#'   }}
+#'   \item{jags.post}{(optional) a [list] of raw [runjags::run.jags()] output
+#'   objects, one per stratification level. Included when
+#'   `with_post = TRUE` in [run_mod()]. These objects can be large.}
+#' }
+#'
+#' @section Construction:
+#'
+#' `sr_model` objects are created by [run_mod()] and should not normally
+#' be constructed directly.
+#'
+#' @section Inheritance:
+#'
+#' The class hierarchy is
+#' `sr_model` > `tbl_df` > `tbl` > `data.frame`,
+#' so standard [dplyr::dplyr-package] and [tibble::tibble-package] operations
+#' work on `sr_model` objects.
+#'
+#' @seealso
+#' * [run_mod()] -- the constructor function.
+#' * [post_summ()] -- posterior summary table.
+#' * [plot_predicted_curve()] -- predicted antibody response curves.
+#' * [plot_jags_trace()] -- MCMC trace plots.
+#' * [plot_jags_dens()] -- posterior density plots.
+#' * [plot_jags_Rhat()] -- Rhat diagnostic plots.
+#' * [plot_jags_effect()] -- effect size plots.
+#'
+#' @name sr_model-class
+#' @aliases sr_model
+NULL
diff --git a/R/use_att_names.R b/R/use_att_names.R
index b72128587..02a40618c 100644
--- a/R/use_att_names.R
+++ b/R/use_att_names.R
@@ -2,7 +2,7 @@
 #' @description
 #'  `use_att_names` takes prepared longitudinal data for antibody kinetic
 #'  modeling and names columns using attribute values to allow merging
-#'  with a modeled [run_mod()] output [dplyr::tbl_df]. The column names include
+#'  with a modeled [run_mod()] output [tibble::tbl_df]. The column names include
 #'  `Subject`, `Iso_type`, `t`, and `result`. 
 #' @param data A [data.frame] raw longitudinal data that has been
 #' prepared for antibody kinetic modeling using [as_case_data()].
diff --git a/inst/WORDLIST b/inst/WORDLIST
index 8ea3768d3..a0716aa22 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -43,6 +43,7 @@ onwards
 params
 pkgdown
 prec
+precisions
 preinstalling
 rhat
 seroconversion
diff --git a/man/nepal_sees_jags_output.Rd b/man/nepal_sees_jags_output.Rd
index 2bd139153..8fdc71a75 100644
--- a/man/nepal_sees_jags_output.Rd
+++ b/man/nepal_sees_jags_output.Rd
@@ -5,7 +5,8 @@
 \alias{nepal_sees_jags_output}
 \title{SEES Typhoid run_mod jags output}
 \format{
-An S3 object of class \code{sr_model}: A \link[dplyr:tbl_df]{dplyr::tbl_df} that contains the
+An S3 object of class \code{sr_model}:
+A \link[tibble:tbl_df-class]{tibble::tbl_df} that contains the
 posterior predictive distribution of the person-specific parameters for a
 "new person" with no observed data (\code{Subject = "newperson"}) and posterior
 distributions of the person-specific parameters for two arbitrarily-chosen
diff --git a/man/plot_predicted_curve.Rd b/man/plot_predicted_curve.Rd
index 7e2fabde6..194ba11f4 100644
--- a/man/plot_predicted_curve.Rd
+++ b/man/plot_predicted_curve.Rd
@@ -31,7 +31,7 @@ samples from the posterior distribution of the model parameters.}
 \item{antigen_iso}{The antigen isotype to plot; for example, "HlyE_IgA" or
 "HlyE_IgG".}
 
-\item{dataset}{(Optional) A \link[dplyr:tbl_df]{dplyr::tbl_df} with observed antibody response
+\item{dataset}{(Optional) A \link[tibble:tbl_df-class]{tibble::tbl_df} with observed antibody response
 data.
 Must contain:
 \itemize{
diff --git a/man/run_mod.Rd b/man/run_mod.Rd
index 08f914275..a3aec9cd6 100644
--- a/man/run_mod.Rd
+++ b/man/run_mod.Rd
@@ -93,7 +93,7 @@ If specified, must be 2 values long:
   }}
 }
 \value{
-An \code{sr_model} class object: a subclass of \link[dplyr:tbl_df]{dplyr::tbl_df} that
+An \code{sr_model} class object: a subclass of \link[tibble:tbl_df-class]{tibble::tbl_df} that
 contains MCMC samples from the joint posterior distribution of the model
 parameters, conditional on the provided input \code{data},
 including the following:
diff --git a/man/sr_model-class.Rd b/man/sr_model-class.Rd
new file mode 100644
index 000000000..dec36f578
--- /dev/null
+++ b/man/sr_model-class.Rd
@@ -0,0 +1,124 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/sr_model-class.R
+\name{sr_model-class}
+\alias{sr_model-class}
+\alias{sr_model}
+\title{\code{sr_model} class}
+\description{
+An S3 class representing the output of a Bayesian MCMC model
+fitted by \code{\link[=run_mod]{run_mod()}}. The \code{sr_model} object is a subclass
+of \link[tibble:tbl_df-class]{tibble::tbl_df} containing MCMC samples from the joint posterior
+distribution of host-specific antibody kinetic parameters,
+conditional on the provided input data.
+
+Each row represents one posterior draw for one parameter, one
+antigen-isotype combination, one subject, and one stratification level.
+}
+\section{Data columns}{
+
+
+\describe{
+\item{Iteration}{\link{integer} MCMC sampling iteration index.}
+\item{Chain}{\link{integer} MCMC chain index (between 1 and the number of
+chains specified in \code{\link[=run_mod]{run_mod()}}).}
+\item{Parameter}{\link{character} name of the antibody dynamic curve parameter.
+One of:
+\itemize{
+\item \code{y0} -- baseline antibody concentration
+\item \code{y1} -- peak antibody concentration
+\item \code{t1} -- time to peak
+\item \code{shape} -- shape parameter
+\item \code{alpha} -- decay rate
+}}
+\item{Iso_type}{\link{character} antibody/antigen isotype combination being
+evaluated (e.g., \code{"HlyE_IgA"}, \code{"HlyE_IgG"}).}
+\item{Stratification}{\link{character} the level of the stratification variable
+used when fitting the model, or \code{"None"} if no stratification was
+specified.}
+\item{Subject}{\link{character} identifier of the subject. Includes observed
+subjects as well as \code{"newperson"}, which represents the posterior
+predictive distribution for a hypothetical new individual with no observed
+data.}
+\item{value}{\link{numeric} posterior sample value of the parameter.}
+}
+}
+
+\section{Attributes}{
+
+
+In addition to the standard \link[tibble:tbl_df-class]{tibble::tbl_df} attributes (\code{names},
+\code{row.names}, \code{class}), an \code{sr_model} object carries the following
+custom attributes:
+
+\describe{
+\item{nChains}{\link{integer} number of MCMC chains run.}
+\item{nParameters}{\link{integer} number of parameters estimated in the model.}
+\item{nIterations}{\link{integer} total number of MCMC iterations specified.}
+\item{nBurnin}{\link{integer} number of burn-in iterations discarded before
+sampling.}
+\item{nThin}{\link{integer} thinning interval (ratio of total iterations to
+retained samples, i.e., \code{niter / nmc}).}
+\item{population_params}{(optional) a \link[tibble:tbl_df-class]{tibble::tbl_df} of modeled
+population-level parameters, included when \code{with_pop_params = TRUE} in
+\code{\link[=run_mod]{run_mod()}}. Indexed by \code{Iteration}, \code{Chain}, \code{Parameter}, \code{Iso_type},
+and \code{Stratification}. Contains the following population parameters:
+\itemize{
+\item \code{mu.par} -- the population means of the host-specific model
+parameters (on logarithmic scales).
+\item \code{prec.par} -- the population precision matrix of the
+hyperparameters (with diagonal elements equal to inverse variances).
+\item \code{prec.logy} -- a vector of population precisions (inverse
+variances), one per antigen/isotype combination.
+}}
+\item{priors}{a \link{list} summarizing the input priors used in the model,
+with the following elements:
+\itemize{
+\item \code{mu_hyp_param} -- prior means for y0, y1, t1, shape, and alpha.
+\item \code{prec_hyp_param} -- precision hyperparameters (inverse variances).
+\item \code{omega_param} -- Wishart hyperprior diagonal entries.
+\item \code{wishdf} -- degrees of freedom for the Wishart distribution.
+\item \code{prec_logy_hyp_param} -- log-scale precision hyperparameters.
+}}
+\item{fitted_residuals}{a \link{data.frame} containing fitted values and
+residuals for all observations, with columns:
+\itemize{
+\item \code{Subject} -- subject identifier.
+\item \code{Iso_type} -- antigen-isotype combination.
+\item \code{t} -- time since infection.
+\item \code{fitted} -- fitted value calculated from posterior parameter
+estimates.
+\item \code{residual} -- residual (observed minus fitted).
+}}
+\item{jags.post}{(optional) a \link{list} of raw \code{\link[runjags:run.jags]{runjags::run.jags()}} output
+objects, one per stratification level. Included when
+\code{with_post = TRUE} in \code{\link[=run_mod]{run_mod()}}. These objects can be large.}
+}
+}
+
+\section{Construction}{
+
+
+\code{sr_model} objects are created by \code{\link[=run_mod]{run_mod()}} and should not normally
+be constructed directly.
+}
+
+\section{Inheritance}{
+
+
+The class hierarchy is
+\code{sr_model} > \code{tbl_df} > \code{tbl} > \code{data.frame},
+so standard \link[dplyr:dplyr-package]{dplyr::dplyr-package} and \link[tibble:tibble-package]{tibble::tibble-package} operations
+work on \code{sr_model} objects.
+}
+
+\seealso{
+\itemize{
+\item \code{\link[=run_mod]{run_mod()}} -- the constructor function.
+\item \code{\link[=post_summ]{post_summ()}} -- posterior summary table.
+\item \code{\link[=plot_predicted_curve]{plot_predicted_curve()}} -- predicted antibody response curves.
+\item \code{\link[=plot_jags_trace]{plot_jags_trace()}} -- MCMC trace plots.
+\item \code{\link[=plot_jags_dens]{plot_jags_dens()}} -- posterior density plots.
+\item \code{\link[=plot_jags_Rhat]{plot_jags_Rhat()}} -- Rhat diagnostic plots.
+\item \code{\link[=plot_jags_effect]{plot_jags_effect()}} -- effect size plots.
+}
+}
diff --git a/man/use_att_names.Rd b/man/use_att_names.Rd
index f43fcef0c..144aa5a81 100644
--- a/man/use_att_names.Rd
+++ b/man/use_att_names.Rd
@@ -16,7 +16,7 @@ The input \link{data.frame} with columns named after attributes.
 \description{
 \code{use_att_names} takes prepared longitudinal data for antibody kinetic
 modeling and names columns using attribute values to allow merging
-with a modeled \code{\link[=run_mod]{run_mod()}} output \link[dplyr:tbl_df]{dplyr::tbl_df}. The column names include
+with a modeled \code{\link[=run_mod]{run_mod()}} output \link[tibble:tbl_df-class]{tibble::tbl_df}. The column names include
 \code{Subject}, \code{Iso_type}, \code{t}, and \code{result}.
 }
 \keyword{internal}
diff --git a/pkgdown/_pkgdown.yml b/pkgdown/_pkgdown.yml
index 61c982025..f8e9528eb 100644
--- a/pkgdown/_pkgdown.yml
+++ b/pkgdown/_pkgdown.yml
@@ -29,6 +29,7 @@ reference:
 - title: Model seroreponse
   contents:
   - run_mod
+  - sr_model-class
 - title: Model diagnostics
   contents:
   - plot_jags_dens