From ba3da4fbb05c787655350b987416f60d35de019d Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Thu, 19 Oct 2023 13:29:31 -0400
Subject: [PATCH 01/10] in progress

---
 vignettes/tutorial.Rmd | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index 51315eea..36390f38 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -5,6 +5,7 @@ date: "`r Sys.Date()`"
 output: 
   rmarkdown::html_vignette:
     toc: yes
+    number-sections: yes
 header-includes: "\\DeclareUnicodeCharacter{2010}{-}"
 bibliography: ../references.bib
 fontsize: 11pt
@@ -82,9 +83,9 @@ b) time to reach peak antibody concentration,
 c) magnitude of the peak concentration, and 
 d) antibody decay parameters describing the time course (shape and rate) of antibody decay. 
 
-A model description that is used for the serocalculator is described in [@Simonsen_2009; @Teunis_2012]. An alternative 
+A model description that is used for the serocalculator is described in @Simonsen_2009 and @Teunis_2012. An alternative 
 model, simplified but with improved interpretation of the underlying biological mechanisms, is given 
-in [@de_Graaf_2014] and further improved in [@Teunis_2016]. 
+in @de_Graaf_2014 and further improved in @Teunis_2016. 
 
 The current model assumes that upon exposure to an initial inoculum, pathogen concentrations 
 increase exponentially. Presence of pathogens (antigen presented to the immune system) signals an 
@@ -94,13 +95,13 @@ causes inactivation or die–off of pathogens, with a rate proportional to the s
 concentration. Ultimately, when all pathogens are removed, infection is over and the promotion of 
 antibody production stops. Then the decay phase starts, and serum antibody concentrations decrease. 
 Antibody decay in the serum compartment may start fast and slow down later, resulting in 
-non–exponential decay. In [@Teunis_2016] this is modelled using a shape parameter, allowing gradual adjustment 
+non–exponential decay. In @Teunis_2016 this is modelled using a shape parameter, allowing gradual adjustment 
 between exponential (log–linear) and strongly non–exponential decay.
 
 ## Heterogenity
 
 The five parameters describing the seroresponse (in round brackets names of corresponding 
-parameters used in the package, see [section 3.2.2](#longParams) for details): baseline antibody 
+parameters used in the package, see @sec-longParams for details): baseline antibody 
 concentration (`y0` and `yb`), time to peak (`t1`), peak antibody concentration (`y1`), decay rate 
 (`alpha`) and shape factor of the decay curve (`r`) are not fixed numbers. In a population of 
 subjects, individuals each have their own seroresponse, different from those of other subjects. 
@@ -298,7 +299,7 @@ Then it can be loaded into R like this:
 serologyData <- read.csv(file = "C:\\cross-sectional-data.csv")
 ```
 
-### Specifying longitudinal response parameters {#longParams}
+### Specifying longitudinal response parameters {#sec-longParams}
 
 The longitudinal response parameters set consists of the following items:
 

From cffc82bb6ba6d5af89f5ac78402ee23d5ef325c8 Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Thu, 19 Oct 2023 13:34:26 -0400
Subject: [PATCH 02/10] add numbers

---
 vignettes/tutorial.Rmd | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index 36390f38..64e2dbd7 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -3,9 +3,9 @@ title: "Serocalculator package tutorial"
 author: "UC Davis SeroEpidemiology Group"
 date: "`r Sys.Date()`"
 output: 
-  rmarkdown::html_vignette:
-    toc: yes
-    number-sections: yes
+  bookdown::html_document2:
+      base_format: rmarkdown::html_vignette
+      toc: true
 header-includes: "\\DeclareUnicodeCharacter{2010}{-}"
 bibliography: ../references.bib
 fontsize: 11pt

From b3695de3e501789d3b0a98d3613d01238e48e958 Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Thu, 19 Oct 2023 13:47:26 -0400
Subject: [PATCH 03/10] fixed

---
 vignettes/tutorial.Rmd | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index cd0aa8be..d16e9351 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -2,9 +2,10 @@
 title: "Serocalculator package tutorial"
 author: "UC Davis SeroEpidemiology Group"
 date: "`r Sys.Date()`"
+output:
   bookdown::html_document2:
-      base_format: rmarkdown::html_vignette
-      toc: true
+    base_format: rmarkdown::html_vignette
+    toc: true
 header-includes: "\\DeclareUnicodeCharacter{2010}{-}"
 bibliography: ../references.bib
 fontsize: 11pt
@@ -100,7 +101,7 @@ between exponential (log–linear) and strongly non–exponential decay.
 ## Heterogenity
 
 The five parameters describing the seroresponse (in round brackets names of corresponding 
-parameters used in the package, see @sec-longParams for details): baseline antibody 
+parameters used in the package, see Section \@ref(longParams) for details): baseline antibody 
 concentration (`y0` and `yb`), time to peak (`t1`), peak antibody concentration (`y1`), decay rate 
 (`alpha`) and shape factor of the decay curve (`r`) are not fixed numbers. In a population of 
 subjects, individuals each have their own seroresponse, different from those of other subjects. 
@@ -293,7 +294,7 @@ Then it can be loaded into R like this:
 serologyData <- read.csv(file = "C:\\cross-sectional-data.csv")
 ```
 
-### Specifying longitudinal response parameters {#sec-longParams}
+### Specifying longitudinal response parameters {#longParams}
 
 The longitudinal response parameters set consists of the following items:
 

From 21b8bed2ac3be922daff63efc48302d4ce4eb351 Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Thu, 19 Oct 2023 14:13:11 -0400
Subject: [PATCH 04/10] in progress

---
 references.bib            |  4 ++--
 vignettes/.gitignore      |  1 +
 vignettes/methodology.Rmd |  6 +++---
 vignettes/tutorial.Rmd    | 30 +++++++++++++++---------------
 4 files changed, 21 insertions(+), 20 deletions(-)

diff --git a/references.bib b/references.bib
index 187a0805..e0133adf 100644
--- a/references.bib
+++ b/references.bib
@@ -20,7 +20,7 @@ @article{Simonsen_2009
 	volume = {28},
 	number = {14},
 	pages = {1882--1895},
-	author = {J. Simonsen and K. M{\o}lbak and G. Falkenhorst and K. A. Krogfelt and A. Linneberg and P. F. M. Teunis},
+	author = {J. Simonsen and K. M{\o}lbak and G. Falkenhorst and K. A. Krogfelt and A. Linneberg and P.F.M. Teunis},
 	title = {Estimation of incidences of infectious diseases based on antibody measurements},
 	journal = {Statistics in Medicine}
 }
@@ -34,7 +34,7 @@ @article{Teunis_2012
 	volume = {31},
 	number = {20},
 	pages = {2240--2248},
-	author = {PFM Teunis and JCH van Eijkeren and CW Ang and YTHP van Duynhoven and JB Simonsen and MA Strid and W van Pelt},
+	author = {P.F.M. Teunis and JCH van Eijkeren and CW Ang and YTHP van Duynhoven and JB Simonsen and MA Strid and W van Pelt},
 	title = {Biomarker dynamics: estimating infection rates from serological data},
 	journal = {Statistics in Medicine}
 }
diff --git a/vignettes/.gitignore b/vignettes/.gitignore
index 097b2416..01b6080a 100644
--- a/vignettes/.gitignore
+++ b/vignettes/.gitignore
@@ -1,2 +1,3 @@
 *.html
 *.R
+methodology.log
diff --git a/vignettes/methodology.Rmd b/vignettes/methodology.Rmd
index b77b59a0..ff2dca0e 100644
--- a/vignettes/methodology.Rmd
+++ b/vignettes/methodology.Rmd
@@ -3,10 +3,10 @@ title: "Serocalculator package methodology"
 author: "European Centre for Disease Prevention and Control (ECDC)"
 date: '`r Sys.Date()`'
 output: 
-  rmarkdown::html_vignette:
-    toc: yes
   pdf_document:
     toc: yes
+  rmarkdown::html_vignette:
+    toc: yes
 header-includes:
 - \usepackage{subfigure}
   \DeclareUnicodeCharacter{2010}{-}
@@ -141,8 +141,8 @@ references:
 fontsize: 11pt
 vignette: >
   %\VignetteIndexEntry{Serocalculator package methodology}
-  %\VignetteEngine{knitr::rmarkdown}
   %\VignetteEncoding{UTF-8}
+  %\VignetteEngine{knitr::rmarkdown}
 ---
 
 <script type="text/x-mathjax-config">
diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index d16e9351..33d61220 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -144,17 +144,17 @@ source, and runs on any modern computer operating system.
 The package contains longitudinal models for seroincidence calculations. Four model variants are 
 possible, depending on whether seroconversion is instantaneous ($t_{1} = 0$) or not ($t_{1} > 0$), 
 and whether decay is exponential ($r = 1$) or proceeds as a power function ($r > 1$). Power function 
-decay allows for rapid inital decay followed by a sustained period of very slow decay [@4]. 
+decay allows for rapid inital decay followed by a sustained period of very slow decay [@Teunis_2016]. 
 Available model variants are described in Table \@ref(tab:model-variants) and Table \@ref(tab:model-variants-available).
 
 Table: (\#tab:model-variants) Model variants 
 
 |Model | Time to<br>Seroconversion<br>($t_{1}$) | Decay<br>parameter<br>($r$) |
-|-------|-------|-----|
-| 1     | 0     | 1   |
-| 2     | 0     | > 1 |
-| 3     | > 0   | 1   |
-| 4     | > 0   | > 1 |
+|:-:|:---:|:---:|
+| 1 | = 0 | = 1 |
+| 2 | = 0 | > 1 |
+| 3 | > 0 | = 1 |
+| 4 | > 0 | > 1 |
 
 Table: (\#tab:model-variants-available) Models variants available by pathogen, antibody, and units:
 
@@ -180,25 +180,23 @@ This section provides step-by-step directions on the usage of the *serocalculato
 ## Loading the package
 
 Functionality of the *serocalculator* package is made available to the end user only once the library 
-is loaded into the current workspace. Assuming the package is installed already (covered in 
-[installation.pdf](installation.pdf)) loading is achieved by running the following command in the R 
-console (bear in mind that the text after character `#` is only a comment):
+is loaded into the current workspace. Assuming the package is installed already^[covered in 
+`vignette("installation", package = "serocalculator")`], loading is achieved by running the following command in the R 
+console^[lines of code beginning with the symbol `#` are comments, which do not do anything]:
 
 ```{r}
 # Load package "seroincidence"
 library(serocalculator)
-library(dplyr)
 ```
 
-At this moment all functions required to run the seroincidence calculation are made available. It 
-can be checked by running:
+At this moment all functions required to run the seroincidence calculation are made available. You can check that the package loaded correctly by running:
 
 ```{r, eval=FALSE}
 # List all objects (functions and data) exposed by package "serocalculator".
 ls("package:serocalculator")
 ```
 
-Here is the resulting output:
+If the package is correctly installed and loaded, the output of `ls("package:serocalculator")` will be:
 
 ```{r, echo=FALSE}
 ls("package:serocalculator")
@@ -243,8 +241,10 @@ can be referenced right away. Here is a small exempt from this data set:
 head(campylobacterSimMediumData, 3)
 ```
 
-Let us create the serology data `serologyData` based on this data set:
-```{r}
+Let us create the serology data `serologyData` based on this data set, using the `mutate()` function from the `dplyr` package^[you may need to install `dplyr`, e.g. with `install.packages("dplyr")`]:
+
+```{r, message=FALSE}
+library(dplyr)
 # Assign data.frame "campylobacterDelftData" to object named "serologyData".
 serologyData <- campylobacterSimMediumData |> 
   mutate(AgeCat = cut(Age, 15, labels = FALSE))

From 3f2f79389bac33b5ace7d9e9ffe22436f731dbc8 Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Thu, 19 Oct 2023 15:12:50 -0400
Subject: [PATCH 05/10] moved references file, extracted refs from
 methodology.rmd

---
 DESCRIPTION               |   2 +-
 references.bib            |  68 -----------------
 vignettes/methodology.Rmd | 156 ++++----------------------------------
 vignettes/references.bib  | 105 +++++++++++++++++++++++++
 vignettes/tutorial.Rmd    |   2 +-
 5 files changed, 121 insertions(+), 212 deletions(-)
 delete mode 100644 references.bib
 create mode 100644 vignettes/references.bib

diff --git a/DESCRIPTION b/DESCRIPTION
index dd5aed41..4383c5f8 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -31,7 +31,7 @@ VignetteBuilder: knitr
 LazyData: true
 Encoding: UTF-8
 URL: https://github.com/UCD-SERG/serocalculator, https://ucd-serg.github.io/serocalculator/
-RoxygenNote: 7.2.3
+RoxygenNote: 7.2.3.9000
 NeedsCompilation: no
 LinkingTo: 
     Rcpp
diff --git a/references.bib b/references.bib
deleted file mode 100644
index e0133adf..00000000
--- a/references.bib
+++ /dev/null
@@ -1,68 +0,0 @@
-@article{de_Graaf_2014,
-	doi = {10.1016/j.epidem.2014.08.002},
-	url = {https://doi.org/10.1016%2Fj.epidem.2014.08.002},
-	year = 2014,
-	month = {dec},
-	publisher = {Elsevier {BV}},
-	volume = {9},
-	pages = {1--7},
-	author = {W.F. de Graaf and M.E.E. Kretzschmar and P.F.M. Teunis and O. Diekmann},
-	title = {A two-phase within-host model for immune response and its application to serological profiles of pertussis},
-	journal = {Epidemics}
-}
-
-@article{Simonsen_2009,
-	doi = {10.1002/sim.3592},
-	url = {https://doi.org/10.1002%2Fsim.3592},
-	year = 2009,
-	month = {jun},
-	publisher = {Wiley},
-	volume = {28},
-	number = {14},
-	pages = {1882--1895},
-	author = {J. Simonsen and K. M{\o}lbak and G. Falkenhorst and K. A. Krogfelt and A. Linneberg and P.F.M. Teunis},
-	title = {Estimation of incidences of infectious diseases based on antibody measurements},
-	journal = {Statistics in Medicine}
-}
-
-@article{Teunis_2012,
-	doi = {10.1002/sim.5322},
-	url = {https://doi.org/10.1002%2Fsim.5322},
-	year = 2012,
-	month = {mar},
-	publisher = {Wiley},
-	volume = {31},
-	number = {20},
-	pages = {2240--2248},
-	author = {P.F.M. Teunis and JCH van Eijkeren and CW Ang and YTHP van Duynhoven and JB Simonsen and MA Strid and W van Pelt},
-	title = {Biomarker dynamics: estimating infection rates from serological data},
-	journal = {Statistics in Medicine}
-}
-
-@article{Teunis_2016,
-	doi = {10.1016/j.epidem.2016.04.001},
-	url = {https://doi.org/10.1016%2Fj.epidem.2016.04.001},
-	year = 2016,
-	month = {sep},
-	publisher = {Elsevier {BV}},
-	volume = {16},
-	pages = {33--39},
-	author = {P.F.M. Teunis and J.C.H. van Eijkeren and W.F. de Graaf and A. Bona{\v{c}}i{\'{c}} Marinovi{\'{c}} and M.E.E. Kretzschmar},
-	title = {Linking the seroresponse to infection to within-host heterogeneity in antibody production},
-	journal = {Epidemics}
-}
-
-@article{Strid_2001,
-	doi = {10.1128/cdli.8.2.314-319.2001},
-	url = {https://doi.org/10.1128%2Fcdli.8.2.314-319.2001},
-	year = 2001,
-	month = {mar},
-	publisher = {American Society for Microbiology},
-	volume = {8},
-	number = {2},
-	pages = {314--319},
-	author = {Mette Aagaard Strid and J{\o}rgen Engberg and Lena Brandt Larsen and Kamilla Begtrup and K{\aa}re M{\o}lbak and Karen Angeliki Krogfelt},
-	title = {Antibody responses to Campylobacter infections determined by an enzyme-linked immunosorbent assay: 2-year follow-up study of 210 patients},
-	journal = {Clinical Diagnostic Laboratory Immunology}
-}
-
diff --git a/vignettes/methodology.Rmd b/vignettes/methodology.Rmd
index ff2dca0e..6c9b97f1 100644
--- a/vignettes/methodology.Rmd
+++ b/vignettes/methodology.Rmd
@@ -3,141 +3,13 @@ title: "Serocalculator package methodology"
 author: "European Centre for Disease Prevention and Control (ECDC)"
 date: '`r Sys.Date()`'
 output: 
-  pdf_document:
-    toc: yes
-  rmarkdown::html_vignette:
-    toc: yes
+  bookdown::html_document2:
+    base_format: rmarkdown::html_vignette
+    toc: true
 header-includes:
 - \usepackage{subfigure}
   \DeclareUnicodeCharacter{2010}{-}
-references:
-- id: teunis_etal12_biomarker
-  DOI: 10.1002/sim.5322
-  author:
-  - family: Teunis
-    given: P. F. M.
-  - family: van Eijkeren
-    given: J. C.
-  - family: Ang
-    given: C. W.
-  - family: van Duynhoven
-    given: Y. T.
-  - family: Simonsen
-    given: J. B.
-  - family: Strid
-    given: M. A.
-  - family: van Pelt
-    given: W.
-  container-title: Statistics in Medicine
-  issue: 20
-  issued:
-    month: 9
-    year: 2012
-  page: 2240-2248
-  title: 'Biomarker dynamics: estimating infection rates from serological data'
-  type: article-journal
-  volume: 31
-- id: degraaf_etal14wh
-  author:
-  - family: de Graaf
-    given: W. F.
-  - family: Kretzschmar 
-    given: M. E. E.
-  - family: Teunis
-    given: P. F. M.
-  - family: Diekmann
-    given: O.
-  container-title: Epidemics
-  DOI: 10.1016/j.epidem.2014.08.002
-  issued:
-    month: 12
-    year: 2014
-  page: 1-7
-  title: 'A two-phase within-host model for immune response and its application to serological profiles of pertussis'
-  type: article-journal
-  volume: 9
-- id: teunis_etal16withinhost
-  author:
-  - family: Teunis
-    given: P. F. M.
-  - family: van Eijkeren
-    given: J. C.
-  - family: de Graaf
-    given: W. F.
-  - family: Bonačić Marinović
-    given: A.
-  - family: Kretzschmar 
-    given: M. E. E.    
-  container-title: Epidemics
-  DOI: 10.1016/j.epidem.2016.04.001
-  issued:
-    month: 9
-    year: 2016
-    page: 33-39
-  title: 'Linking the seroresponse to infection to within-host heterogeneity in antibody production'
-  type: article-journal
-  volume: 16  
-- id: satten_etal04
-  author:
-  - family: Satten
-    given: G. A.
-  - family: Kong
-    given: F.
-  - family: Wright
-    given: D. J.
-  - family: Glynn
-    given: S. A.
-  - family: Schreiber 
-    given: G. B.  
-  container-title: Biostatistics
-  DOI: 10.1093/biostatistics/5.1.145
-  issued:
-    month: 1
-    year: 2004
-    page: 145-151
-  title: 'How special is a ‘special’ interval: modeling departure from length‐biased sampling in renewal processes'
-  type: article-journal
-  volume: 5
-  issue: 1
-- id: zelen04
-  author:
-  - family: Zelen
-    given: M.
-  container-title: Lifetime Data Analysis
-  issued:
-    month: 12
-    year: 2004
-    page: 325-334
-  title: 'Forward and backward recurrence times and length biased sampling: age specific models'
-  type: article-journal
-  volume: 10
-  issue: 4
-- id: degreeff_etal12
-  author:
-  - family: de Greeff
-    given: S. C.
-  - family: Teunis
-    given: P. F. M.
-  - family: de Melker
-    given: H. E.
-  - family: Mooi
-    given: F. R.
-  - family: Notermans
-    given: D. W.
-  - family: Elvers
-    given: B.
-  - family: Schellekens
-    given: J. F. P.
-  container-title: Clinical and Vaccine Immunology
-  DOI: 10.1128/CVI.00229-12
-  issued:
-    month: 9
-    year: 2012
-    page: 1452-1456
-  title: 'Two-Component Cluster Analysis of a Large Serodiagnostic Database for Specificity of Increases of IgG Antibodies against Pertussis Toxin in Paired Serum Samples and of Absolute Values in Single Serum Samples'
-  type: article-journal
-  volume: 19
-  issue: 9
+bibliography: references.bib
 fontsize: 11pt
 vignette: >
   %\VignetteIndexEntry{Serocalculator package methodology}
@@ -156,17 +28,17 @@ MathJax.Hub.Config({
 # Introduction
 
 The revised seroincidence calculator package provides three refinements to the method for 
-calculating seroincidence published earlier [@teunis_etal12_biomarker] and implemented in R package
+calculating seroincidence published earlier [@Teunis_2012] and implemented in R package
 **seroincidence**, versions 1.x: (1) inclusion of infection episode with rising antibody levels, (2) 
 non--exponential decay of serum antibodies after infection, and (3) age--dependent correction for 
 subjects who have never seroconverted. It is important to note that, although the implemented 
-methods use a specific parametric model, as proposed in [@degraaf_etal14wh] and augmented in 
-[@teunis_etal16withinhost], the methods used to calculate the likelihood function allow 
+methods use a specific parametric model, as proposed in [@de_Graaf_2014] and augmented in 
+[@Teunis_2016], the methods used to calculate the likelihood function allow 
 seroresponses of arbitrary shape.
 
 # 1. A simple model for the seroresponse
 
-The current version of the serocalculator package uses the model of [@teunis_etal16withinhost] for 
+The current version of the serocalculator package uses the model of [@Teunis_2016] for 
 the shape of the seroresponse:
 $$
 \begin{array}{l@{\qquad}l}
@@ -207,7 +79,7 @@ decay is restored.
 
 Considering the (fundamental) uniform distribution $u_{f}$ of sampling within a given interval, the 
 interval length distribution $p(\Delta t)$ and the distribution of (cross--sectionally) sampled 
-interval length [@teunis_etal12_biomarker]
+interval length [@Teunis_2012]
 $$
 q(\Delta t) = \frac{p(\Delta t)\cdot\Delta t}{\overline{\Delta t_{p}}}
 $$
@@ -224,11 +96,11 @@ u(\tau) & = \int_{\Delta t=0}^{\infty} u_{f}(\tau;\Delta t)\cdot q(\Delta t)\tex
 
 # 3. Incidence of seroconversions
 
-To calculate the incidence of seroconversions, as in [@teunis_etal12_biomarker], the distribution 
+To calculate the incidence of seroconversions, as in [@Teunis_2012], the distribution 
 $p(\Delta t)$ of intervals $\Delta t$ between seroconversions, is important. Assuming any subject is 
 sampled completely at random during their intervals between seroconversions, and accounting for 
 interval length bias [@satten_etal04; @zelen04], the distribution of backward recurrence times 
-$\tau$ can be written as [@teunis_etal12_biomarker]
+$\tau$ can be written as [@Teunis_2012]
 $$
 u(\tau) = \frac{1}{\overline{\Delta t}} \int_{\tau=0}^{\infty}p(\Delta t)\text{d}\Delta t 
         = \frac{1-P(\Delta t)}{\overline{\Delta t}}
@@ -286,7 +158,7 @@ So that
 when $[y_{0} \le y < y_{1}]$ there are two contributions to the density, one from the rising and one 
 from the decaying branch of the antibody response.
 
-If, as assumed before [@teunis_etal12_biomarker], intervals between incident infections are 
+If, as assumed before [@Teunis_2012], intervals between incident infections are 
 generated by a process with Gamma probability density, $\overline{\Delta t} = (m+1)/\lambda$. The 
 cumulative distribution function for $\tau$ is
 \begin{equation}\label{pm_cumul}
@@ -320,8 +192,8 @@ seroresponse to the density of $y$.
 The within--host parameters $\boldsymbol{\theta} = (y_{0}, y_{1}, t_{1}, \nu, r)$ vary among 
 responses of individual subjects. Heterogeneity in these parameters may be described by their joint 
 distribution, which can be used to calculate the marginal distribution $\rho(y)$ 
-[@teunis_etal12_biomarker]. Since a Monte Carlo sample of the posterior joint distribution is 
-available from the longitudinal model [@teunis_etal16withinhost] the marginal distribution of 
+[@Teunis_2012]. Since a Monte Carlo sample of the posterior joint distribution is 
+available from the longitudinal model [@Teunis_2016] the marginal distribution of 
 $\rho(y)$ may be approximated by the sum
 \begin{equation}\label{rho_numsum}
 \rho(y) = \frac{1}{N}\sum_{n=1}^{N} \rho_{+}(y\vert \lambda, m, \boldsymbol{\theta}_{n}) + 
diff --git a/vignettes/references.bib b/vignettes/references.bib
new file mode 100644
index 00000000..438f7cd5
--- /dev/null
+++ b/vignettes/references.bib
@@ -0,0 +1,105 @@
+@article{de_Graaf_2014,
+	doi = {10.1016/j.epidem.2014.08.002},
+	url = {https://doi.org/10.1016%2Fj.epidem.2014.08.002},
+	year = 2014,
+	month = {dec},
+	publisher = {Elsevier {BV}},
+	volume = {9},
+	pages = {1--7},
+	author = {W.F. de Graaf and M.E.E. Kretzschmar and P.F.M. Teunis and O. Diekmann},
+	title = {A two-phase within-host model for immune response and its application to serological profiles of pertussis},
+	journal = {Epidemics}
+}
+
+@article{Simonsen_2009,
+	doi = {10.1002/sim.3592},
+	url = {https://doi.org/10.1002%2Fsim.3592},
+	year = 2009,
+	month = {jun},
+	publisher = {Wiley},
+	volume = {28},
+	number = {14},
+	pages = {1882--1895},
+	author = {J. Simonsen and K. M{\o}lbak and G. Falkenhorst and K. A. Krogfelt and A. Linneberg and P.F.M. Teunis},
+	title = {Estimation of incidences of infectious diseases based on antibody measurements},
+	journal = {Statistics in Medicine}
+}
+
+@article{Teunis_2012,
+	doi = {10.1002/sim.5322},
+	url = {https://doi.org/10.1002%2Fsim.5322},
+	year = 2012,
+	month = {mar},
+	publisher = {Wiley},
+	volume = {31},
+	number = {20},
+	pages = {2240--2248},
+	author = {P.F.M. Teunis and JCH van Eijkeren and CW Ang and YTHP van Duynhoven and JB Simonsen and MA Strid and W van Pelt},
+	title = {Biomarker dynamics: estimating infection rates from serological data},
+	journal = {Statistics in Medicine}
+}
+
+@article{Teunis_2016,
+	doi = {10.1016/j.epidem.2016.04.001},
+	url = {https://doi.org/10.1016%2Fj.epidem.2016.04.001},
+	year = 2016,
+	month = {sep},
+	publisher = {Elsevier {BV}},
+	volume = {16},
+	pages = {33--39},
+	author = {P.F.M. Teunis and J.C.H. van Eijkeren and W.F. de Graaf and A. Bona{\v{c}}i{\'{c}} Marinovi{\'{c}} and M.E.E. Kretzschmar},
+	title = {Linking the seroresponse to infection to within-host heterogeneity in antibody production},
+	journal = {Epidemics}
+}
+
+@article{Strid_2001,
+	doi = {10.1128/cdli.8.2.314-319.2001},
+	url = {https://doi.org/10.1128%2Fcdli.8.2.314-319.2001},
+	year = 2001,
+	month = {mar},
+	publisher = {American Society for Microbiology},
+	volume = {8},
+	number = {2},
+	pages = {314--319},
+	author = {Mette Aagaard Strid and J{\o}rgen Engberg and Lena Brandt Larsen and Kamilla Begtrup and K{\aa}re M{\o}lbak and Karen Angeliki Krogfelt},
+	title = {Antibody responses to Campylobacter infections determined by an enzyme-linked immunosorbent assay: 2-year follow-up study of 210 patients},
+	journal = {Clinical Diagnostic Laboratory Immunology}
+}
+
+@article{satten_etal04,
+    author = {Satten, Glen A. and Kong, Fanhui and Wright, David J. and Glynn, Simone A. and Schreiber, George B.},
+    title = "{How special is a ‘special’ interval: modeling departure from length‐biased sampling in renewal processes}",
+    journal = {Biostatistics},
+    volume = {5},
+    number = {1},
+    pages = {145-151},
+    year = {2004},
+    month = {01},
+    abstract = "{Length‐biased sampling occurs in renewal processes when the probability that an interval is selected is proportional to the length of the interval. This can occur when intervals are selected because they contain an event that is independent of the renewal process and occurs with constant hazard. For example, if the times between donations for repeat blood donors are independent and identically distributed, and if the donor seroconverts to HIV (develops antibodies that indicate infection with human immunodeficiency virus), then the interval between the last HIV seronegative and first HIV seropositive test is expected to be longer than that donor's previous time intervals between donations. We develop hypothesis tests to determine if the relationship between the typical and length‐biased intervals is as expected, or if there is departure from length‐biased sampling. We further develop a regression method to determine if there are covariates that explain the departure from length‐biased sampling. Our approach is motivated by the question of whether there is evidence that repeat blood donors who develop antibodies to HIV or other viral infections change their donation pattern in some way because of seroconversion.}",
+    issn = {1465-4644},
+    doi = {10.1093/biostatistics/5.1.145},
+    url = {https://doi.org/10.1093/biostatistics/5.1.145},
+    eprint = {https://academic.oup.com/biostatistics/article-pdf/5/1/145/941872/050145.pdf},
+}
+
+@article{zelen04,
+  title={Forward and backward recurrence times and length biased sampling: age specific models},
+  author={Zelen, Marvin},
+  journal={Lifetime Data Analysis},
+  volume={10},
+  pages={325--334},
+  year={2004},
+  publisher={Springer}
+}
+
+
+@article{degreeff_etal12,
+  title={Two-component cluster analysis of a large serodiagnostic database for specificity of increases of IgG antibodies against pertussis toxin in paired serum samples and of absolute values in single serum samples},
+  author={de Greeff, Sabine C and Teunis, Peter and de Melker, Hester E and Mooi, Frits R and Notermans, Daan W and Elvers, Bert and Schellekens, Joop FP},
+  journal={Clinical and Vaccine Immunology},
+  volume={19},
+  number={9},
+  pages={1452--1456},
+  year={2012},
+  publisher={Am Soc Microbiol}
+}
diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index 33d61220..ca7574fd 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -7,7 +7,7 @@ output:
     base_format: rmarkdown::html_vignette
     toc: true
 header-includes: "\\DeclareUnicodeCharacter{2010}{-}"
-bibliography: ../references.bib
+bibliography: references.bib
 fontsize: 11pt
 vignette: > 
   %\VignetteIndexEntry{Serocalculator package tutorial}    

From 6e31c25ab6a36c86493224b57a8be47b153081b9 Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Tue, 24 Oct 2023 14:25:17 -0400
Subject: [PATCH 06/10] in progress

---
 R/estimateSeroincidence.R |  2 +-
 vignettes/methodology.Rmd |  4 ++--
 vignettes/tutorial.Rmd    | 17 +++++++++++------
 3 files changed, 14 insertions(+), 9 deletions(-)

diff --git a/R/estimateSeroincidence.R b/R/estimateSeroincidence.R
index 1ccfc5de..b38bd097 100644
--- a/R/estimateSeroincidence.R
+++ b/R/estimateSeroincidence.R
@@ -113,7 +113,7 @@ estimateSeroincidence <- function(
                         Antibodies = antibodies,
                         Strata = strata,
                         CensorLimits = censorLimits)
-  class(incidenceData) <- c("seroincidence", "list")
+  class(incidenceData) <- c("seroincidence",  class(incidenceData))
 
   return(incidenceData)
 }
diff --git a/vignettes/methodology.Rmd b/vignettes/methodology.Rmd
index 6c9b97f1..cb383414 100644
--- a/vignettes/methodology.Rmd
+++ b/vignettes/methodology.Rmd
@@ -27,7 +27,7 @@ MathJax.Hub.Config({
 
 # Introduction
 
-The revised seroincidence calculator package provides three refinements to the method for 
+The `serocalculator` package provides three refinements to the method for 
 calculating seroincidence published earlier [@Teunis_2012] and implemented in R package
 **seroincidence**, versions 1.x: (1) inclusion of infection episode with rising antibody levels, (2) 
 non--exponential decay of serum antibodies after infection, and (3) age--dependent correction for 
@@ -38,7 +38,7 @@ seroresponses of arbitrary shape.
 
 # 1. A simple model for the seroresponse
 
-The current version of the serocalculator package uses the model of [@Teunis_2016] for 
+The current version of the serocalculator package uses the model proposed in @Teunis_2016 for 
 the shape of the seroresponse:
 $$
 \begin{array}{l@{\qquad}l}
diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index ca7574fd..923ed891 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -81,7 +81,7 @@ described by means of a set of parameters describing it. These parameters may in
 a) baseline antibody concentration, 
 b) time to reach peak antibody concentration, 
 c) magnitude of the peak concentration, and 
-d) antibody decay parameters describing the time course (shape and rate) of antibody decay. 
+d) antibody decay parameters describing the time course (shape and rate) of antibody decay.
 
 A model description that is used for the serocalculator is described in @Simonsen_2009 and @Teunis_2012. An alternative 
 model, simplified but with improved interpretation of the underlying biological mechanisms, is given 
@@ -98,12 +98,17 @@ Antibody decay in the serum compartment may start fast and slow down later, resu
 non–exponential decay. In @Teunis_2016 this is modelled using a shape parameter, allowing gradual adjustment 
 between exponential (log–linear) and strongly non–exponential decay.
 
-## Heterogenity
+## Heterogeneity
 
-The five parameters describing the seroresponse (in round brackets names of corresponding 
-parameters used in the package, see Section \@ref(longParams) for details): baseline antibody 
-concentration (`y0` and `yb`), time to peak (`t1`), peak antibody concentration (`y1`), decay rate 
-(`alpha`) and shape factor of the decay curve (`r`) are not fixed numbers. In a population of 
+The five parameters describing the seroresponse are:
+
+* baseline antibody concentration (`y0` and `yb`^[the corresponding variable names used in the package are listed in monospace font with gray background; see Section \@ref(longParams) for details])
+* time to peak (`t1`)
+* peak antibody concentration (`y1`)
+* decay rate (`alpha`)
+* shape factor of the decay curve (`r`)
+
+These parameters are not fixed numbers. In a population of 
 subjects, individuals each have their own seroresponse, different from those of other subjects. 
 Therefore, these parameters are provided as a (joint) distribution, describing their variation among 
 individuals in the sampled population. Of course, such a distribution depends on the pathogen, the 

From a124df226d29a8146647b53bb78b9bd490553926 Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Tue, 24 Oct 2023 15:10:07 -0400
Subject: [PATCH 07/10] more

---
 vignettes/tutorial.Rmd | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index 923ed891..b04d409a 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -303,9 +303,9 @@ serologyData <- read.csv(file = "C:\\cross-sectional-data.csv")
 
 The longitudinal response parameters set consists of the following items:
 
-- `y1`: antibody peak level (ELISA units)
+- $y_1$ (`y1`): antibody peak level (ELISA units)
 - `alpha`: antibody decay rate (1/days for the current longitudinal parameter sets)
-- `yb`: baseline antibody level at $t$ approaching infinity ($y(t->inf)$)
+- $y_0$ (`yb`): baseline antibody level at $t$ approaching infinity ($y(t->inf)$)
 - `r`: shape factor of antibody decay
 - `y0`: baseline antibody level at $t=0$ ($y(t=0)$)
 - `mu1`: initial antibody growth rate

From 91d6a99df91b2347d5376d87fe009f1f9010b79c Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Tue, 14 Nov 2023 19:40:50 -0800
Subject: [PATCH 08/10] clean up references

---
 vignettes/references.bib | 12 ------------
 1 file changed, 12 deletions(-)

diff --git a/vignettes/references.bib b/vignettes/references.bib
index aa95da0d..f77b691d 100644
--- a/vignettes/references.bib
+++ b/vignettes/references.bib
@@ -20,11 +20,7 @@ @article{Simonsen_2009
 	volume = {28},
 	number = {14},
 	pages = {1882--1895},
-<<<<<<< HEAD
 	author = {J. Simonsen and K. M{\o}lbak and G. Falkenhorst and K. A. Krogfelt and A. Linneberg and P.F.M. Teunis},
-=======
-	author = {J. Simonsen and K. M{\o}lbak and G. Falkenhorst and K. A. Krogfelt and A. Linneberg and P. F. M. Teunis},
->>>>>>> origin/main
 	title = {Estimation of incidences of infectious diseases based on antibody measurements},
 	journal = {Statistics in Medicine}
 }
@@ -38,11 +34,7 @@ @article{Teunis_2012
 	volume = {31},
 	number = {20},
 	pages = {2240--2248},
-<<<<<<< HEAD
 	author = {P.F.M. Teunis and JCH van Eijkeren and CW Ang and YTHP van Duynhoven and JB Simonsen and MA Strid and W van Pelt},
-=======
-	author = {PFM Teunis and JCH van Eijkeren and CW Ang and YTHP van Duynhoven and JB Simonsen and MA Strid and W van Pelt},
->>>>>>> origin/main
 	title = {Biomarker dynamics: estimating infection rates from serological data},
 	journal = {Statistics in Medicine}
 }
@@ -74,7 +66,6 @@ @article{Strid_2001
 	journal = {Clinical Diagnostic Laboratory Immunology}
 }
 
-<<<<<<< HEAD
 @article{satten_etal04,
     author = {Satten, Glen A. and Kong, Fanhui and Wright, David J. and Glynn, Simone A. and Schreiber, George B.},
     title = "{How special is a ‘special’ interval: modeling departure from length‐biased sampling in renewal processes}",
@@ -84,7 +75,6 @@ @article{satten_etal04
     pages = {145-151},
     year = {2004},
     month = {01},
-    abstract = "{Length‐biased sampling occurs in renewal processes when the probability that an interval is selected is proportional to the length of the interval. This can occur when intervals are selected because they contain an event that is independent of the renewal process and occurs with constant hazard. For example, if the times between donations for repeat blood donors are independent and identically distributed, and if the donor seroconverts to HIV (develops antibodies that indicate infection with human immunodeficiency virus), then the interval between the last HIV seronegative and first HIV seropositive test is expected to be longer than that donor's previous time intervals between donations. We develop hypothesis tests to determine if the relationship between the typical and length‐biased intervals is as expected, or if there is departure from length‐biased sampling. We further develop a regression method to determine if there are covariates that explain the departure from length‐biased sampling. Our approach is motivated by the question of whether there is evidence that repeat blood donors who develop antibodies to HIV or other viral infections change their donation pattern in some way because of seroconversion.}",
     issn = {1465-4644},
     doi = {10.1093/biostatistics/5.1.145},
     url = {https://doi.org/10.1093/biostatistics/5.1.145},
@@ -112,5 +102,3 @@ @article{degreeff_etal12
   year={2012},
   publisher={Am Soc Microbiol}
 }
-=======
->>>>>>> origin/main

From 4d338adf514dd160b494b063ab62cf8faceef40c Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Tue, 14 Nov 2023 19:41:43 -0800
Subject: [PATCH 09/10] fix link

---
 vignettes/tutorial.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/vignettes/tutorial.Rmd b/vignettes/tutorial.Rmd
index b0b37e23..26717add 100644
--- a/vignettes/tutorial.Rmd
+++ b/vignettes/tutorial.Rmd
@@ -312,7 +312,7 @@ The longitudinal response parameters set consists of the following items:
 - `mu1`: initial antibody growth rate
 - `t1`: duration of infection
 
-Please, refer to vignette [methodology.pdf](methodology.pdf) for more details on the underlying 
+Please, refer to `vignette("methodology", package = "serocalculator")` for more details on the underlying 
 methodology.
 
 End user has three options for loading the response parameters into R session:

From 4901de0725afe447648fdf503a0671119b5cce45 Mon Sep 17 00:00:00 2001
From: Douglas Ezra Morrison <demorrison@ucdavis.edu>
Date: Mon, 27 Nov 2023 17:51:32 -0800
Subject: [PATCH 10/10] formatting

---
 vignettes/methodology.Rmd | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/vignettes/methodology.Rmd b/vignettes/methodology.Rmd
index cb383414..1fcfe39e 100644
--- a/vignettes/methodology.Rmd
+++ b/vignettes/methodology.Rmd
@@ -29,9 +29,15 @@ MathJax.Hub.Config({
 
 The `serocalculator` package provides three refinements to the method for 
 calculating seroincidence published earlier [@Teunis_2012] and implemented in R package
-**seroincidence**, versions 1.x: (1) inclusion of infection episode with rising antibody levels, (2) 
-non--exponential decay of serum antibodies after infection, and (3) age--dependent correction for 
-subjects who have never seroconverted. It is important to note that, although the implemented 
+`seroincidence`, versions 1.x: 
+
+(1) inclusion of infection episode with rising antibody levels, 
+
+(2) non--exponential decay of serum antibodies after infection, and 
+
+(3) age--dependent correction for subjects who have never seroconverted. 
+
+It is important to note that, although the implemented 
 methods use a specific parametric model, as proposed in [@de_Graaf_2014] and augmented in 
 [@Teunis_2016], the methods used to calculate the likelihood function allow 
 seroresponses of arbitrary shape.