diff --git a/R/collapse_group_row.R b/R/collapse_group_row.R
index 451342c..42f1884 100644
--- a/R/collapse_group_row.R
+++ b/R/collapse_group_row.R
@@ -2,6 +2,7 @@
 #'
 #' This function is for replacing repeated rows in a data.frame into NA for nice printing. This
 #' is not intended for use during processing.
+#' It is an alternative to `kableExtra::collapse_rows()` for long tables in latex.
 #'
 #' @param .data a data.frame
 #' @param ... Columns to use to identify which to rows to replace with NA's
diff --git a/R/data.R b/R/data.R
index b8460c5..5a62fb7 100644
--- a/R/data.R
+++ b/R/data.R
@@ -1,4 +1,4 @@
-#' Example BAMA dataset
+#' Example dataset for BAMA (Binding Antibody Multiplex Assay)
 #'
 #' A dataset containing response (0/1) and magnitude (continuous) BAMA data for
 #' 7 antigens, 2 groups, and 3 visits. Can be used to run VISCfunctions examples.
@@ -16,7 +16,7 @@
 #' }
 "exampleData_BAMA"
 
-#' Example ICS dataset
+#' Example dataset for ICS (Intracellular Cytokine Staining) assay
 #'
 #' A dataset containing response (0/1) and magnitude (continuous) ICS data for
 #' 3 cell populations and 2 antigen stimulations. Can be used to run VISCfunctions examples.
@@ -44,7 +44,7 @@
 #' }
 "exampleData_ICS"
 
-#' Example NAb dataset
+#' Example dataset for NAb (Neutralizing Antibody) assay
 #'
 #' A dataset containing response (0/1) and magnitude (continuous) NAb data for
 #' 6 isolates, 4 groups, and 1 visit. Can be used to run VISCfunctions examples.
@@ -67,9 +67,10 @@
 #' }
 "exampleData_NAb"
 
-#' Example mAB dataset from DataSpace
+#' Example dataset for mAB (monoclonal antibody) data
 #'
-#' A subset dataset from the Farzan CAVD 812 Study, looking at eCD4 neutralization.
+#' A subset of data from the Farzan CAVD 812 Study, looking at eCD4 neutralization.
+#' Data is sourced from the CAVD DataSpace (CDS).
 #'
 #' @format A data frame with 480 rows and 4 variables:
 #' \describe{
diff --git a/R/pairwise_comparisons.R b/R/pairwise_comparisons.R
index 62af1d2..e0617ed 100644
--- a/R/pairwise_comparisons.R
+++ b/R/pairwise_comparisons.R
@@ -1,7 +1,7 @@
 #'Pairwise Testing for a Continuous Variable
 #'
 #'Takes a continuous variable and performs pairwise testing (t-test or wilcox
-#'test)
+#'test, paired or unpaired) for all possible combinations of the group variable.
 #'
 #'@param x numeric vector (can include NA values).
 #'@param group categorical vector of group values.
@@ -31,7 +31,7 @@
 #'  missing values.
 #'@param verbose a logical variable indicating if warnings and messages should
 #'  be displayed.
-#'@return Returns a data frame with all possible pairwise comparisons:
+#'@return Returns a data frame covering all possible pairwise comparisons with the following columns:
 #' * `Comparison` - Comparisons made
 #' * `SampleSizes` - number of samples per group
 #' * `Median_Min_Max` - Median \[Min, Max\] per group
@@ -447,7 +447,7 @@ pairwise_test_cont <- function(
 #' @param ... other parameters to pass to Exact::exact.test when running
 #'   Barnard test
 #' @return Returns a data frame with all possible pairwise comparisons.
-#'   Variables include Comparison, ResponseStats (group stats; number positive /
+#'   Columns include Comparison, ResponseStats (group stats; number positive /
 #'  number = rate (Wilson CI Bounds)), ResponseTest (fisher/chisq p value),
 #'  PerfectSeparation (a logical flag indicating if one group if 0% and the
 #'  other 100%)
@@ -741,9 +741,9 @@ pairwise_test_bin <- function(x,
 #'   should be displayed.
 #' @param ... parameters passed to `stats::cor.test` or `coin:spearman_test`
 #'
-#' @return Returns a data frame of all possible pairwise correlations
+#' @return Returns a data frame covering all possible pairwise correlations
 #' with pair sizes greater than or equal to the minimum number of values
-#' in pair, as set by `n_distinct_value`:
+#' in pair, as set by `n_distinct_value`; columns are
 #' * `Correlation` - Comparisons made
 #' * `NPairs` - number of non-missing pairs considered
 #' * `Ties` - are ties present in either variable
diff --git a/R/pretty_output_functions.R b/R/pretty_output_functions.R
index c9041c6..f9d9847 100644
--- a/R/pretty_output_functions.R
+++ b/R/pretty_output_functions.R
@@ -1,11 +1,11 @@
 #' Pasting Together Information for Two Groups
 #'
-#' Paste together information, often statistics, from two groups. There are three
+#' Paste together information, usually descriptive statistics, from two groups. There are three
 #' predefined combinations: mean(sd) and median\[min, max\] and median\[first quartile, third quartile\], but user may also
 #' paste any single measure together.
 #'
 #'
-#' @param data input dataset. User must use consistent naming throughout,
+#' @param data input dataset (wide). User must use consistent naming throughout,
 #' \strong{with an underscore} to separate the group names from the measures
 #' (i.e. `Group1_mean` and `Group2_mean`). There also must be two
 #' columns with column names that exactly match the input for `first_name`
@@ -37,7 +37,7 @@
 #' `alternative` included as a parameter so the direction can easily be seen in one-sided test. If "two.sided" is selected the value to be pasted between the two group names will be set to `sep_val`, where "greater" will use " > " and "less" with use " < " as the pasting value.
 #'
 #'
-#' @return data.frame with all the pasted values requested. Each name will have '_comparison' at the end of the names (i.e. mean_comparison, median_comparison, ...)
+#' @return Long data.frame with all the pasted values requested. Each name will have '_comparison' at the end of the names (i.e. mean_comparison, median_comparison, ...)
 #' @examples
 #'
 #' library(dplyr)
@@ -289,24 +289,24 @@ paste_tbl_grp <- function(
 
 
 
-#' Rounds and combines up to three numbers into table friendly presentation
+#' Rounds and combines up to three numbers into table-friendly presentation
 #'
 #' Takes in up to 3 numeric values, rounds each to a specified digit amount
 #' (if numeric), and then combines them accordingly.
 #'
-#' @param stat1 first statistic to be pasted.
-#' @param stat2 second statistic to be pasted (optional).
-#' @param stat3 third statistic to be pasted (optional).
+#' @param stat1 first statistic to be pasted (e.g., mean)
+#' @param stat2 optional second statistic to be pasted (e.g., sd/se, p-value, CI lower bound, minimum)
+#' @param stat3 optional third statistic to be pasted (e.g., CI upper bound, maximum, nth percentile).
 #' @param digits positive integer of length 1 between 0 (default) and 14,
-#' giving the amount of digits to round to.
-#' @param trailing_zeros logical indicating if trailing zeros should included
-#' (i.e. 0.100 instead of 0.1). Note is set to TRUE output is a character vector
+#' giving the amount of digits to round stat1, stat2, and stat3 to.
+#' @param trailing_zeros logical indicating if trailing zeros should be included
+#' (i.e. 0.100 instead of 0.1); default is TRUE
 #' @param bound_char the character to be used between stat1 and stat2/stat3.
 #' Available options are '(' (default), '[', '\{', and '|'.
 #' @param sep the string to be used between stat2 and stat3. The default is ', '.
-#' @param na_str_out the character to replace missing values with.
-#' @param suffix a character string to add at the end of each stat
-#' (i.e. `%` if doing response rates)
+#' @param na_str_out the character to replace missing values with (default is '---')
+#' @param suffix an optional character string to add at the end of each stat
+#' (e.g. `%` if doing response rates); default is NULL
 #'
 #' @return string of combined values
 #'
@@ -422,7 +422,7 @@ stat_paste = function(
 #' @param output_type output type, "latex" (default), "html" , "pandoc"
 #' (for Word document output), or "no_markup"
 #'
-#' @return Vector of transformed p-values for table output
+#' @return Character vector of transformed p-values for table output
 #'
 #' @details
 #'
diff --git a/R/reproducibility_tables.R b/R/reproducibility_tables.R
index c070a08..9b64651 100644
--- a/R/reproducibility_tables.R
+++ b/R/reproducibility_tables.R
@@ -1,6 +1,4 @@
-#' Get Full Username from ID
-#'
-#' For a given ID looks up user name
+#' Look up a username from a Fred Hutch ID
 #'
 #' @param id ID to look full name up. If null (default) looks up ID of current
 #'   user
@@ -256,9 +254,9 @@ get_session_info <- function(libpath = FALSE){
 
 #' Shorten git hash
 #'
-#' Internal function for Reproducibility Tables. find '@' followed by 40 hex
-#' digits, and substitute with the '@' and the first 7 hex digits in ()-captured
-#' group.
+#' Internal function for reproducibility tables; used by get_session_info().
+#' Finds '@' followed by 40 hex digits, and substitutes with the '@' and the
+#' first 7 hex digits in ()-captured group.
 #'
 #' @param x String containing `@` followed by long git hash
 #' @return String containing `@` followed by short git hash
diff --git a/R/statistical_tests_and_estimates.R b/R/statistical_tests_and_estimates.R
index 3f814f6..4c54690 100644
--- a/R/statistical_tests_and_estimates.R
+++ b/R/statistical_tests_and_estimates.R
@@ -1,6 +1,6 @@
 #' Rounding Using Round Away From 0 Method
 #'
-#' round_away_0 takes a numeric vector, rounds them to a specified digit amount using the round away from 0 method for ties (i.e. 1.5). This is the SAS method for rounding.
+#' round_away_0 is an alternative to `round()` to  to properly perform mathematical rounding. It takes a numeric vector, and rounds values to a specified digit amount using the round away from 0 method for ties (e.g., 1.5). This is the SAS method for rounding.
 #'
 #' @param x numeric vector (can include NA values).
 #' @param digits positive integer of length 1 between 0 (default) and 14, giving the amount of digits to round to.
@@ -71,7 +71,7 @@ round_away_0 <- function(x, digits = 0, trailing_zeros = FALSE){
 }
 
 
-#' Continuous Variable Compared to Binary Variable Test (VISC)
+#' Continuous (Response) Variable Compared across Binary (Group) Variable
 #'
 #' Either Wilcox or T-Test Performed, for unpaired or paired data
 #'
@@ -135,7 +135,7 @@ two_samp_cont_test <- function(x, y, method = c('wilcox', 't.test'), paired = FA
 
 
 
-#' Binary (Response) Variable Compared to Binary (Group) Variable Test (VISC)
+#' Binary (Response) Variable Compared across Binary (Group) Variable
 #'
 #' Either Barnard, Fisher's, or Chi-sq test performed for unpaired data and
 #'   McNemar's test for paired data
@@ -254,14 +254,15 @@ two_samp_bin_test <- function(x, y, method = c('barnard', 'fisher' ,'chi.sq' , '
 
 #' Correlation Test for Two Continuous Variables
 #'
-#' This function is a wrapper for [stats::cor.test] function, except if
-#' `method = "spearman"` is selected and there are ties in at least one
+#' This function performs a test to determine if the value of the association
+#' between two continuous variables equals zero. It is a wrapper for [stats::cor.test],
+#' except if `method = "spearman"` is selected and there are ties in at least one
 #' variable, in which case this is a wrapper for [coin::spearman_test]
 #' employing the approximate method.
 #'
 #'
-#' @param x numeric vector (can include NA values).
-#' @param y numeric vector (can include NA values).
+#' @param x numeric vector (can include NA values) representing variable 1
+#' @param y numeric vector (can include NA values) representing variable 2
 #' @param method a character string indicating which correlation coefficient
 #'   is to be used for the test. One of "pearson", "kendall", or "spearman",
 #'   can be abbreviated to "p", "k", or "s".
@@ -275,7 +276,7 @@ two_samp_bin_test <- function(x, y, method = c('barnard', 'fisher' ,'chi.sq' , '
 #' @param verbose a logical variable indicating if warnings and messages
 #'   should be displayed.
 #' @param ... parameters passed to [stats::cor.test] or [coin::spearman_test]
-#' @return correlation estimate p value.
+#' @return estimated p-value.
 #'
 #' @details
 #'
@@ -430,7 +431,7 @@ wilson_ci <- function(x, conf.level = .95){
 #'
 #' `r lifecycle::badge("stable")`
 #'
-#' Wrapper for [binom::binom.confint]
+#' Wrapper for [binom::binom.confint] that estimates binomial confidence intervals for a binary vector.
 #'
 #' @param x vector of type integer (0/1) or logical (TRUE/FALSE)
 #' @param conf.level confidence level (between 0 and 1). Default is 0.95.
@@ -441,14 +442,13 @@ wilson_ci <- function(x, conf.level = .95){
 #'
 #' See [binom::binom.confint] for method details
 #'
-#' @return data.frame with with mean (`mean`), and bounds of confidence interval (`lower`, `upper`)
-#' @return Returns a data frame with the following columns:
+#' @return Returns a data frame of summary statistics with the following columns:
 #' * `method` - method(s) selected
 #' * `x` - number of successes in the binomial experiment
 #' * `n` - number of independent trials in the binomial experiment
 #' * `mean` -  success proportion mean
-#' * `lower` - success proportion lower bound
-#' * `upper` - success proportion upper bound
+#' * `lower` - success proportion confidence internal lower bound
+#' * `upper` - success proportion confidence internal upper bound
 #'
 #' @examples
 #'
diff --git a/R/step_curves.R b/R/step_curves.R
index 426088b..d46f96b 100644
--- a/R/step_curves.R
+++ b/R/step_curves.R
@@ -6,8 +6,8 @@
 #' step line outcomes such as time-to-event (Kaplan-Meier curves) and magnitude
 #' breadth (MB) curves.
 #'
-#' @param x Time values used to create the x-axis in step curves (numeric
-#'   vector)
+#' @param x Values used to create the x-axis in step curves (numeric
+#'   vector) - typically time, or net-MFI for MB.
 #' @param event event status, 0=censor and 1=event (numeric vector). If NULL
 #'   assumes no censoring
 #' @param flip_surv logical indicating if reverse survival estimates should be
diff --git a/R/trapz_sorted.R b/R/trapz_sorted.R
index 21da307..8405784 100644
--- a/R/trapz_sorted.R
+++ b/R/trapz_sorted.R
@@ -1,81 +1,81 @@
-#' Sorted Trapezoidal Integration
-#'
-#' This function is a wrapper for the `trapz` function. It sorts the x and y values
-#' so that it is monotonically increasing along the x values.  Then computes the
-#' area of a function with values `y` and points `x`. There is an optional
-#' parameter to remove any NA values so that integration can proceed by
-#' omitting the `x` and `y` values where the NA occurred.
-#'
-#' @param x A vector of numeric values representing the x-axis over which to integrate.
-#' @param y A vector of numeric values representing the y-axis.
-#' @param na.rm A logical indicating whether to remove NA values from both x and y values.
-#' @return Approximated integral of the function, discretized through the points
-#' x, y, from \code{min(x)} to \code{max(x)}.
-#'
-#' @details
-#'The points (x, 0) and (x, y) are taken as vertices of a polygon. The area is
-#'computed using the trapezoid rule for approximation the definite integral of
-#'the function.
-#'
-#' @examples
-#' set.seed(93)
-#'
-#' # Calculate the area under the sine curve from 0 to pi:
-#' n <- 101
-#' x <- seq(0, pi, len = n)
-#' y <- sin(x)
-#' trapz_sorted(x, y)
-#'
-#' # Calculate area under the curve for unsorted data:
-#' x <- sample(1:n, n, replace = FALSE)
-#' y <- runif(n, 0, 33)
-#' trapz_sorted(x, y)
-#'
-#' # Calculate the area without NA removal
-#' x[10] <- NA
-#' y[3] <- NA
-#' # Will fail to produce a result
-#' trapz_sorted(x, y, na.rm=FALSE)
-#' trapz_sorted(x, y, na.rm=TRUE)
-#'
-#'
-#'
-#' @export
-#'
-trapz_sorted <- function(x, y, na.rm = TRUE){
-  # Input Checking
-  .check_numeric_input(x, allow_dup = FALSE)
-  .check_numeric_input(y)
-  m <- length(x)
-  if (length(y) != m) stop("Arguments 'x', 'y' must be vectors of the same length.")
-  if (na.rm == TRUE) {
-    # Sort by increasing values, NA are removed from x
-    x <- x[order(x, decreasing = FALSE, method = "auto", na.last = NA)]
-    y <- y[order(x, decreasing = FALSE, method = "auto", na.last = NA)]
-    # NA removed from y
-    x <- x[!is.na(y)]
-    y <- y[!is.na(y)]
-  } else{
-    # Warn that data points will be removed if NA
-    if (anyNA(x)) warning("NA values are present in the 'x' values. Returns NA.")
-    if (anyNA(y)) warning("NA values are present in the 'y' values. Returns NA.")
-    # Sort by increasing values, NA are not removed
-    x <- x[order(x, decreasing = FALSE, method = "auto")]
-    y <- y[order(x, decreasing = FALSE, method = "auto")]
-  }
-  # Check for length of x and y after NA removal
-  m <- length(x)
-  if (m < 2) {
-    warning("There are less than 2 observations with non-missing values of both 'x' and 'y', so NA returned.")
-    return(NA)
-  } else {
-    # Integrate
-    xp <- c(x, x[m:1])
-    yp <- c(numeric(m), y[m:1])
-    n <- 2 * m
-    p1 <- sum(xp[1:(n - 1)] * yp[2:n]) + xp[n] * yp[1]
-    p2 <- sum(xp[2:n] * yp[1:(n - 1)]) + xp[1] * yp[n]
-    return(0.5 * (p1 - p2))
-    }
-}
-
+#' Sorted Trapezoidal Integration
+#'
+#' This function is a wrapper for the `pracma::trapz` function. It sorts the x and y values
+#' so that it is monotonically increasing along the x values.  Then computes the
+#' area of a function with values `y` and points `x`. There is an optional
+#' parameter to remove any NA values so that integration can proceed by
+#' omitting the `x` and `y` values where the NA occurred.
+#'
+#' @param x A vector of numeric values representing the x-axis over which to integrate.
+#' @param y A vector of numeric values representing the y-axis.
+#' @param na.rm A logical indicating whether to remove NA values from both x and y values.
+#' @return Numeric value of approximated integral of the function, discretized through the points
+#' x, y, from \code{min(x)} to \code{max(x)}.
+#'
+#' @details
+#'The points (x, 0) and (x, y) are taken as vertices of a polygon. The area is
+#'computed using the trapezoid rule for approximation the definite integral of
+#'the function.
+#'
+#' @examples
+#' set.seed(93)
+#'
+#' # Calculate the area under the sine curve from 0 to pi:
+#' n <- 101
+#' x <- seq(0, pi, len = n)
+#' y <- sin(x)
+#' trapz_sorted(x, y)
+#'
+#' # Calculate area under the curve for unsorted data:
+#' x <- sample(1:n, n, replace = FALSE)
+#' y <- runif(n, 0, 33)
+#' trapz_sorted(x, y)
+#'
+#' # Calculate the area without NA removal
+#' x[10] <- NA
+#' y[3] <- NA
+#' # Will fail to produce a result
+#' trapz_sorted(x, y, na.rm=FALSE)
+#' trapz_sorted(x, y, na.rm=TRUE)
+#'
+#'
+#'
+#' @export
+#'
+trapz_sorted <- function(x, y, na.rm = TRUE){
+  # Input Checking
+  .check_numeric_input(x, allow_dup = FALSE)
+  .check_numeric_input(y)
+  m <- length(x)
+  if (length(y) != m) stop("Arguments 'x', 'y' must be vectors of the same length.")
+  if (na.rm == TRUE) {
+    # Sort by increasing values, NA are removed from x
+    x <- x[order(x, decreasing = FALSE, method = "auto", na.last = NA)]
+    y <- y[order(x, decreasing = FALSE, method = "auto", na.last = NA)]
+    # NA removed from y
+    x <- x[!is.na(y)]
+    y <- y[!is.na(y)]
+  } else{
+    # Warn that data points will be removed if NA
+    if (anyNA(x)) warning("NA values are present in the 'x' values. Returns NA.")
+    if (anyNA(y)) warning("NA values are present in the 'y' values. Returns NA.")
+    # Sort by increasing values, NA are not removed
+    x <- x[order(x, decreasing = FALSE, method = "auto")]
+    y <- y[order(x, decreasing = FALSE, method = "auto")]
+  }
+  # Check for length of x and y after NA removal
+  m <- length(x)
+  if (m < 2) {
+    warning("There are less than 2 observations with non-missing values of both 'x' and 'y', so NA returned.")
+    return(NA)
+  } else {
+    # Integrate
+    xp <- c(x, x[m:1])
+    yp <- c(numeric(m), y[m:1])
+    n <- 2 * m
+    p1 <- sum(xp[1:(n - 1)] * yp[2:n]) + xp[n] * yp[1]
+    p2 <- sum(xp[2:n] * yp[1:(n - 1)]) + xp[1] * yp[n]
+    return(0.5 * (p1 - p2))
+    }
+}
+
diff --git a/README.Rmd b/README.Rmd
deleted file mode 100644
index 6ad3809..0000000
--- a/README.Rmd
+++ /dev/null
@@ -1,98 +0,0 @@
----
-output: github_document
----
-
-<!-- badges: start -->
-  [![R build status](https://github.com/FredHutch/VISCfunctions/workflows/R-CMD-check/badge.svg)](https://github.com/FredHutch/VISCfunctions/actions)
-[![Codecov test coverage](https://codecov.io/gh/FredHutch/VISCfunctions/graph/badge.svg)](https://app.codecov.io/gh/FredHutch/VISCfunctions)
-  [![License:MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-<!-- badges: end -->
-
-  
-```{r setup, include = FALSE}
-knitr::opts_chunk$set(
-  collapse = TRUE,
-  comment = "#>",
-  fig.path = "man/figures/README-",
-  out.width = "100%"
-)
-```
-
-# VISCfunctions
-
-The package provides functions for common tasks for creating statistical reports at Vaccine Immunology Statistical Center (VISC).  The goal of VISCfunctions is to:
-
-* provide standard statistical testing and estimating functions
-* help format output for PDF and Word reports
-* provide frequently used utility functions
-
-for VISC statisticians and programmers at Fred Hutch.
-
-# Installation
-
-The package is available on the Fred Hutch organization GitHub page.
-
-```{r eval=FALSE}
-remotes::install_github("FredHutch/VISCfunctions")
-
-# Use the build_vignettes parameter to access the vignette
-# (Note that this may auto-upgrade dependencies - this behavior can be controlled with the `upgrade` argument)
-remotes::install_github("FredHutch/VISCfunctions", dependencies = TRUE, build_vignettes = TRUE)
-vignette("Overview")
-```
-
-# Overview
-
-Below is an overview of the currently available functions in VISCfunctions.
-
-## Statistical testing and estimates
-
-Compare two groups, return a p-value:
-
-* `two_sample_bin_test()` for a Barnard, Fisher's Exact, Chi-Square or McNemar test.
-* `two_samp_cont_test()` for a t.test (paired or unpaired), Wilcox Rank-Sum, or Wilcox Signed-Rank test.
-* `cor_test()` for a Spearman, Pearson, or Kendall correlation test.
-
-Make all pairwise comparisons of a grouping variable (or any categorical variable), return descriptive statistics and p-values:
-
-* `pairwise_test_bin()` for a Barnard, Fisher's Exact, Chi-Square or McNemar test.
-* `pairwise_test_cont()` for a t.test (paired or unpaired), Wilcox Rank-Sum, or Wilcox Signed-Rank test.
-* `cor_test_pairs()` for a Spearman, Pearson, or Kendall correlation test.
-
-Estimate binomial confidence intervals for a binary vector:
-
-* `binom_ci()`
-
-## Formatting output
-
-* `paste_tbl_grp()` to paste together information (usually descriptive statistics) from two groups.
-* `pretty_pvalues()` to round and format p-values.
-* `stat_paste()` to combine and format values, such as:
-    + Mean (sd)
-    + Median [min, max]
-    + Estimate (SE of Estimate)
-    + Estimate (95% CI Lower Bound, Upper Bound)
-    + Estimate/Statistic (p value)
-* `escape()` to protect control characters in a string for use in a latex table or caption
-* `collapse_group_row()` as an alternative to `kableExtra::collapse_rows()` for long tables in latex
-
-## Survival and Magnitude Breadth
-
-* `create_step_curve()` to create survival probabilities and generate a risk table
-* `mb_results()` to create step curve info for magnitude breadth (MB) plots and AUC-MB
-
-## Utility functions
-
-* `round_away_0()` is an alternative to the `round()` function to properly perform mathematical rounding.
-* `escape()` is used to inserts a "\\" in front of values, which is needed for Latex.
-* `get_full_name()` looks up a username from Fred Hutch ID.
-* `get_session_info()` creates a a data frame with session information.
-
-
-# Vignette
-
-For more information, browse the vignette (`browseVignettes("VISCfunctions")`).
-
-# Contribute to this package
-
-See our [contributing guide](CONTRIBUTING.md) to learn more about how you can contribute to this package.
diff --git a/README.md b/README.md
index dae75a4..69e00c0 100644
--- a/README.md
+++ b/README.md
@@ -6,23 +6,26 @@ status](https://github.com/FredHutch/VISCfunctions/workflows/R-CMD-check/badge.s
 [![Codecov test
 coverage](https://codecov.io/gh/FredHutch/VISCfunctions/graph/badge.svg)](https://app.codecov.io/gh/FredHutch/VISCfunctions)
 [![License:MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
 <!-- badges: end -->
 
 # VISCfunctions
 
-The package provides functions for common tasks for creating statistical
-reports at Vaccine Immunology Statistical Center (VISC). The goal of
-VISCfunctions is to:
-
-- provide standard statistical testing and estimating functions
-- help format output for PDF and Word reports
-- provide frequently used utility functions
+VISCfunctions is an open-source R package that helps automate and
+standardize common tasks that are part of the process of analysis at the
+Vaccine & Immunology Statistical Center (VISC) at Fred Hutch. The scope
+of VISCfunctions is to aid VISC statisticians and programmers by
+providing:
 
-for VISC statisticians and programmers at Fred Hutch.
+-   standard statistical testing and estimating functions
+-   standard figure and table formatting functions
+-   utility functions for formatting PDF and Word output
+-   utility functions that aid with transparency and reproducibility
+-   example datasets for common lab assays
 
-# Installation
+## Installation
 
-The package is available on the Fred Hutch organization GitHub page.
+The package is available through the Fred Hutch GitHub organization:
 
 ``` r
 remotes::install_github("FredHutch/VISCfunctions")
@@ -30,76 +33,23 @@ remotes::install_github("FredHutch/VISCfunctions")
 # Use the build_vignettes parameter to access the vignette
 # (Note that this may auto-upgrade dependencies - this behavior can be controlled with the `upgrade` argument)
 remotes::install_github("FredHutch/VISCfunctions", dependencies = TRUE, build_vignettes = TRUE)
-vignette("Overview")
 ```
 
-# Overview
-
-Below is an overview of the currently available functions in
-VISCfunctions.
-
-## Statistical testing and estimates
-
-Compare two groups, return a p-value:
-
-- `two_sample_bin_test()` for a Barnard, Fisher’s Exact, Chi-Square or
-  McNemar test.
-- `two_samp_cont_test()` for a t.test (paired or unpaired), Wilcox
-  Rank-Sum, or Wilcox Signed-Rank test.
-- `cor_test()` for a Spearman, Pearson, or Kendall correlation test.
-
-Make all pairwise comparisons of a grouping variable (or any categorical
-variable), return descriptive statistics and p-values:
-
-- `pairwise_test_bin()` for a Barnard, Fisher’s Exact, Chi-Square or
-  McNemar test.
-- `pairwise_test_cont()` for a t.test (paired or unpaired), Wilcox
-  Rank-Sum, or Wilcox Signed-Rank test.
-- `cor_test_pairs()` for a Spearman, Pearson, or Kendall correlation
-  test.
-
-Estimate binomial confidence intervals for a binary vector:
+Documentation can be viewed at
+<https://fredhutch.github.io/VISCfunctions> and also through standard R
+syntax such as:
 
-- `binom_ci()`
-
-## Formatting output
-
-- `paste_tbl_grp()` to paste together information (usually descriptive
-  statistics) from two groups.
-- `pretty_pvalues()` to round and format p-values.
-- `stat_paste()` to combine and format values, such as:
-  - Mean (sd)
-  - Median \[min, max\]
-  - Estimate (SE of Estimate)
-  - Estimate (95% CI Lower Bound, Upper Bound)
-  - Estimate/Statistic (p value)
-- `escape()` to protect control characters in a string for use in a
-  latex table or caption
-- `collapse_group_row()` as an alternative to
-  `kableExtra::collapse_rows()` for long tables in latex
-
-## Survival and Magnitude Breadth
-
-- `create_step_curve()` to create survival probabilities and generate a
-  risk table
-- `mb_results()` to create step curve info for magnitude breadth (MB)
-  plots and AUC-MB
-
-## Utility functions
-
-- `round_away_0()` is an alternative to the `round()` function to
-  properly perform mathematical rounding.
-- `escape()` is used to inserts a “\\” in front of values, which is
-  needed for Latex.
-- `get_full_name()` looks up a username from Fred Hutch ID.
-- `get_session_info()` creates a a data frame with session information.
-
-# Vignette
+``` r
+library(VISCfunctions)
+browseVignettes("VISCfunctions")
+vignette("Overview")
+help(two_samp_bin_test)  # or ?two_sample_bin_test; similarly for other functions
+```
 
-For more information, browse the vignette
-(`browseVignettes("VISCfunctions")`).
+## Contribute to this package
 
-# Contribute to this package
+You can file an issue or feature request on GitHub:
+<https://github.com/FredHutch/VISCfunctions/issues>
 
-See our [contributing guide](CONTRIBUTING.md) to learn more about how you
-can contribute to this package.
+See our [contributing guide](CONTRIBUTING.md) to learn more about how
+you can contribute.
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 2062931..9f869a3 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -2,3 +2,60 @@ url: https://fredhutch.github.io/VISCfunctions/
 template:
   bootstrap: 5
 
+navbar:
+  structure:
+    left:
+      - home
+      - reference
+      - vignettes   # instead of default "articles"
+      - news        # instead of default "changelog"
+  components:
+    vignettes:
+      text: "Vignettes"
+      href: articles/index.html
+    news:
+      text: "News"
+      href: news/index.html
+
+
+reference:
+  - title: "General Statistical Tests"
+    desc: "Formal hypothesis testing and p-value computations"
+    contents:
+      - two_samp_bin_test
+      - two_samp_cont_test
+      - cor_test
+      - pairwise_test_bin
+      - pairwise_test_cont
+      - cor_test_pairs
+      - binom_ci
+      - wilson_ci
+
+  - title: "Survival and Magnitude Breadth"
+    contents:
+      - create_step_curve
+      - mb_results
+      - trapz_sorted
+
+  - title: "Figure, Table, PDF/Word Output Formatting"
+    contents:
+      - collapse_group_row
+      - escape
+      - paste_tbl_grp
+      - pretty_pvalues
+      - round_away_0
+      - stat_paste
+
+  - title: "Transparency and Reproducibility"
+    contents:
+      - get_full_name
+      - get_session_info
+      - shorten_git_hash
+
+  - title: "Example Datasets"
+    contents:
+      - exampleData_BAMA
+      - exampleData_ICS
+      - exampleData_NAb
+      - CAVD812_mAB
+      - G001_Bcell_flow_seq_PBMC
diff --git a/man/CAVD812_mAB.Rd b/man/CAVD812_mAB.Rd
index 5d671f3..017a259 100644
--- a/man/CAVD812_mAB.Rd
+++ b/man/CAVD812_mAB.Rd
@@ -3,7 +3,7 @@
 \docType{data}
 \name{CAVD812_mAB}
 \alias{CAVD812_mAB}
-\title{Example mAB dataset from DataSpace}
+\title{Example dataset for mAB (monoclonal antibody) data}
 \format{
 A data frame with 480 rows and 4 variables:
 \describe{
@@ -20,6 +20,7 @@ A data frame with 480 rows and 4 variables:
 CAVD812_mAB
 }
 \description{
-A subset dataset from the Farzan CAVD 812 Study, looking at eCD4 neutralization.
+A subset of data from the Farzan CAVD 812 Study, looking at eCD4 neutralization.
+Data is sourced from the CAVD DataSpace (CDS).
 }
 \keyword{datasets}
diff --git a/man/VISCfunctions-package.Rd b/man/VISCfunctions-package.Rd
index cd6f1ec..bbc5bde 100644
--- a/man/VISCfunctions-package.Rd
+++ b/man/VISCfunctions-package.Rd
@@ -5,7 +5,7 @@
 \alias{VISCfunctions-package}
 \title{VISCfunctions: VISCfunctions}
 \description{
-Statistical, data processing, and annotation functions for VISC.
+Statistical, data processing, and annotation functions for VISC statisticians and programmers.
 }
 \seealso{
 Useful links:
diff --git a/man/VISCfunctions.Rd b/man/VISCfunctions.Rd
index ddcd9d7..f11efd9 100644
--- a/man/VISCfunctions.Rd
+++ b/man/VISCfunctions.Rd
@@ -5,7 +5,7 @@
 \alias{VISCfunctions}
 \title{VISCfunctions: VISC STP/SRA functions}
 \description{
-Statistical, data processing, and annotation functions for VISC.
+Statistical, data processing, and annotation functions for VISC statisticians and programmers.
 }
 \seealso{
 Useful links:
diff --git a/man/binom_ci.Rd b/man/binom_ci.Rd
index faad482..343d838 100644
--- a/man/binom_ci.Rd
+++ b/man/binom_ci.Rd
@@ -16,22 +16,20 @@ binom_ci(x, conf.level = 0.95, methods = "wilson", ...)
 \item{...}{Additional arguments to be passed to \link[binom:binom.bayes]{binom::binom.bayes}}
 }
 \value{
-data.frame with with mean (\code{mean}), and bounds of confidence interval (\code{lower}, \code{upper})
-
-Returns a data frame with the following columns:
+Returns a data frame of summary statistics with the following columns:
 \itemize{
 \item \code{method} - method(s) selected
 \item \code{x} - number of successes in the binomial experiment
 \item \code{n} - number of independent trials in the binomial experiment
 \item \code{mean} -  success proportion mean
-\item \code{lower} - success proportion lower bound
-\item \code{upper} - success proportion upper bound
+\item \code{lower} - success proportion confidence internal lower bound
+\item \code{upper} - success proportion confidence internal upper bound
 }
 }
 \description{
 \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#stable}{\figure{lifecycle-stable.svg}{options: alt='[Stable]'}}}{\strong{[Stable]}}
 
-Wrapper for \link[binom:binom.confint]{binom::binom.confint}
+Wrapper for \link[binom:binom.confint]{binom::binom.confint} that estimates binomial confidence intervals for a binary vector.
 }
 \details{
 See \link[binom:binom.confint]{binom::binom.confint} for method details
diff --git a/man/collapse_group_row.Rd b/man/collapse_group_row.Rd
index 3a05ff8..a41ce1e 100644
--- a/man/collapse_group_row.Rd
+++ b/man/collapse_group_row.Rd
@@ -19,6 +19,7 @@ a data.frame where repeated rows in the columns identified by ... are replaced w
 \description{
 This function is for replacing repeated rows in a data.frame into NA for nice printing. This
 is not intended for use during processing.
+It is an alternative to \code{kableExtra::collapse_rows()} for long tables in latex.
 }
 \examples{
 sample_df <- data.frame(
diff --git a/man/cor_test.Rd b/man/cor_test.Rd
index d6243b5..43bd098 100644
--- a/man/cor_test.Rd
+++ b/man/cor_test.Rd
@@ -16,9 +16,9 @@ cor_test(
 )
 }
 \arguments{
-\item{x}{numeric vector (can include NA values).}
+\item{x}{numeric vector (can include NA values) representing variable 1}
 
-\item{y}{numeric vector (can include NA values).}
+\item{y}{numeric vector (can include NA values) representing variable 2}
 
 \item{method}{a character string indicating which correlation coefficient
 is to be used for the test. One of "pearson", "kendall", or "spearman",
@@ -40,11 +40,12 @@ should be displayed.}
 \item{...}{parameters passed to \link[stats:cor.test]{stats::cor.test} or \link[coin:CorrelationTests]{coin::spearman_test}}
 }
 \value{
-correlation estimate p value.
+estimated p-value.
 }
 \description{
-This function is a wrapper for \link[stats:cor.test]{stats::cor.test} function, except if
-\code{method = "spearman"} is selected and there are ties in at least one
+This function performs a test to determine if the value of the association
+between two continuous variables equals zero. It is a wrapper for \link[stats:cor.test]{stats::cor.test},
+except if \code{method = "spearman"} is selected and there are ties in at least one
 variable, in which case this is a wrapper for \link[coin:CorrelationTests]{coin::spearman_test}
 employing the approximate method.
 }
diff --git a/man/cor_test_pairs.Rd b/man/cor_test_pairs.Rd
index cc38f7b..57f0b4c 100644
--- a/man/cor_test_pairs.Rd
+++ b/man/cor_test_pairs.Rd
@@ -57,9 +57,9 @@ should be displayed.}
 \item{...}{parameters passed to \code{stats::cor.test} or \code{coin:spearman_test}}
 }
 \value{
-Returns a data frame of all possible pairwise correlations
+Returns a data frame covering all possible pairwise correlations
 with pair sizes greater than or equal to the minimum number of values
-in pair, as set by \code{n_distinct_value}:
+in pair, as set by \code{n_distinct_value}; columns are
 \itemize{
 \item \code{Correlation} - Comparisons made
 \item \code{NPairs} - number of non-missing pairs considered
diff --git a/man/create_step_curve.Rd b/man/create_step_curve.Rd
index 3e9febd..e48e118 100644
--- a/man/create_step_curve.Rd
+++ b/man/create_step_curve.Rd
@@ -7,8 +7,8 @@
 create_step_curve(x, event = NULL, flip_surv = FALSE, flip_top_x = Inf)
 }
 \arguments{
-\item{x}{Time values used to create the x-axis in step curves (numeric
-vector)}
+\item{x}{Values used to create the x-axis in step curves (numeric
+vector) - typically time, or net-MFI for MB.}
 
 \item{event}{event status, 0=censor and 1=event (numeric vector). If NULL
 assumes no censoring}
diff --git a/man/exampleData_BAMA.Rd b/man/exampleData_BAMA.Rd
index e142402..b4787cc 100644
--- a/man/exampleData_BAMA.Rd
+++ b/man/exampleData_BAMA.Rd
@@ -3,7 +3,7 @@
 \docType{data}
 \name{exampleData_BAMA}
 \alias{exampleData_BAMA}
-\title{Example BAMA dataset}
+\title{Example dataset for BAMA (Binding Antibody Multiplex Assay)}
 \format{
 A data frame with 252 rows and 6 variables:
 \describe{
diff --git a/man/exampleData_ICS.Rd b/man/exampleData_ICS.Rd
index 6b0b136..598275c 100644
--- a/man/exampleData_ICS.Rd
+++ b/man/exampleData_ICS.Rd
@@ -3,7 +3,7 @@
 \docType{data}
 \name{exampleData_ICS}
 \alias{exampleData_ICS}
-\title{Example ICS dataset}
+\title{Example dataset for ICS (Intracellular Cytokine Staining) assay}
 \format{
 A data frame with 306 rows and 15 variables:
 \describe{
diff --git a/man/exampleData_NAb.Rd b/man/exampleData_NAb.Rd
index 1fa48cc..1a75456 100644
--- a/man/exampleData_NAb.Rd
+++ b/man/exampleData_NAb.Rd
@@ -3,7 +3,7 @@
 \docType{data}
 \name{exampleData_NAb}
 \alias{exampleData_NAb}
-\title{Example NAb dataset}
+\title{Example dataset for NAb (Neutralizing Antibody) assay}
 \format{
 A data frame with 210 rows and 9 variables:
 \describe{
diff --git a/man/get_full_name.Rd b/man/get_full_name.Rd
index b0d083c..ea2520b 100644
--- a/man/get_full_name.Rd
+++ b/man/get_full_name.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/reproducibility_tables.R
 \name{get_full_name}
 \alias{get_full_name}
-\title{Get Full Username from ID}
+\title{Look up a username from a Fred Hutch ID}
 \usage{
 get_full_name(id = NULL)
 }
@@ -14,7 +14,7 @@ user}
 First and Last name associated with ID
 }
 \description{
-For a given ID looks up user name
+Look up a username from a Fred Hutch ID
 }
 \details{
 If \code{id} null, uses system "USERNAME" variable for Windows and "USER"
diff --git a/man/pairwise_test_bin.Rd b/man/pairwise_test_bin.Rd
index cca4305..a488c81 100644
--- a/man/pairwise_test_bin.Rd
+++ b/man/pairwise_test_bin.Rd
@@ -77,7 +77,7 @@ Barnard test}
 }
 \value{
 Returns a data frame with all possible pairwise comparisons.
-Variables include Comparison, ResponseStats (group stats; number positive /
+Columns include Comparison, ResponseStats (group stats; number positive /
 number = rate (Wilson CI Bounds)), ResponseTest (fisher/chisq p value),
 PerfectSeparation (a logical flag indicating if one group if 0\% and the
 other 100\%)
diff --git a/man/pairwise_test_cont.Rd b/man/pairwise_test_cont.Rd
index c7c2df3..e55d473 100644
--- a/man/pairwise_test_cont.Rd
+++ b/man/pairwise_test_cont.Rd
@@ -65,7 +65,7 @@ missing values.}
 be displayed.}
 }
 \value{
-Returns a data frame with all possible pairwise comparisons:
+Returns a data frame covering all possible pairwise comparisons with the following columns:
 \itemize{
 \item \code{Comparison} - Comparisons made
 \item \code{SampleSizes} - number of samples per group
@@ -85,7 +85,7 @@ separation).
 }
 \description{
 Takes a continuous variable and performs pairwise testing (t-test or wilcox
-test)
+test, paired or unpaired) for all possible combinations of the group variable.
 }
 \details{
 Runs \code{wilcox_test()} in the coin package, with "exact" distribution.
diff --git a/man/paste_tbl_grp.Rd b/man/paste_tbl_grp.Rd
index c86d46d..ecf40ea 100644
--- a/man/paste_tbl_grp.Rd
+++ b/man/paste_tbl_grp.Rd
@@ -19,7 +19,7 @@ paste_tbl_grp(
 )
 }
 \arguments{
-\item{data}{input dataset. User must use consistent naming throughout,
+\item{data}{input dataset (wide). User must use consistent naming throughout,
 \strong{with an underscore} to separate the group names from the measures
 (i.e. \code{Group1_mean} and \code{Group2_mean}). There also must be two
 columns with column names that exactly match the input for \code{first_name}
@@ -56,10 +56,10 @@ determine the character to be pasted between the group names
 \item{verbose}{a logical variable indicating if warnings and messages should be displayed. Default FALSE.}
 }
 \value{
-data.frame with all the pasted values requested. Each name will have '_comparison' at the end of the names (i.e. mean_comparison, median_comparison, ...)
+Long data.frame with all the pasted values requested. Each name will have '_comparison' at the end of the names (i.e. mean_comparison, median_comparison, ...)
 }
 \description{
-Paste together information, often statistics, from two groups. There are three
+Paste together information, usually descriptive statistics, from two groups. There are three
 predefined combinations: mean(sd) and median[min, max] and median[first quartile, third quartile], but user may also
 paste any single measure together.
 }
diff --git a/man/pretty_pvalues.Rd b/man/pretty_pvalues.Rd
index 8d1c5ad..a883a35 100644
--- a/man/pretty_pvalues.Rd
+++ b/man/pretty_pvalues.Rd
@@ -46,7 +46,7 @@ with trailing zeros to the defined number of digits (i.e. 0.100 instead of 0.1 i
 (for Word document output), or "no_markup"}
 }
 \value{
-Vector of transformed p-values for table output
+Character vector of transformed p-values for table output
 }
 \description{
 pretty_pvalues() takes a vector of p-values, rounds them to a specified
diff --git a/man/round_away_0.Rd b/man/round_away_0.Rd
index df58519..3ec1511 100644
--- a/man/round_away_0.Rd
+++ b/man/round_away_0.Rd
@@ -17,7 +17,7 @@ round_away_0(x, digits = 0, trailing_zeros = FALSE)
 if \code{trailing_zeros = TRUE} returns a character vector of rounded values with trailing zeros, otherwise returns a numeric vector of rounded values.
 }
 \description{
-round_away_0 takes a numeric vector, rounds them to a specified digit amount using the round away from 0 method for ties (i.e. 1.5). This is the SAS method for rounding.
+round_away_0 is an alternative to \code{round()} to  to properly perform mathematical rounding. It takes a numeric vector, and rounds values to a specified digit amount using the round away from 0 method for ties (e.g., 1.5). This is the SAS method for rounding.
 }
 \details{
 \code{round_away_0} is not designed for use at precision levels <= 1e-15
diff --git a/man/shorten_git_hash.Rd b/man/shorten_git_hash.Rd
index fe223ff..6bd1912 100644
--- a/man/shorten_git_hash.Rd
+++ b/man/shorten_git_hash.Rd
@@ -13,7 +13,7 @@ shorten_git_hash(x)
 String containing \code{@} followed by short git hash
 }
 \description{
-Internal function for Reproducibility Tables. find '@' followed by 40 hex
-digits, and substitute with the '@' and the first 7 hex digits in ()-captured
-group.
+Internal function for reproducibility tables; used by get_session_info().
+Finds '@' followed by 40 hex digits, and substitutes with the '@' and the
+first 7 hex digits in ()-captured group.
 }
diff --git a/man/stat_paste.Rd b/man/stat_paste.Rd
index 1ebaa47..02a9712 100644
--- a/man/stat_paste.Rd
+++ b/man/stat_paste.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/pretty_output_functions.R
 \name{stat_paste}
 \alias{stat_paste}
-\title{Rounds and combines up to three numbers into table friendly presentation}
+\title{Rounds and combines up to three numbers into table-friendly presentation}
 \usage{
 stat_paste(
   stat1,
@@ -17,27 +17,27 @@ stat_paste(
 )
 }
 \arguments{
-\item{stat1}{first statistic to be pasted.}
+\item{stat1}{first statistic to be pasted (e.g., mean)}
 
-\item{stat2}{second statistic to be pasted (optional).}
+\item{stat2}{optional second statistic to be pasted (e.g., sd/se, p-value, CI lower bound, minimum)}
 
-\item{stat3}{third statistic to be pasted (optional).}
+\item{stat3}{optional third statistic to be pasted (e.g., CI upper bound, maximum, nth percentile).}
 
 \item{digits}{positive integer of length 1 between 0 (default) and 14,
-giving the amount of digits to round to.}
+giving the amount of digits to round stat1, stat2, and stat3 to.}
 
-\item{trailing_zeros}{logical indicating if trailing zeros should included
-(i.e. 0.100 instead of 0.1). Note is set to TRUE output is a character vector}
+\item{trailing_zeros}{logical indicating if trailing zeros should be included
+(i.e. 0.100 instead of 0.1); default is TRUE}
 
 \item{bound_char}{the character to be used between stat1 and stat2/stat3.
 Available options are '(' (default), '[', '\{', and '|'.}
 
 \item{sep}{the string to be used between stat2 and stat3. The default is ', '.}
 
-\item{na_str_out}{the character to replace missing values with.}
+\item{na_str_out}{the character to replace missing values with (default is '---')}
 
-\item{suffix}{a character string to add at the end of each stat
-(i.e. \verb{\%} if doing response rates)}
+\item{suffix}{an optional character string to add at the end of each stat
+(e.g. \verb{\%} if doing response rates); default is NULL}
 }
 \value{
 string of combined values
diff --git a/man/trapz_sorted.Rd b/man/trapz_sorted.Rd
index 5d599c7..f5981ab 100644
--- a/man/trapz_sorted.Rd
+++ b/man/trapz_sorted.Rd
@@ -14,11 +14,11 @@ trapz_sorted(x, y, na.rm = TRUE)
 \item{na.rm}{A logical indicating whether to remove NA values from both x and y values.}
 }
 \value{
-Approximated integral of the function, discretized through the points
+Numeric value of approximated integral of the function, discretized through the points
 x, y, from \code{min(x)} to \code{max(x)}.
 }
 \description{
-This function is a wrapper for the \code{trapz} function. It sorts the x and y values
+This function is a wrapper for the \code{pracma::trapz} function. It sorts the x and y values
 so that it is monotonically increasing along the x values.  Then computes the
 area of a function with values \code{y} and points \code{x}. There is an optional
 parameter to remove any NA values so that integration can proceed by
diff --git a/man/two_samp_bin_test.Rd b/man/two_samp_bin_test.Rd
index a254047..b3c424f 100644
--- a/man/two_samp_bin_test.Rd
+++ b/man/two_samp_bin_test.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/statistical_tests_and_estimates.R
 \name{two_samp_bin_test}
 \alias{two_samp_bin_test}
-\title{Binary (Response) Variable Compared to Binary (Group) Variable Test (VISC)}
+\title{Binary (Response) Variable Compared across Binary (Group) Variable}
 \usage{
 two_samp_bin_test(
   x,
diff --git a/man/two_samp_cont_test.Rd b/man/two_samp_cont_test.Rd
index 2f58915..eb156f4 100644
--- a/man/two_samp_cont_test.Rd
+++ b/man/two_samp_cont_test.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/statistical_tests_and_estimates.R
 \name{two_samp_cont_test}
 \alias{two_samp_cont_test}
-\title{Continuous Variable Compared to Binary Variable Test (VISC)}
+\title{Continuous (Response) Variable Compared across Binary (Group) Variable}
 \usage{
 two_samp_cont_test(
   x,