diff --git a/R/data_generation.R b/R/data_generation.R
index 7b34c1ca..ec702ea5 100644
--- a/R/data_generation.R
+++ b/R/data_generation.R
@@ -9,6 +9,7 @@
 #' of 35% under the active treatment at baseline (with the values of the covariates set to zero).
 #'
 #' @param N sample size
+#' @param ncov number of covariates to generate
 #' @param lambda scale parameter in baseline hazard function
 #' @param nu shape parameter in baseline hazard function
 #' @param censor_rate rate parameter of the exponential distribution of censoring times
diff --git a/R/matching.R b/R/matching.R
index 2f3383e4..aa695724 100644
--- a/R/matching.R
+++ b/R/matching.R
@@ -4,8 +4,9 @@
 
 #' Derive individual weights in the matching step of MAIC
 #'
-#' Assuming data is properly processed, this function takes individual patient data (IPD) with centered covariates (effect modifiers and/or prognostic variables) as input,
-#' and generates weights for each individual in IPD trial that matches the chosen statistics of those covariates in Aggregated Data (AgD) trial.
+#' Assuming data is properly processed, this function takes individual patient data (IPD) with centered covariates
+#' (effect modifiers and/or prognostic variables) as input, and generates weights for each individual in IPD trial that
+#' matches the chosen statistics of those covariates in Aggregated Data (AgD) trial.
 #'
 #' @param data a numeric matrix, centered covariates of IPD, no missing value in any cell is allowed
 #' @param centered_colnames a character or numeric vector (column indicators) of centered covariates
@@ -17,9 +18,11 @@
 #' @return a list with the following 4 elements,
 #' \describe{
 #'   \item{data}{a data.frame, includes the input \code{data} with appended column 'weights' and 'scaled_weights'.
-#'   Scaled weights has a summation to be the number of rows in \code{data} that has no missing value in any of the effect modifiers}
+#'   Scaled weights has a summation to be the number of rows in \code{data} that has no missing value in any of the
+#'   effect modifiers}
 #'   \item{centered_colnames}{column names of centered effect modifiers in \code{data}}
-#'   \item{nr_missing}{number of rows in \code{data} that has at least 1 missing value in specified centered effect modifiers}
+#'   \item{nr_missing}{number of rows in \code{data} that has at least 1 missing value in specified centered effect
+#'   modifiers}
 #'   \item{ess}{effective sample size, square of sum divided by sum of squares}
 #'   \item{opt}{R object returned by \code{base::optim()}, for assess convergence and other details}
 #' }
@@ -32,10 +35,10 @@ estimate_weights <- function(data, centered_colnames = NULL, start_val = 0, meth
   if (!ch1) stop("'data' is not a data.frame")
 
   ch2 <- (!is.null(centered_colnames))
-  if (ch2 & is.numeric(centered_colnames)) {
+  if (ch2 && is.numeric(centered_colnames)) {
     ch2b <- any(centered_colnames < 1 | centered_colnames > ncol(data))
     if (ch2b) stop("specified centered_colnames are out of bound")
-  } else if (ch2 & is.character(centered_colnames)) {
+  } else if (ch2 && is.character(centered_colnames)) {
     ch2b <- !all(centered_colnames %in% names(data))
     if (ch2b) stop("1 or more specified centered_colnames are not found in 'data'")
   } else {
@@ -45,7 +48,9 @@ estimate_weights <- function(data, centered_colnames = NULL, start_val = 0, meth
   ch3 <- sapply(seq_along(centered_colnames), function(ii) {
     !is.numeric(data[, centered_colnames[ii]])
   })
-  if (any(ch3)) stop(paste0("following columns of 'data' are not numeric for the calculation:", paste(which(ch3), collapse = ",")))
+  if (any(ch3)) {
+    stop(paste0("following columns of 'data' are not numeric for the calculation:", paste(which(ch3), collapse = ",")))
+  }
 
   # prepare data for optimization
   if (is.null(centered_colnames)) centered_colnames <- seq_len(ncol(data))
@@ -149,8 +154,9 @@ plot_weights <- function(wt, main_title = "Unscaled Individual Weights") {
 #' before and after adjustment.
 #'
 #' @param optimized object returned after calculating weights using \code{\link{cal_weights}}
-#' @param match_cov covariates that should be checked to see if the IPD weighted average matches the aggregate data average
-#' This could be same set of variables that were used to match or it can include variables that were not included to match (i.e. stratification variables)
+#' @param match_cov covariates that should be checked to see if the IPD weighted average matches the aggregate data
+#' average. This could be same set of variables that were used to match or it can include variables that were not
+#' included to match (i.e. stratification variables)
 #' @param digits number of digits for rounding summary table
 #'
 #' @return data.frame of weighted and unweighted covariate averages of the IPD
diff --git a/R/process_data.R b/R/process_data.R
index 60ab9cce..74a84349 100644
--- a/R/process_data.R
+++ b/R/process_data.R
@@ -226,6 +226,7 @@ complete_agd <- function(use_agd) {
 #'
 #' @param dd data frame, ADTTE read via haven::read_sas
 #' @param time_scale a character string, 'year', 'month', 'week' or 'day', time unit of median survival time
+#' @param trt values to include in treatment column
 #'
 #' @return a data frame that can be used as input to survival::Surv
 ext_tte_transfer <- function(dd, time_scale = "month", trt = NULL) {
diff --git a/man/check_weights.Rd b/man/check_weights.Rd
index bcb61209..03d81c34 100644
--- a/man/check_weights.Rd
+++ b/man/check_weights.Rd
@@ -9,8 +9,9 @@ check_weights(optimized, match_cov, digits = 2)
 \arguments{
 \item{optimized}{object returned after calculating weights using \code{\link{cal_weights}}}
 
-\item{match_cov}{covariates that should be checked to see if the IPD weighted average matches the aggregate data average
-This could be same set of variables that were used to match or it can include variables that were not included to match (i.e. stratification variables)}
+\item{match_cov}{covariates that should be checked to see if the IPD weighted average matches the aggregate data
+average. This could be same set of variables that were used to match or it can include variables that were not
+included to match (i.e. stratification variables)}
 
 \item{digits}{number of digits for rounding summary table}
 }
diff --git a/man/estimate_weights.Rd b/man/estimate_weights.Rd
index 8295cdf8..d3d1151c 100644
--- a/man/estimate_weights.Rd
+++ b/man/estimate_weights.Rd
@@ -28,14 +28,17 @@ The default is \code{"BFGS"}, other options are \code{"Nelder-Mead"}, \code{"CG"
 a list with the following 4 elements,
 \describe{
 \item{data}{a data.frame, includes the input \code{data} with appended column 'weights' and 'scaled_weights'.
-Scaled weights has a summation to be the number of rows in \code{data} that has no missing value in any of the effect modifiers}
+Scaled weights has a summation to be the number of rows in \code{data} that has no missing value in any of the
+effect modifiers}
 \item{centered_colnames}{column names of centered effect modifiers in \code{data}}
-\item{nr_missing}{number of rows in \code{data} that has at least 1 missing value in specified centered effect modifiers}
+\item{nr_missing}{number of rows in \code{data} that has at least 1 missing value in specified centered effect
+modifiers}
 \item{ess}{effective sample size, square of sum divided by sum of squares}
 \item{opt}{R object returned by \code{base::optim()}, for assess convergence and other details}
 }
 }
 \description{
-Assuming data is properly processed, this function takes individual patient data (IPD) with centered covariates (effect modifiers and/or prognostic variables) as input,
-and generates weights for each individual in IPD trial that matches the chosen statistics of those covariates in Aggregated Data (AgD) trial.
+Assuming data is properly processed, this function takes individual patient data (IPD) with centered covariates
+(effect modifiers and/or prognostic variables) as input, and generates weights for each individual in IPD trial that
+matches the chosen statistics of those covariates in Aggregated Data (AgD) trial.
 }
diff --git a/man/ext_tte_transfer.Rd b/man/ext_tte_transfer.Rd
index 1ab0ab4b..588cc50d 100644
--- a/man/ext_tte_transfer.Rd
+++ b/man/ext_tte_transfer.Rd
@@ -10,6 +10,8 @@ ext_tte_transfer(dd, time_scale = "month", trt = NULL)
 \item{dd}{data frame, ADTTE read via haven::read_sas}
 
 \item{time_scale}{a character string, 'year', 'month', 'week' or 'day', time unit of median survival time}
+
+\item{trt}{values to include in treatment column}
 }
 \value{
 a data frame that can be used as input to survival::Surv
diff --git a/man/generate_survival_data.Rd b/man/generate_survival_data.Rd
index eb5ab5e5..c428ee50 100644
--- a/man/generate_survival_data.Rd
+++ b/man/generate_survival_data.Rd
@@ -22,6 +22,8 @@ generate_survival_data(
 \arguments{
 \item{N}{sample size}
 
+\item{ncov}{number of covariates to generate}
+
 \item{lambda}{scale parameter in baseline hazard function}
 
 \item{nu}{shape parameter in baseline hazard function}