diff --git a/DESCRIPTION b/DESCRIPTION
index 4bf5e4c0..b5125cda 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,11 +1,12 @@
-Type: Package
+Title: Matching Adjusted Indirect Comparison
 Package: maicplus
-Title: R Package Template
 Version: 0.1.0
 Date: 2023-03-03
 Authors@R:
     person("hta-pharma", , , "hta-pharma@example.com", role = c("aut", "cre"))
-Description: R package template with GitHub Actions workflows included.
+Description: The maicplus package facilitates performing matching adjusted indirect comparison
+ (MAIC) analysis where the endpoint of interest is either time-to-event
+ (e.g. overall survival) or binary (e.g. objective tumor response).
 License: Apache License 2.0
 URL: https://github.com/hta-pharma/maicplus/
 BugReports: https://github.com/hta-pharma/maicplus/issues
@@ -16,10 +17,12 @@ Imports:
     stats,
     survival,
     DescTools,
-    MASS
+    MASS,
+    boot
 Suggests:
     knitr,
-    testthat (>= 2.0)
+    testthat (>= 2.0),
+    ggplot2
 VignetteBuilder:
     knitr
 biocViews:
diff --git a/NAMESPACE b/NAMESPACE
index 3dcacc76..23412536 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -15,15 +15,8 @@ export(process_agd)
 export(resid_plot)
 export(survfit_makeup)
 import(DescTools)
+import(MASS)
+import(boot)
+import(graphics)
 import(stats)
-importFrom(graphics,abline)
-importFrom(graphics,axis)
-importFrom(graphics,hist)
-importFrom(graphics,legend)
-importFrom(graphics,lines)
-importFrom(graphics,par)
-importFrom(graphics,points)
-importFrom(survival,Surv)
-importFrom(survival,cox.zph)
-importFrom(survival,coxph)
-importFrom(survival,survfit)
+import(survival)
diff --git a/R/bucher.R b/R/bucher.R
index 79388cca..def049f2 100644
--- a/R/bucher.R
+++ b/R/bucher.R
@@ -24,9 +24,10 @@
 #'   \item{pval}{p-value of Z-test, with null hypothesis that \code{est} is zero}
 #' }
 #' @export
-#' @import stats
-#'
 #' @examples
+#' trt <- list(est = 1.1, se = 0.2)
+#' com <- list(est = 1.3, se = 0.18)
+#' bucher(trt, com, conf_lv = 0.9)
 bucher <- function(trt, com, conf_lv = 0.95) {
   est <- trt$est - com$est
   se <- sqrt(trt$se^2 + com$se^2)
diff --git a/R/maic_unanchored_tte.R b/R/maic_unanchored_tte.R
index 86583ff1..8d7e0bdc 100644
--- a/R/maic_unanchored_tte.R
+++ b/R/maic_unanchored_tte.R
@@ -16,12 +16,9 @@
 #'   \item time - numeric column, observation time of the \code{status}; unit in days
 #' }
 #'
-#' @return
-#' @importFrom survival Surv survfit coxph cox.zph
-#' @importFrom graphics par axis lines points legend abline
+#' @return A list of KM plot, analysis table, and diagnostic plot
 #' @export
-#'
-#' @examples
+
 maic_tte_unanchor <- function(useWt, dat, dat_ext, trt, trt_ext,
                               time_scale = "month", endpoint_name = "OS",
                               transform = "log") {
@@ -53,7 +50,7 @@ maic_tte_unanchor <- function(useWt, dat, dat_ext, trt, trt_ext,
   kmobj_adj <- survfit(Surv(time, status) ~ treatment, dat, weights = dat$weight, conf.type = "log-log")
 
   par(cex.main = 0.85)
-  km_makeup(kmobj, kmobj_adj,
+  km_plot(kmobj, kmobj_adj,
     time_scale = time_scale,
     trt = trt, trt_ext = trt_ext,
     endpoint_name = endpoint_name
diff --git a/R/maicplus-package.R b/R/maicplus-package.R
new file mode 100644
index 00000000..900cae40
--- /dev/null
+++ b/R/maicplus-package.R
@@ -0,0 +1,16 @@
+#' @keywords internal
+"_PACKAGE"
+
+# The following block is used by usethis to automatically manage
+# roxygen namespace tags. Modify with care!
+## usethis namespace: start
+## usethis namespace: end
+NULL
+
+#' @import graphics
+#' @import stats
+#' @import survival
+#' @import DescTools
+#' @import MASS
+#' @import boot
+NULL
diff --git a/R/matching.R b/R/matching.R
index 582a9818..aeb64447 100644
--- a/R/matching.R
+++ b/R/matching.R
@@ -1,12 +1,10 @@
 # Functions for matching step: estimation of individual weights
 
-# functions to be exported ---------------------------------------
-
 #' 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.
+#' 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 to match the covariates in aggregate data.
 #'
 #' @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
@@ -27,8 +25,7 @@
 #'   \item{opt}{R object returned by \code{base::optim()}, for assess convergence and other details}
 #' }
 #' @export
-#'
-#' @examples
+
 estimate_weights <- function(data, centered_colnames = NULL, start_val = 0, method = "BFGS", ...) {
   # pre check
   ch1 <- is.data.frame(data)
@@ -116,7 +113,7 @@ estimate_weights <- function(data, centered_colnames = NULL, start_val = 0, meth
 #' @param main_title a character string, main title of the plot
 #'
 #' @return a plot of unscaled or scaled weights
-#' @importFrom graphics hist
+#' @examples
 #' @export
 
 plot_weights <- function(wt, bin_col = "#6ECEB2", vline_col = "#688CE8", main_title = "Unscaled Individual Weights") {
@@ -155,13 +152,13 @@ plot_weights <- function(wt, bin_col = "#6ECEB2", vline_col = "#688CE8", main_ti
 #' This function checks to see if the optimization is done properly by checking the covariate averages
 #' before and after adjustment.
 #'
-#' @param optimized object returned after calculating weights using \code{\link{estimate_weights}}
+#' @param weighted_data object returned after calculating weights using \code{\link{estimate_weights}}
 #' @param processed_agd a data frame, object returned after using \code{\link{process_agd}} or
 #' aggregated data following the same naming convention
 #'
 #' @import DescTools
 #'
-#' @return data.frame of weighted and unweighted covariate averages of the IPD
+#' @return data.frame of weighted and unweighted covariate averages of the IPD, and average of aggregate data
 #' @export
 #'
 #' @examples
@@ -209,14 +206,15 @@ plot_weights <- function(wt, bin_col = "#6ECEB2", vline_col = "#688CE8", main_ti
 #' )
 #'
 #' check <- check_weights(
-#'   optimized = match_res,
+#'   weighted_data = match_res,
 #'   processed_agd = target_pop
 #' )
 #'
 #' print(check)
-check_weights <- function(optimized, processed_agd) {
-  ipd_with_weights <- optimized$data
-  match_cov <- optimized$centered_colnames
+#'
+check_weights <- function(weighted_data, processed_agd) {
+  ipd_with_weights <- weighted_data$data
+  match_cov <- weighted_data$centered_colnames
 
   # if algorithm is correct, all centered columns should have a weighted summation to a very small number around zero
   num_check <- ipd_with_weights$weights %*% as.matrix(ipd_with_weights[, match_cov, drop = FALSE])
diff --git a/R/process_data.R b/R/process_data.R
index 57db8ff3..96df5d1d 100644
--- a/R/process_data.R
+++ b/R/process_data.R
@@ -18,7 +18,6 @@
 #' by legal suffixes (i.e. MEAN, MEDIAN, SD, COUNT, or PROP).
 #'
 #' @examples
-#' # example
 #' target_pop <- read.csv(system.file("extdata", "aggregate_data_example_1.csv",
 #'   package = "maicplus", mustWork = TRUE
 #' ))
@@ -33,20 +32,6 @@
 #' target_pop2 <- process_agd(target_pop2)
 #' target_pop3 <- process_agd(target_pop3)
 #'
-#' # another example
-#' target_pop <- data.frame(
-#'   STUDY = "Study_XXXX",
-#'   ARM = "Total",
-#'   N = 300,
-#'   AGE_MEAN = 51,
-#'   AGE_MEDIAN = 49,
-#'   AGE_SD = 3.25,
-#'   SEX_MALE_COUNT = 147,
-#'   ECOG0_COUNT = 105,
-#'   SMOKE_PROP = 58 / 290
-#' )
-#' process_agd(target_pop)
-#'
 #' @return pre-processed aggregate level data
 #' @export
 
@@ -155,7 +140,7 @@ dummize_ipd <- function(raw_ipd, dummize_cols, dummize_ref_level) {
 #'
 #' @param ipd IPD variable names should match the aggregate data names without the suffix.
 #' This would involve either changing the aggregate data name or the ipd name.
-#' For instance, if we binarize SEX variable with MALE as a reference, function names the new variable as SEX_MALE.
+#' For instance, if we binarize SEX variable with MALE as a reference using [dummize_ipd], function names the new variable as SEX_MALE.
 #' In this case, SEX_MALE should also be available in the aggregate data.
 #' @param agd pre-processed aggregate data which contain STUDY, ARM, and N. Variable names should be followed
 #' by legal suffixes (i.e. MEAN, MEDIAN, SD, or PROP). Note that COUNT suffix is no longer accepted.
@@ -247,13 +232,14 @@ complete_agd <- function(use_agd) {
 }
 
 
-#' helper function: transform TTE ADaM data to suitable input for survival R pkg
+#' helper function: transform TTE ADaM data to suitable input for survival R package
 #'
 #' @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) {
   time_units <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
 
diff --git a/R/survival-helper.R b/R/survival-helper.R
index 8f22818d..b9b3dd03 100644
--- a/R/survival-helper.R
+++ b/R/survival-helper.R
@@ -1,6 +1,6 @@
 #' helper function: makeup to get median survival time from a `survival::survfit` object
 #'
-#' extract and display median survival time with confidence interval
+#' Extract and display median survival time with confidence interval
 #'
 #' @param km_fit returned object from \code{survival::survfit}
 #' @param legend a character string, name used in 'type' column in returned data frame
@@ -9,13 +9,13 @@
 #' @return a data frame with a index column 'type', median survival time and confidence interval
 #' @export
 medSurv_makeup <- function(km_fit, legend = "before matching", time_scale) {
-  timeUnit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
+  time_unit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
 
-  if (!time_scale %in% names(timeUnit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
+  if (!time_scale %in% names(time_unit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
 
   # km_fit is the returned object from survival::survfit
   km_fit <- summary(km_fit)$table
-  km_fit[, 5:ncol(km_fit)] <- km_fit[, 5:ncol(km_fit)] / timeUnit[[time_scale]]
+  km_fit[, 5:ncol(km_fit)] <- km_fit[, 5:ncol(km_fit)] / time_unit[[time_scale]]
 
   toyadd <- data.frame(
     treatment = gsub("treatment=", "", rownames(km_fit)),
@@ -30,13 +30,12 @@ medSurv_makeup <- function(km_fit, legend = "before matching", time_scale) {
 
 
 
-#' helper function: makeup `survival::survfit` object for km plot
+#' Helper function to select a set of variables used for Kaplan-Meier plot
 #'
 #' @param km_fit returned object from \code{survival::survfit}
-#'
+#' @return a list of data frames of variables from \code{survival::survfit}. Data frames are divided by treatment.
 #' @export
-#'
-#' @return a list of data frames, one element per treatment
+
 survfit_makeup <- function(km_fit) {
   kmdat <- data.frame(
     time = km_fit$time,
@@ -60,14 +59,15 @@ survfit_makeup <- function(km_fit) {
 #' @param km_fit_after returned object from \code{survival::survfit} after adjustment
 #' @param time_scale a character string, 'year', 'month', 'week' or 'day', time unit of median survival time
 #' @param trt  a character string, name of the interested treatment in internal trial (real IPD)
-#' @param trt_ext character string, name of the interested comparator in external trial used to subset \code{dat_ext} (pseudo IPD)
+#' @param trt_ext character string, name of the interested comparator in external trial used to
+#' subset \code{dat_ext} (pseudo IPD)
 #' @param endpoint_name a character string, name of the endpoint
 #'
 #' @return a KM plot
-km_makeup <- function(km_fit_before, km_fit_after = NULL, time_scale, trt, trt_ext, endpoint_name = "") {
-  timeUnit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
+km_plot <- function(km_fit_before, km_fit_after = NULL, time_scale, trt, trt_ext, endpoint_name = "") {
+  time_unit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
 
-  if (!time_scale %in% names(timeUnit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
+  if (!time_scale %in% names(time_unit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
 
   # prepare data for plot
   pd_be <- survfit_makeup(km_fit_before)
@@ -79,12 +79,12 @@ km_makeup <- function(km_fit_before, km_fit_after = NULL, time_scale, trt, trt_e
   } else {
     max_t <- max(km_fit_before$time)
   }
-  t_range <- c(0, (max_t / timeUnit[[time_scale]]) * 1.07)
+  t_range <- c(0, (max_t / time_unit[[time_scale]]) * 1.07)
 
   # base plot
   par(mfrow = c(1, 1), bty = "n", tcl = -0.15, mgp = c(2.3, 0.5, 0))
   plot(0, 0,
-    type = "n", xlab = paste0("Time in", time_scale), ylab = "Survival Probability",
+    type = "n", xlab = paste0("Time in ", time_scale), ylab = "Survival Probability",
     ylim = c(0, 1), xlim = t_range, yaxt = "n",
     main = paste0(
       "Kaplan-Meier Curves of Comparator ", ifelse(!is.null(km_fit_after), "(AgD) ", ""),
@@ -94,29 +94,29 @@ km_makeup <- function(km_fit_before, km_fit_after = NULL, time_scale, trt, trt_e
   )
   axis(2, las = 1)
 
-  # add km lines from external trail
+  # add km lines from external trial
   lines(
     y = pd_be[[trt_ext]]$surv,
-    x = (pd_be[[trt_ext]]$time / timeUnit[[time_scale]]), col = "#5450E4",
+    x = (pd_be[[trt_ext]]$time / time_unit[[time_scale]]), col = "#5450E4",
     type = "s"
   )
   tmpid <- pd_be[[trt_ext]]$censor == 1
   points(
     y = pd_be[[trt_ext]]$surv[tmpid],
-    x = (pd_be[[trt_ext]]$time[tmpid] / timeUnit[[time_scale]]),
+    x = (pd_be[[trt_ext]]$time[tmpid] / time_unit[[time_scale]]),
     col = "#5450E4", pch = 3, cex = 0.7
   )
 
   # add km lines from internal trial before adjustment
   lines(
     y = pd_be[[trt]]$surv,
-    x = (pd_be[[trt]]$time / timeUnit[[time_scale]]), col = "#00857C",
+    x = (pd_be[[trt]]$time / time_unit[[time_scale]]), col = "#00857C",
     type = "s"
   )
   tmpid <- pd_be[[trt]]$censor == 1
   points(
     y = pd_be[[trt]]$surv[tmpid],
-    x = (pd_be[[trt]]$time[tmpid] / timeUnit[[time_scale]]),
+    x = (pd_be[[trt]]$time[tmpid] / time_unit[[time_scale]]),
     col = "#00857C", pch = 3, cex = 0.7
   )
 
@@ -124,13 +124,13 @@ km_makeup <- function(km_fit_before, km_fit_after = NULL, time_scale, trt, trt_e
   if (!is.null(km_fit_after)) {
     lines(
       y = pd_af[[trt]]$surv,
-      x = (pd_af[[trt]]$time / timeUnit[[time_scale]]), col = "#6ECEB2", lty = 2,
+      x = (pd_af[[trt]]$time / time_unit[[time_scale]]), col = "#6ECEB2", lty = 2,
       type = "s"
     )
     tmpid <- pd_af[[trt]]$censor == 1
     points(
       y = pd_af[[trt]]$surv[tmpid],
-      x = (pd_af[[trt]]$time[tmpid] / timeUnit[[time_scale]]),
+      x = (pd_af[[trt]]$time[tmpid] / time_unit[[time_scale]]),
       col = "#6ECEB2", pch = 3, cex = 0.7
     )
   }
@@ -142,7 +142,7 @@ km_makeup <- function(km_fit_before, km_fit_after = NULL, time_scale, trt, trt_e
     legend = c(
       paste0("Comparator: ", trt_ext),
       paste0("Treatment: ", trt),
-      paste0("Treatment: ", trt, "(with weights)")
+      paste0("Treatment: ", trt, " (with weights)")
     )[use_leg]
   )
 }
@@ -161,15 +161,20 @@ km_makeup <- function(km_fit_before, km_fit_after = NULL, time_scale, trt, trt_e
 #'
 #' @return a plot
 #' @export
-log_cum_haz_plot <- function(clldat, time_scale, log_time = TRUE, endpoint_name = "", subtitle = "", exclude_censor = TRUE) {
-  timeUnit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
-  if (!time_scale %in% names(timeUnit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
+log_cum_haz_plot <- function(clldat,
+                             time_scale,
+                             log_time = TRUE,
+                             endpoint_name = "",
+                             subtitle = "",
+                             exclude_censor = TRUE) {
+  time_unit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
+  if (!time_scale %in% names(time_unit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
 
   if (exclude_censor) {
     clldat <- lapply(clldat, function(xxt) xxt[xxt$censor == 0, , drop = FALSE])
   }
 
-  all.times <- do.call(rbind, clldat)$time / timeUnit[[time_scale]]
+  all.times <- do.call(rbind, clldat)$time / time_unit[[time_scale]]
   if (log_time) all.times <- log(all.times)
   t_range <- range(all.times)
   y_range <- range(log(do.call(rbind, clldat)$cumhaz))
@@ -190,7 +195,7 @@ log_cum_haz_plot <- function(clldat, time_scale, log_time = TRUE, endpoint_name
   cols <- c("dodgerblue3", "firebrick3")
   pchs <- c(1, 4)
   for (i in seq_along(clldat)) {
-    use_x <- (clldat[[i]]$time / timeUnit[[time_scale]])
+    use_x <- (clldat[[i]]$time / time_unit[[time_scale]])
     if (log_time) use_x <- log(use_x)
 
     lines(
@@ -222,18 +227,18 @@ log_cum_haz_plot <- function(clldat, time_scale, log_time = TRUE, endpoint_name
 #' @export
 
 resid_plot <- function(coxobj, time_scale = "month", log_time = TRUE, endpoint_name = "", subtitle = "") {
-  timeUnit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
-  if (!time_scale %in% names(timeUnit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
+  time_unit <- list("year" = 365.24, "month" = 30.4367, "week" = 7, "day" = 1)
+  if (!time_scale %in% names(time_unit)) stop("time_scale has to be 'year', 'month', 'week' or 'day'")
 
   schresid <- residuals(coxobj, type = "schoenfeld")
-  plotX <- as.numeric(names(schresid)) / timeUnit[[time_scale]]
-  if (log_time) plotX <- log(plotX)
+  plot_x <- as.numeric(names(schresid)) / time_unit[[time_scale]]
+  if (log_time) plot_x <- log(plot_x)
   par(mfrow = c(1, 1), bty = "n", tcl = -0.15, mgp = c(2.3, 0.5, 0))
   plot(schresid ~ plotX,
     cex = 0.9, col = "navyblue", yaxt = "n",
     ylab = "Unscaled Schoenfeld Residual", xlab = paste0(ifelse(log_time, "Log-", ""), "Time in ", time_scale),
     main = paste0(
-      "Diagnosis Plot: Unscaled Schoenfeld Residual\nEndpoint: ", endpoint_name,
+      "Diagnostic Plot: Unscaled Schoenfeld Residual\nEndpoint: ", endpoint_name,
       ifelse(subtitle == "", "", "\n"), subtitle
     )
   )
diff --git a/inst/extdata/adsl.csv b/inst/extdata/adsl.csv
index 112719f1..23447c16 100644
--- a/inst/extdata/adsl.csv
+++ b/inst/extdata/adsl.csv
@@ -1,501 +1,501 @@
-"USUBJID","ARM","AGE","SEX","SMOKE","ECOG0"
-"001","A",45,"Male",0,0
-"002","A",71,"Male",0,0
-"003","A",58,"Male",1,1
-"004","A",48,"Female",0,1
-"005","A",69,"Male",0,1
-"006","A",48,"Female",0,1
-"007","A",47,"Male",1,0
-"008","A",61,"Male",1,0
-"009","A",54,"Female",1,1
-"010","A",56,"Female",1,0
-"011","A",63,"Female",0,0
-"012","A",50,"Female",0,0
-"013","A",57,"Male",0,1
-"014","A",62,"Female",1,1
-"015","A",57,"Female",0,1
-"016","A",66,"Male",0,0
-"017","A",75,"Male",1,1
-"018","A",47,"Female",0,0
-"019","A",57,"Male",0,0
-"020","A",54,"Male",0,0
-"021","A",55,"Male",1,0
-"022","A",64,"Male",0,1
-"023","A",53,"Female",1,0
-"024","A",58,"Male",1,1
-"025","A",47,"Male",0,0
-"026","A",60,"Female",1,0
-"027","A",49,"Female",0,1
-"028","A",55,"Female",0,0
-"029","A",66,"Female",0,1
-"030","A",58,"Male",0,1
-"031","A",49,"Male",0,1
-"032","A",61,"Male",0,0
-"033","A",66,"Male",1,0
-"034","A",45,"Male",0,0
-"035","A",59,"Female",1,1
-"036","A",74,"Female",1,0
-"037","A",73,"Female",0,0
-"038","A",74,"Male",0,1
-"039","A",54,"Male",0,0
-"040","A",58,"Female",1,1
-"041","A",61,"Female",0,1
-"042","A",47,"Female",1,1
-"043","A",73,"Female",1,1
-"044","A",68,"Male",0,0
-"045","A",49,"Female",0,0
-"046","A",71,"Female",0,0
-"047","A",70,"Male",0,1
-"048","A",62,"Female",1,0
-"049","A",49,"Male",0,0
-"050","A",74,"Female",0,0
-"051","A",46,"Female",0,1
-"052","A",68,"Female",1,0
-"053","A",46,"Male",1,0
-"054","A",75,"Female",1,1
-"055","A",47,"Female",0,0
-"056","A",56,"Male",0,1
-"057","A",72,"Female",0,0
-"058","A",57,"Male",1,1
-"059","A",46,"Male",0,0
-"060","A",56,"Female",1,1
-"061","A",73,"Male",0,1
-"062","A",60,"Female",1,1
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diff --git a/inst/extdata/aggregate_data_example_2.csv b/inst/extdata/aggregate_data_example_2.csv
index 30b9d510..19c682a5 100644
--- a/inst/extdata/aggregate_data_example_2.csv
+++ b/inst/extdata/aggregate_data_example_2.csv
@@ -1,3 +1,3 @@
 STUDY,ARM,N,AGE_MEAN,AGE_MEDIAN,AGE_SD,SEX_MALE_COUNT,ECOG0_COUNT,SMOKE_COUNT
 Study_XXXX,Intervention,149,49,50,3.10,72,53,29
-Study_XXXX,Comparator,151,54,53,3.32,75,52,29
\ No newline at end of file
+Study_XXXX,Comparator,151,54,53,3.32,75,52,29
diff --git a/inst/extdata/aggregate_data_example_3.csv b/inst/extdata/aggregate_data_example_3.csv
index 2a96102e..e278b7d9 100644
--- a/inst/extdata/aggregate_data_example_3.csv
+++ b/inst/extdata/aggregate_data_example_3.csv
@@ -1,4 +1,4 @@
 STUDY,ARM,N,AGE_MEAN,AGE_MEDIAN,AGE_SD,SEX_MALE_COUNT,SEX_MALE_PROP,ECOG0_PROP,SMOKE_COUNT
 Study_XXXX,Total,300,51,49,3.25,146,0.49,0.49,58
 Study_XXXX,Intervention,,,,,,,,
-Study_XXXX,Comparator,,,,,,,,
\ No newline at end of file
+Study_XXXX,Comparator,,,,,,,,
diff --git a/man/bucher.Rd b/man/bucher.Rd
index df3f8b17..23ab391e 100644
--- a/man/bucher.Rd
+++ b/man/bucher.Rd
@@ -31,3 +31,8 @@ Given two estimated treatment effects of A vs. C and B vs. C
 derive the adjusted treatment of A vs. B using Bucher method,
 with two-sided confidence limits and Z-test p-value
 }
+\examples{
+trt <- list(est = 1.1, se = 0.2)
+com <- list(est = 1.3, se = 0.18)
+bucher(trt, com, conf_lv = 0.9)
+}
diff --git a/man/center_ipd.Rd b/man/center_ipd.Rd
index 0446773a..6ecf390d 100644
--- a/man/center_ipd.Rd
+++ b/man/center_ipd.Rd
@@ -9,7 +9,7 @@ center_ipd(ipd, agd)
 \arguments{
 \item{ipd}{IPD variable names should match the aggregate data names without the suffix.
 This would involve either changing the aggregate data name or the ipd name.
-For instance, if we binarize SEX variable with MALE as a reference, function names the new variable as SEX_MALE.
+For instance, if we binarize SEX variable with MALE as a reference using \link{dummize_ipd}, function names the new variable as SEX_MALE.
 In this case, SEX_MALE should also be available in the aggregate data.}
 
 \item{agd}{pre-processed aggregate data which contain STUDY, ARM, and N. Variable names should be followed
diff --git a/man/check_weights.Rd b/man/check_weights.Rd
index 1848c67f..e16ac18e 100644
--- a/man/check_weights.Rd
+++ b/man/check_weights.Rd
@@ -5,7 +5,7 @@
 \alias{print.maicplus_check_weights}
 \title{Check to see if weights are optimized correctly}
 \usage{
-check_weights(optimized, processed_agd)
+check_weights(weighted_data, processed_agd)
 
 \method{print}{maicplus_check_weights}(
   x,
@@ -17,7 +17,7 @@ check_weights(optimized, processed_agd)
 )
 }
 \arguments{
-\item{optimized}{object returned after calculating weights using \code{\link{estimate_weights}}}
+\item{weighted_data}{object returned after calculating weights using \code{\link{estimate_weights}}}
 
 \item{processed_agd}{a data frame, object returned after using \code{\link{process_agd}} or
 aggregated data following the same naming convention}
@@ -35,7 +35,7 @@ aggregated data following the same naming convention}
 \item{...}{further arguments to \link{print.data.frame}}
 }
 \value{
-data.frame of weighted and unweighted covariate averages of the IPD
+data.frame of weighted and unweighted covariate averages of the IPD, and average of aggregate data
 }
 \description{
 This function checks to see if the optimization is done properly by checking the covariate averages
@@ -91,9 +91,10 @@ match_res <- estimate_weights(
 )
 
 check <- check_weights(
-  optimized = match_res,
+  weighted_data = match_res,
   processed_agd = target_pop
 )
 
 print(check)
+
 }
diff --git a/man/estimate_weights.Rd b/man/estimate_weights.Rd
index d3d1151c..d40060cf 100644
--- a/man/estimate_weights.Rd
+++ b/man/estimate_weights.Rd
@@ -38,7 +38,7 @@ modifiers}
 }
 }
 \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.
+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 to match the covariates in aggregate data.
 }
diff --git a/man/ext_tte_transfer.Rd b/man/ext_tte_transfer.Rd
index 588cc50d..8210753d 100644
--- a/man/ext_tte_transfer.Rd
+++ b/man/ext_tte_transfer.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/process_data.R
 \name{ext_tte_transfer}
 \alias{ext_tte_transfer}
-\title{helper function: transform TTE ADaM data to suitable input for survival R pkg}
+\title{helper function: transform TTE ADaM data to suitable input for survival R package}
 \usage{
 ext_tte_transfer(dd, time_scale = "month", trt = NULL)
 }
@@ -17,5 +17,5 @@ ext_tte_transfer(dd, time_scale = "month", trt = NULL)
 a data frame that can be used as input to survival::Surv
 }
 \description{
-helper function: transform TTE ADaM data to suitable input for survival R pkg
+helper function: transform TTE ADaM data to suitable input for survival R package
 }
diff --git a/man/km_makeup.Rd b/man/km_plot.Rd
similarity index 88%
rename from man/km_makeup.Rd
rename to man/km_plot.Rd
index e218cc2c..c786013e 100644
--- a/man/km_makeup.Rd
+++ b/man/km_plot.Rd
@@ -1,10 +1,10 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/survival-helper.R
-\name{km_makeup}
-\alias{km_makeup}
+\name{km_plot}
+\alias{km_plot}
 \title{helper function: KM plot with unadjusted and adjusted KM}
 \usage{
-km_makeup(
+km_plot(
   km_fit_before,
   km_fit_after = NULL,
   time_scale,
@@ -22,7 +22,8 @@ km_makeup(
 
 \item{trt}{a character string, name of the interested treatment in internal trial (real IPD)}
 
-\item{trt_ext}{character string, name of the interested comparator in external trial used to subset \code{dat_ext} (pseudo IPD)}
+\item{trt_ext}{character string, name of the interested comparator in external trial used to
+subset \code{dat_ext} (pseudo IPD)}
 
 \item{endpoint_name}{a character string, name of the endpoint}
 }
diff --git a/man/maic_tte_unanchor.Rd b/man/maic_tte_unanchor.Rd
index 1cdd650a..30360592 100644
--- a/man/maic_tte_unanchor.Rd
+++ b/man/maic_tte_unanchor.Rd
@@ -32,6 +32,9 @@ maic_tte_unanchor(
 
 \item{transform}{a character string, pass to \code{\link[survival]{cox.zph}}}
 }
+\value{
+A list of KM plot, analysis table, and diagnostic plot
+}
 \description{
 Unanchored MAIC for time-to-event endpoint
 }
diff --git a/man/maicplus-package.Rd b/man/maicplus-package.Rd
new file mode 100644
index 00000000..5e91779e
--- /dev/null
+++ b/man/maicplus-package.Rd
@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/maicplus-package.R
+\docType{package}
+\name{maicplus-package}
+\alias{maicplus}
+\alias{maicplus-package}
+\title{maicplus: Matching Adjusted Indirect Comparison}
+\description{
+The maicplus package facilitates performing matching adjusted indirect comparison (MAIC) analysis where the endpoint of interest is either time-to-event (e.g. overall survival) or binary (e.g. objective tumor response).
+}
+\seealso{
+Useful links:
+\itemize{
+  \item \url{https://github.com/hta-pharma/maicplus/}
+  \item Report bugs at \url{https://github.com/hta-pharma/maicplus/issues}
+}
+
+}
+\author{
+\strong{Maintainer}: hta-pharma \email{hta-pharma@example.com}
+
+}
+\keyword{internal}
diff --git a/man/medSurv_makeup.Rd b/man/medSurv_makeup.Rd
index 77b7b894..68c0cb3d 100644
--- a/man/medSurv_makeup.Rd
+++ b/man/medSurv_makeup.Rd
@@ -17,5 +17,5 @@ medSurv_makeup(km_fit, legend = "before matching", time_scale)
 a data frame with a index column 'type', median survival time and confidence interval
 }
 \description{
-extract and display median survival time with confidence interval
+Extract and display median survival time with confidence interval
 }
diff --git a/man/process_agd.Rd b/man/process_agd.Rd
index 7dc640c4..d14e13e9 100644
--- a/man/process_agd.Rd
+++ b/man/process_agd.Rd
@@ -25,7 +25,6 @@ sample size differs for each variable, one option is to specify proportion direc
 _PROP.
 }
 \examples{
-# example
 target_pop <- read.csv(system.file("extdata", "aggregate_data_example_1.csv",
   package = "maicplus", mustWork = TRUE
 ))
@@ -40,18 +39,4 @@ target_pop <- process_agd(target_pop)
 target_pop2 <- process_agd(target_pop2)
 target_pop3 <- process_agd(target_pop3)
 
-# another example
-target_pop <- data.frame(
-  STUDY = "Study_XXXX",
-  ARM = "Total",
-  N = 300,
-  AGE_MEAN = 51,
-  AGE_MEDIAN = 49,
-  AGE_SD = 3.25,
-  SEX_MALE_COUNT = 147,
-  ECOG0_COUNT = 105,
-  SMOKE_PROP = 58 / 290
-)
-process_agd(target_pop)
-
 }
diff --git a/man/survfit_makeup.Rd b/man/survfit_makeup.Rd
index 6c5b3557..ed253440 100644
--- a/man/survfit_makeup.Rd
+++ b/man/survfit_makeup.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/survival-helper.R
 \name{survfit_makeup}
 \alias{survfit_makeup}
-\title{helper function: makeup \code{survival::survfit} object for km plot}
+\title{Helper function to select a set of variables used for Kaplan-Meier plot}
 \usage{
 survfit_makeup(km_fit)
 }
@@ -10,8 +10,8 @@ survfit_makeup(km_fit)
 \item{km_fit}{returned object from \code{survival::survfit}}
 }
 \value{
-a list of data frames, one element per treatment
+a list of data frames of variables from \code{survival::survfit}. Data frames are divided by treatment.
 }
 \description{
-helper function: makeup \code{survival::survfit} object for km plot
+Helper function to select a set of variables used for Kaplan-Meier plot
 }