CRAN release v1.0

DESCRIPTION

@@ -1,7 +1,7 @@
 Title: Matching Adjusted Indirect Comparison
 Package: maicplus
 Version: 0.1.0
-Date: 2023-03-03
+Date: 2024-10-29
 Authors@R: c(
    person(
       given = "Gregory",
@@ -36,9 +36,10 @@ Authors@R: c(
    person("MSD, Inc.", role = c("cph", "fnd")),
    person("F. Hoffmann-La Roche AG", role = c("cph", "fnd"))
    )
-Description: The maicplus package facilitates performing matching adjusted indirect comparison
+Description: 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).
+ (e.g. overall survival) or binary (e.g. objective tumor response). The method
+ is described by Signorovitch et al (2012) <doi:10.1016/j.jval.2012.05.004>.
 License: Apache License 2.0
 URL: https://github.com/hta-pharma/maicplus/, https://hta-pharma.github.io/maicplus/
 BugReports: https://github.com/hta-pharma/maicplus/issues
@@ -75,3 +76,4 @@ Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.3.2
+Config/testthat/edition: 3

NEWS.md

@@ -1,13 +1,3 @@
 # maicplus 0.1.0
 
-### New features
-
-* Add an initializer script.
-
-### Enhancements
-
-* Documentation on how to use the initialize a package.
-
-### Bug fixes
-
-* None.
+- first CRAN release

R/binary-helper.R

@@ -91,6 +91,8 @@ get_pseudo_ipd_binary <- function(binary_agd, format = c("stacked", "unstacked")
 #' @param binobj returned object from \code{stats::glm}
 #' @param legend label to indicate the binary fit
 #' @param weighted logical flag indicating whether weights have been applied in the glm fit
+#' @returns A `data.frame` containing a summary of the number of events and subjects in a logistic
+#' regression model.
 #' @examples
 #' data(adrs_sat)
 #' pseudo_adrs <- get_pseudo_ipd_binary(

R/plot_km2.R

@@ -169,6 +169,7 @@ kmplot2 <- function(weights_object,
 #' @param use_line_types a numeric vector of length up to 4, line type to the KM curves,
 #'   it will be passed to \code{lty} of \code{lines()}
 #' @example inst/examples/basic_kmplot2_ex.R
+#' @returns A Kaplan-Meier plot object created with `survminer::ggsurvplot()`.
 #' @export
 
 basic_kmplot2 <- function(kmlist,

inst/WORDLIST

@@ -15,6 +15,7 @@ binarize
 bootswatch
 Bucher
 bucher
+Chrysostomos
 Comparator
 comparator
 confounders
@@ -59,6 +60,7 @@ maicplus
 medSurv
 meier
 MGG
+Miranta
 MSD
 multivariable
 navbar

inst/examples/maic_unanchored_binary_ex.R

@@ -1,4 +1,7 @@
+#
 # unanchored example using maic_unanchored for binary outcome
+#
+
 data(centered_ipd_sat)
 data(adrs_sat)
 
@@ -7,7 +10,7 @@ centered_colnames <- grep("_CENTERED$", colnames(centered_ipd_sat), value = TRUE
 weighted_data <- estimate_weights(data = centered_ipd_sat, centered_colnames = centered_colnames)
 weighted_data2 <- estimate_weights(
   data = centered_ipd_sat, centered_colnames = centered_colnames,
-  n_boot_iteration = 500
+  n_boot_iteration = 100
 )
 
 # get dummy binary IPD
@@ -51,3 +54,5 @@ maic_unanchored(
   # binary specific args
   binary_robust_cov_type = "HC3"
 )
+
+#---------------------------------

inst/examples/maic_unanchored_ex.R

@@ -1,4 +1,6 @@
+#
 # unanchored example using maic_unanchored for time-to-event data
+#
 data(centered_ipd_sat)
 data(adtte_sat)
 data(pseudo_ipd_sat)
@@ -16,7 +18,7 @@ weighted_data2 <- estimate_weights(
   centered_colnames = grep("_CENTERED$", names(centered_ipd_sat)),
   start_val = 0,
   method = "BFGS",
-  n_boot_iteration = 500,
+  n_boot_iteration = 100,
   set_seed_boot = 1234
 )