Require R 4.1

DESCRIPTION

@@ -1,6 +1,6 @@
 Title: Matching Adjusted Indirect Comparison
 Package: maicplus
-Version: 0.1.0
+Version: 0.1.1
 Date: 2024-10-29
 Authors@R: c(
    person(
@@ -44,7 +44,7 @@ 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
 Depends:
-    R (>= 3.6)
+    R (>= 4.1)
 Imports:
     graphics,
     grDevices,

NEWS.md

@@ -1,3 +1,7 @@
+# maicplus 0.1.1
+
+- bug fixes
+
 # maicplus 0.1.0
 
 - first CRAN release

R/maic_anchored.R

@@ -703,32 +703,32 @@ maic_anchored_binary <- function(res,
   res$inferential[["summary"]] <- data.frame(
     case = c("AC", "adjusted_AC", "BC", "AB", "adjusted_AB"),
     EST = c(
-      res_AC$est,
       res_AC_unadj$est,
+      res_AC$est,
       res_BC$est,
-      res_AB$est,
-      res_AB_unadj$est
+      res_AB_unadj$est,
+      res_AB$est
     ),
     LCL = c(
-      res_AC$ci_l,
       res_AC_unadj$ci_l,
+      res_AC$ci_l,
       res_BC$ci_l,
-      res_AB$ci_l,
-      res_AB_unadj$ci_l
+      res_AB_unadj$ci_l,
+      res_AB$ci_l
     ),
     UCL = c(
-      res_AC$ci_u,
       res_AC_unadj$ci_u,
+      res_AC$ci_u,
       res_BC$ci_u,
-      res_AB$ci_u,
-      res_AB_unadj$ci_u
+      res_AB_unadj$ci_u,
+      res_AB$ci_u
     ),
     pval = c(
-      res_AC$pval,
       res_AC_unadj$pval,
+      res_AC$pval,
       res_BC$pval,
-      res_AB$pval,
-      res_AB_unadj$pval
+      res_AB_unadj$pval,
+      res_AB$pval
     )
   )
   names(res$inferential[["summary"]])[2] <- eff_measure

R/maic_unanchored.R

@@ -367,7 +367,7 @@ maic_unanchored_binary <- function(res,
 
   # : fit glm for binary outcome and robust estimate with weights
   binobj_dat <- glm(RESPONSE ~ ARM, dat, family = glm_link)
-  binobj_dat_adj <- glm(RESPONSE ~ ARM, dat, weights = weights, family = glm_link) |> suppressWarnings()
+  binobj_dat_adj <- suppressWarnings(glm(RESPONSE ~ ARM, dat, weights = weights, family = glm_link))
 
   bin_robust_cov <- sandwich::vcovHC(binobj_dat_adj, type = binary_robust_cov_type)
   bin_robust_coef <- lmtest::coeftest(binobj_dat_adj, vcov. = bin_robust_cov)
@@ -424,7 +424,7 @@ maic_unanchored_binary <- function(res,
       }
       boot_dat <- rbind(boot_ipd, pseudo_ipd)
       boot_dat$ARM <- factor(boot_dat$ARM, levels = c(trt_agd, trt_ipd))
-      boot_binobj_dat_adj <- glm(RESPONSE ~ ARM, boot_dat, weights = weights, family = glm_link) |> suppressWarnings()
+      boot_binobj_dat_adj <- suppressWarnings(glm(RESPONSE ~ ARM, boot_dat, weights = weights, family = glm_link))
       c(est = coef(boot_binobj_dat_adj)[2], var = vcov(boot_binobj_dat_adj)[2, 2])
     }
 

tests/testthat/_snaps/maic_anchored.md

@@ -401,11 +401,11 @@
       testout$inferential$summary
     Output
                case        OR       LCL       UCL         pval
-      1          AC 1.3119021 0.8210000 2.0963303 2.562849e-01
-      2 adjusted_AC 1.6993007 1.2809976 2.2541985 2.354448e-04
+      1          AC 1.6993007 1.2809976 2.2541985 2.354448e-04
+      2 adjusted_AC 1.3119021 0.8210000 2.0963303 2.562849e-01
       3          BC 2.3333333 1.7458092 3.1185794 1.035032e-08
-      4          AB 0.5622438 0.3239933 0.9756933 4.061296e-02
-      5 adjusted_AB 0.7282717 0.4857575 1.0918611 1.248769e-01
+      4          AB 0.7282717 0.4857575 1.0918611 1.248769e-01
+      5 adjusted_AB 0.5622438 0.3239933 0.9756933 4.061296e-02
 
 ---
 
@@ -540,11 +540,11 @@
       testout2$inferential$summary
     Output
                case        OR       LCL       UCL         pval
-      1          AC 1.3119021 0.8210000 2.0963303 2.562849e-01
-      2 adjusted_AC 1.6993007 1.2809976 2.2541985 2.354448e-04
+      1          AC 1.6993007 1.2809976 2.2541985 2.354448e-04
+      2 adjusted_AC 1.3119021 0.8210000 2.0963303 2.562849e-01
       3          BC 2.3333333 1.7458092 3.1185794 1.035032e-08
-      4          AB 0.5622438 0.3239933 0.9756933 4.061296e-02
-      5 adjusted_AB 0.7282717 0.4857575 1.0918611 1.248769e-01
+      4          AB 0.7282717 0.4857575 1.0918611 1.248769e-01
+      5 adjusted_AB 0.5622438 0.3239933 0.9756933 4.061296e-02
 
 ---
 

vignettes/anchored_binary.Rmd

@@ -112,7 +112,7 @@ ipd$ARM <- stats::relevel(as.factor(ipd$ARM), ref = "C")
 pseudo_ipd$ARM <- stats::relevel(as.factor(pseudo_ipd$ARM), ref = "C")
 
 binobj_dat <- glm(RESPONSE ~ ARM, ipd, family = binomial(link = "logit"))
-binobj_dat_adj <- glm(RESPONSE ~ ARM, ipd, weights = weights, family = binomial(link = "logit")) |> suppressWarnings()
+binobj_dat_adj <- suppressWarnings(glm(RESPONSE ~ ARM, ipd, weights = weights, family = binomial(link = "logit")))
 binobj_agd <- glm(RESPONSE ~ ARM, pseudo_ipd, family = binomial(link = "logit"))
 
 bin_robust_cov <- sandwich::vcovHC(binobj_dat_adj, type = "HC3")

vignettes/unanchored_binary.Rmd

@@ -115,10 +115,12 @@ combined_data_binary <- rbind(
 combined_data_binary$ARM <- stats::relevel(as.factor(combined_data_binary$ARM), ref = "B")
 
 binobj_dat <- glm(RESPONSE ~ ARM, combined_data_binary, family = binomial(link = "logit"))
-binobj_dat_adj <- glm(RESPONSE ~ ARM, combined_data_binary,
-  weights = weights,
-  family = binomial(link = "logit")
-) |> suppressWarnings()
+binobj_dat_adj <- suppressWarnings(
+  glm(RESPONSE ~ ARM, combined_data_binary,
+    weights = weights,
+    family = binomial(link = "logit")
+  )
+)
 
 bin_robust_cov <- sandwich::vcovHC(binobj_dat_adj, type = "HC3")
 bin_robust_coef <- lmtest::coeftest(binobj_dat_adj, vcov. = bin_robust_cov)