Adding Bland- Altman statistical function

DESCRIPTION

@@ -88,6 +88,7 @@ Collate:
     'analyze_variables.R'
     'analyze_vars_in_cols.R'
     'argument_convention.R'
+    'bland_altman.R'
     'combination_function.R'
     'compare_variables.R'
     'control_incidence_rate.R'

R/bland_altman.R

@@ -0,0 +1,79 @@
+
+#' Bland Altman analysis
+#'
+#' @description 'r lifecycle::badge("stable")'
+#'
+#' @inheritParams argument_convention
+#' @param y ('numeric')\cr vector of numbers we want to analyze.
+#'
+#' @name s_bland_altman
+#' @details
+#' https://doi.org/10.1016/S0140-6736(86)90837-8
+#' @references
+#' @article{bland1986statistical,
+# title={Statistical methods for assessing agreement between two methods of clinical measurement},
+# author={Bland, J Martin and Altman, DouglasG},
+# journal={The lancet},
+# volume={327},
+# number={8476},
+# pages={307--310},
+# year={1986},
+# publisher={Elsevier}
+# }
+# https://cran.r-project.org/web/packages/Rdpack/vignettes/Inserting_bibtex_references.pdf
+
+#' @examples
+#' x <- seq(1, 60, 5)
+#' y <- seq(5, 50, 4)
+#' conf_level <- 0.9
+#' s_bland_altman(x, y, conf_level = conf_level)
+
+
+s_bland_altman <- function(x, y, conf_level = 0.95){
+  checkmate::assert_numeric(x, min.len = 1, any.missing = TRUE)
+  checkmate::assert_numeric(y, len = length(x), any.missing = TRUE)
+  checkmate::assert_numeric(conf_level, lower = 0, upper = 1, any.missing = TRUE)
+
+  alpha <- 1 - conf_level
+
+  ind <- complete.cases(x, y) # use only pairwise complete observations, and check if x and y have the same length
+  x <- x[ind]
+  y <- y[ind]
+  n <- length(n)                                      # number of 'observations'
+
+  if(n ==0){
+    stop("there is no valid paired data")
+  }
+
+  difference <- x - y                                 # vector of differences
+  average <- (x + y) / 2                              # vector of means
+  difference_mean <- mean(difference)                 # mean difference
+  difference_sd <- sd(difference)                     # SD of differences
+  al <- qnorm(1 - alpha / 2) * difference_sd
+  upper_agreement_limit <- difference_mean + al       # agreement limits
+  lower_agreement_limit <- difference_mean - al
+
+
+  difference_se <- difference_sd / sqrt(n)            # standard error of the mean
+  al_se <- difference_sd * sqrt(3) / sqrt(n)          # standard error of the agreement limit
+  tvalue <- qt(1 - alpha / 2, n - 1)                  # t value for 95% CI calculation
+  difference_mean_ci <- difference_se * tvalue
+  al_ci <- al_se * tvalue
+  upper_agreement_limit_ci <- c(upper_agreement_limit - al_ci, upper_agreement_limit + al_ci)
+  lower_agreement_limit_ci <- c(lower_agreement_limit - al_ci, lower_agreement_limit + al_ci)
+
+
+  list(
+    difference_mean = difference_mean,
+    ci_mean = difference_mean + c(-1, 1) * difference_mean_ci,
+    difference_sd = difference_sd,
+    difference_se = difference_se,
+    upper_agreement_limit = upper_agreement_limit,
+    lower_agreement_limit = lower_agreement_limit,
+    agreement_limit_se = al_se,
+    upper_agreement_limit_ci = upper_agreement_limit_ci,
+    lower_agreement_limit_ci = lower_agreement_limit_ci,
+    t_value = tvalue,
+    n = n
+  )
+}

tests/testthat/test-bland-altman.R

@@ -0,0 +1,56 @@
+testthat::test_that("unequal length vector gives correct error", {
+  testthat::expect_error(s_bland_altman (x = 1:5, y = 1:6, 0.95))
+})
+
+testthat::test_that("infeasible input gives correct error", {
+  testthat::expect_error(s_bland_altman (x = c('a', 'b', 'c'), y = 1:3, 0.95))
+  testthat::expect_error(s_bland_altman (x = 1:3, y = 4:6, 2))
+})
+
+
+testthat::test_that("works correctly", {
+  set.seed(1)
+  x <- rnorm(20)
+  y <- rnorm(20)
+  res <- s_bland_altman(x, y, 0.9)
+  expect <- list(
+    difference_mean = mean(x) - mean(y),
+    ci_mean = c(-0.3414723, 0.7354631),
+    difference_sd = 1.392664,
+    difference_se = 0.3114091,
+    upper_agreement_limit = 2.487724,
+    lower_agreement_limit = -2.093733,
+    agreement_limit_se = 0.5393764,
+    upper_agreement_limit_ci = c(1.555070, 3.420377),
+    lower_agreement_limit_ci = c(-3.026386,-1.161079),
+    t_value = 1.729133,
+    n = 20L
+  )
+  expect_identical(res, expect, tolerance = 1e-5)
+
+
+})
+
+
+testthat::test_that("works correctly with NA element in either vectors", {
+  set.seed(1)
+  x <- rnorm(20)
+  y <- rnorm(20)
+  x <- c(NA_real_, 2, x, NA_real_)
+  y <- c(1, NA_real_, y, 2)
+  res <- s_bland_altman(x, y, 0.9)
+  expect <- list(
+    difference_mean = 0.1969954,
+    ci_mean = c(-0.3414723, 0.7354631),
+    difference_sd = 1.392664,
+    difference_se = 0.3114091,
+    upper_agreement_limit = 2.487724,
+    lower_agreement_limit = -2.093733,
+    agreement_limit_se = 0.5393764,
+    upper_agreement_limit_ci = c(1.555070, 3.420377),
+    lower_agreement_limit_ci = c(-3.026386,-1.161079),
+    t_value = 1.729133,
+    n = 20L
+  )
+  expect_identical(res, expect)
+})