Merge pull request #93 from nutriverse/dev

add squeacr functions as utilities; remove squeacr dependency

Author: ernestguevarra

DESCRIPTION

@@ -33,7 +33,6 @@ Imports:
     methods,
     parallel,
     parallelly,
-    squeacr,
     stats
 Suggests: 
     covr,
@@ -42,8 +41,6 @@ Suggests:
     spelling,
     testthat (>= 3.0.0),
     tibble
-Remotes:
-    rapidsurveys/squeacr
 Encoding: UTF-8
 Language: en-GB
 LazyData: true

R/03-classify_coverage.R

@@ -7,7 +7,8 @@
 #'   are in the CMAM programme.
 #' @param rec_in Number of children recovering from SAM or MAM found during the
 #'   survey who are in the programme.
-#' @inheritParams squeacr::calculate_tc
+#' @param k Correction factor. Ratio of the mean length of an untreated episode
+#'   to the mean length of a CMAM treatment episode
 #' @param threshold  Decision rule threshold/s. Should be between 0 and 1. At
 #'   least one threshold should be provided for a two-tier classifier. Two 
 #'   thresholds should be provided for a three-tier classifier. Default is a 
@@ -150,7 +151,7 @@ lqas_classify_cf <- function(cases_in, cases_out,
 
 lqas_classify_tc <- function(cases_in, cases_out, rec_in, k,
                              threshold = c(0.2, 0.5), label = FALSE) {
-  rec_out <- squeacr::calculate_rout(cases_in, cases_out, rec_in, k = k)
+  rec_out <- calculate_rout(cases_in, cases_out, rec_in, k = k)
 
   d <- (cases_in + cases_out + rec_in + rec_out) * threshold
 

R/05-post_strat_estimator.R

@@ -20,10 +20,11 @@
 #' @param u5 A numeric value for the proportion of the population that is under
 #'   years old.
 #' @param p Prevalence of SAM or MAM in the given population.
+#' @param k Correction factor. Ratio of the mean length of an untreated episode
+#'   to the mean length of a CMAM treatment episode
 #' @param cov_type Coverage estimator to report. Either *"cf"* for
 #'   *case-finding effectiveness* or *"tc"* for *treatment coverage*.
 #'   Default is *"cf"*.
-#' @inheritParams squeacr::calculate_tc
 #'
 #' @returns A list of overall coverage estimates with corresponding 95%
 #'   confidence intervals for case-finding effectiveness and treatment coverage.
@@ -141,11 +142,11 @@ estimate_coverage <- function(cov_df,
   cov_type <- match.arg(cov_type)
 
   if (cov_type == "cf") {
-    cov <- with(cov_df, squeacr::calculate_cf(cin = cases_in, cout = cases_out))
+    cov <- with(cov_df, calculate_cf(cin = cases_in, cout = cases_out))
   } else {
     cov <- with(
       cov_df, 
-      squeacr::calculate_tc(
+      calculate_tc(
         cin = cases_in, cout = cases_out, rin = rec_in, k = k
       )
     )
@@ -166,7 +167,7 @@ calculate_ci <- function(cov_df, cov_type = c("cf", "tc"), k = 3, weights) {
   } else {
     rec_out <- with(
       cov_df,
-      squeacr::calculate_rout(cases_in, cases_out, rec_in, k = k)
+      calculate_rout(cases_in, cases_out, rec_in, k = k)
     )
 
     c <- cov_df$cases_in + cov_df$rec_in

R/06-chi-square.R

@@ -92,7 +92,7 @@ calculate_x2_stat <- function(cases_in, cases_out, rec_in, k = 3) {
   observed_tc <- cases_in + rec_in
 
   ## Calculate rec_out ----
-  rec_out <- squeacr::calculate_rout(
+  rec_out <- calculate_rout(
     cin = cases_in, cout = cases_out, rin = rec_in, k = k
   )
 

R/utils.R

@@ -169,4 +169,37 @@ check_p <- function(p) {
 }
 
 
+#'
+#' Calculate r_out
+#'
+#' @keywords internal
+#'  
+
+calculate_rout <- function(cin, cout, rin, k = 3) {
+  floor((1 / k) * (rin * ((cin + 1 + cout) / (cin + 1)) - rin))
+}
+
+
+#'
+#' Calculate case-finding effectiveness
+#' 
+#' @keywords internal
+#'
+
+calculate_cf <- function(cin, cout) {
+  cin / (cin + cout)
+}
+
+
+#'
+#' Calculate treatment coverage
+#' 
+#' @keywords internal
+#'
+
+calculate_tc <- function(cin, cout, rin, k = 3) {
+  rout <- calculate_rout(cin = cin, cout = cout, rin = rin, k = k)
+  (cin + rin) / (cin + cout + rin + rout)
+}
+
 

man/calculate_cf.Rd

@@ -9,4 +9,6 @@
 library(testthat)
 library(sleacr)
 
+set.seed(1972)
+
 test_check("sleacr")