Checked all functions, examples and test scripts for handling new typ…

…e=full default argument value - amended from type=standard for LE function.

R/DSR.R

@@ -62,7 +62,8 @@
 # -------------------------------------------------------------------------------------------------
 
 # define the DSR function using Dobson method
-phe_dsr <- function(data, x, n, stdpop = esp2013, stdpoptype = "vector", type = "full", confidence = 0.95, multiplier = 100000) {
+phe_dsr <- function(data, x, n, stdpop = esp2013, stdpoptype = "vector",
+                    type = "full", confidence = 0.95, multiplier = 100000) {
 
     # check required arguments present
     if (missing(data)|missing(x)|missing(n)) {

R/LifeExpectancy.R

@@ -16,9 +16,9 @@
 #'   "all", where the function returns the life expectancy values for all ages
 #'   appended onto the input table. Any other value (or vector of values) must be age bands
 #'   described by the age_contents input
-#' @param type type of output; can be "standard" or "full" (which contains
-#'   details added details on the calculation within the dataframe); quoted
-#'   string; default standard
+#' @param type type of output; can be "standard" or "full" (full contains
+#'   added details on the calculation within the dataframe); quoted
+#'   string; default full
 #' @details This function aligns with the methodology in Public Health England's
 #'   \href{https://fingertips.phe.org.uk/documents/PHE Life Expectancy Calculator.xlsm}{Life Expectancy Excel Tool}.
 #'
@@ -83,7 +83,7 @@
 #'
 #' ## OR
 #'
-#' phe_life_expectancy(df, deaths, pops, startage, le_age = c(5, 25), type = "full")
+#' phe_life_expectancy(df, deaths, pops, startage, le_age = c(5, 25), type = "standard")
 #'
 #' ## Unordered age bands example
 #' df <- data.frame(startage = c("0", "1-4", "5-9", "10 - 14", "15 - 19", "20 - 24", "25 - 29",
@@ -129,7 +129,7 @@ phe_life_expectancy <- function(data, deaths, population, startage,
                                                  20L, 25L, 30L, 35L, 40L,
                                                  45L, 50L, 55L, 60L, 65L,
                                                  70L, 75L, 80L, 85L, 90L),
-                                le_age = "all", type = "standard", confidence = 0.95) {
+                                le_age = "all", type = "full", confidence = 0.95) {
 
   # check required arguments present
   if (missing(data) | missing(deaths) | missing(population) | missing(startage)) {

R/Rates.R

@@ -24,7 +24,8 @@
 #'                  pop = rep(c(100,10000,10000,10000), each=3))
 #'
 #' phe_rate(df, obs, pop)
-#' phe_rate(df, obs, pop, type="full", confidence=99.8, multiplier=100)
+#' phe_rate(df, obs, pop, type="standard")
+#' phe_rate(df, obs, pop, confidence=99.8, multiplier=100)
 #'
 #' # grouped data frame
 #' library(dplyr)

R/SMR.R

@@ -32,13 +32,13 @@
 #'
 #' df %>%
 #'     group_by(indicatorid, year, sex) %>%
-#'     phe_smr(obs, pop, refdf$refcount, refdf$refpop)
+#'     phe_smr(obs, pop, refdf$refcount, refdf$refpop, type="standard")
 #'
 #' ## OR
 #'
 #' df %>%
 #'     group_by(indicatorid, year, sex) %>%
-#'     phe_smr(obs, pop, refdf$refcount, refdf$refpop, type="standard", confidence=99.8, refvalue=100)
+#'     phe_smr(obs, pop, refdf$refcount, refdf$refpop, confidence=99.8, refvalue=100)
 #'
 #' @section Notes: User MUST ensure that x, n, x_ref and n_ref vectors are all ordered by
 #' the same standardisation category values as records will be matched by position. \cr \cr
@@ -60,7 +60,8 @@
 # -------------------------------------------------------------------------------------------------
 
 
-phe_smr <- function(data, x, n, x_ref, n_ref, refpoptype = "vector", type = "full", confidence = 0.95, refvalue = 1) {
+phe_smr <- function(data, x, n, x_ref, n_ref, refpoptype = "vector",
+                    type = "full", confidence = 0.95, refvalue = 1) {
 
     # check required arguments present
     if (missing(data)|missing(x)|missing(n)|missing(x_ref)|missing(n_ref)) {

tests/testthat/testLifeExpectancy.R

@@ -136,7 +136,7 @@ answer2 <- cbind(df1[c(3, 7),],
                             statistic = paste("life expectancy at", c(5, 25)),
                             method = rep("Chiang, using Silcocks et al for confidence limits", 2)))
 
-test1 <- phe_life_expectancy(df1, deaths, pops, startage) %>%
+test1 <- phe_life_expectancy(df1, deaths, pops, startage, type="standard") %>%
   select(value:uppercl)
 test1.1 <- phe_life_expectancy(df1, deaths, pops, startage, confidence = 95) %>%
   select(value:uppercl)
@@ -163,7 +163,7 @@ test4 <- phe_life_expectancy(df3, deaths, pops, startage,
   select(value:uppercl)
 test5 <- phe_life_expectancy(df1, deaths, pops, startage, le_age = 5) %>%
   select(value:uppercl)
-test6 <- phe_life_expectancy(df1, deaths, pops, startage, le_age = c(5, 25), type = "full") %>%
+test6 <- phe_life_expectancy(df1, deaths, pops, startage, le_age = c(5, 25), type="full") %>%
   mutate_at(c("value", "lowercl", "uppercl"), round, digits = n)
 negative_warning <- capture_warnings(test_neg <- phe_life_expectancy(df_neg_deaths, deaths, pop, age) %>%
                                        select(value:uppercl))
@@ -188,7 +188,7 @@ multi_warnings <- capture_warnings(
 #test calculations
 test_that("LE and CIs calculate correctly",{
   expect_equal(round(test1, n), round(answer1, n),
-               info = "test default")
+               info = "test defaults but with type standard")
   expect_equal(round(test1.1, n), round(answer1, n),
                info = "test confidence = 95")
   expect_equal(round(test2, n), round(answer1, n),