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Update R, tests, man and vignettes
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R/functions.R

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man/get_manual_mean.Rd

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man/vimc.rpkg.template-package.Rd

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man/vimcheck-package.Rd

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tests/spelling.R

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if (requireNamespace("spelling", quietly = TRUE)) {
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if (requireNamespace('spelling', quietly = TRUE))
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spelling::spell_check_test(
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vignettes = TRUE,
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error = FALSE,
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skip_on_cran = TRUE
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)
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}

tests/testthat.R

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# * https://testthat.r-lib.org/articles/special-files.html
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library(testthat)
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library(vimc.rpkg.template)
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library(vimcheck)
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test_check("vimc.rpkg.template")
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test_check("vimcheck")

tests/testthat/helper-state.R

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# function, or more conveniently with the `withr` package.
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# We add a test on R >= 4.0.0 because some functions such as
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# `globalCallingHandlers()` did not exist before.
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get_pars_toreset <- function() {
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pars <- par(no.readonly = TRUE)
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# The following params are set and modified automatically by plot(), as
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# documented in ?plot.window() and we:
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# 1. have no control over them
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# 2. do not care about resetting them
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pars <- pars[!names(pars) %in% c("usr", "xaxp", "yaxp")]
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}
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if (getRversion() >= "4.0.0") {
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testthat::set_state_inspector(function() {
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list(

tests/testthat/test-functions.R

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[
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{"id":"echeverria-londono2021","abstract":"Abstract\n \n Background\n Deaths due to vaccine preventable diseases cause a notable proportion of mortality worldwide. To quantify the importance of vaccination, it is necessary to estimate the burden averted through vaccination. The Vaccine Impact Modelling Consortium (VIMC) was established to estimate the health impact of vaccination.\n \n \n Methods\n We describe the methods implemented by the VIMC to estimate impact by calendar year, birth year and year of vaccination (YoV). The calendar and birth year methods estimate impact in a particular year and over the lifetime of a particular birth cohort, respectively. The YoV method estimates the impact of a particular year’s vaccination activities through the use of impact ratios which have no stratification and stratification by activity type and/or birth cohort. Furthermore, we detail an impact extrapolation (IE) method for use between coverage scenarios. We compare the methods, focusing on YoV for hepatitis B, measles and yellow fever.\n \n \n Results\n We find that the YoV methods estimate similar impact with routine vaccinations but have greater yearly variation when campaigns occur with the birth cohort stratification. The IE performs well for the YoV methods, providing a time-efficient mechanism for updates to impact estimates.\n \n \n Conclusions\n These methods provide a robust set of approaches to quantify vaccination impact; however it is vital that the area of impact estimation continues to develop in order to capture the full effect of immunisation.","accessed":{"date-parts":[["2025",12,9]]},"author":[{"family":"Echeverria-Londono","given":"Susy"},{"family":"Li","given":"Xiang"},{"family":"Toor","given":"Jaspreet"},{"family":"De Villiers","given":"Margaret J."},{"family":"Nayagam","given":"Shevanthi"},{"family":"Hallett","given":"Timothy B."},{"family":"Abbas","given":"Kaja"},{"family":"Jit","given":"Mark"},{"family":"Klepac","given":"Petra"},{"family":"Jean","given":"Kévin"},{"family":"Garske","given":"Tini"},{"family":"Ferguson","given":"Neil M."},{"family":"Gaythorpe","given":"Katy A. M."}],"citation-key":"echeverria-londono2021","container-title":"BMC Public Health","container-title-short":"BMC Public Health","DOI":"10.1186/s12889-021-12040-9","ISSN":"1471-2458","issue":"1","issued":{"date-parts":[["2021",12]]},"language":"en","page":"2049","source":"DOI.org (Crossref)","title":"How can the public health impact of vaccination be estimated?","type":"article-journal","URL":"https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-12040-9","volume":"21"}
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]

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