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Type 'q()' to quit R. > # test that the p_bp and q_bp functions return as expected for all the different > # source options > library(pedbp) > > # first, verify that the source input options are as expected > x <- tryCatch(q_bp(p_sbp = 1, p_dbp = 1, male = 1, age = numeric(1), source = "Not a real source"), error = function(e) e) > stopifnot(inherits(x, "error")) > > # the message appears to print in one of two ways, using the unicode \u8220 and > # \u8221 for the double quotes when in an interactive session, and \u22 when not > # interactive > stopifnot( + identical(x$message, "'arg' should be one of “martin2022”, “gemelli1990”, “nhlbi”, “lo2013”, “flynn2017”") | + identical(x$message, "'arg' should be one of \"martin2022\", \"gemelli1990\", \"nhlbi\", \"lo2013\", \"flynn2017\"") + ) > > ################################################################################ > qbp_expected <- list(sbp = rep(NA_real_, 9), dbp = rep(NA_real_, 9)) > > # return NA for age out of bounds > # too young > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 0.9) + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 0.9, source = "martin2022") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 0.9, source = "gemelli1990") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 35.9, source = "lo2013") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 11.9, source = "nhlbi") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 11.9, source = "flynn2017") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > > # too old > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 19*12, source = "flynn2017") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 19*12, source = "nhlbi") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 19*12, source = "martin2022") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 19*12) + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 19*12, source = "lo2013") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + q_bp(p_sbp = 1:9/10, p_dbp = 1:9/10, male = 0, age = 13, source = "gemelli1990") + , + qbp_expected + , + check.attributes = FALSE + ) + ) + ) > > ################################################################################ > # nhlbi and flynn2017 values will be different from the publications. > # The difference is due to having a Gaussian mean and variance estimated by the > # three or four percentiles published. The tests here are to verify that the > # estimates are not too different. > > # NOTE: IF THIS FAILS UPDATE THE VIGNETTE > fq <- + q_bp( + p_sbp = flynn2017$bp_percentile/100, + p_dbp = flynn2017$bp_percentile/100, + male = flynn2017$male, + age = flynn2017$age, + height_percentile = flynn2017$height_percentile, + source = "flynn2017") > > fp <- + p_bp( + q_sbp = flynn2017$sbp, + q_dbp = flynn2017$dbp, + male = flynn2017$male, + age = flynn2017$age, + height_percentile = flynn2017$height_percentile, + source = "flynn2017") > > nq <- + q_bp( + p_sbp = nhlbi_bp_norms$bp_percentile/100, + p_dbp = nhlbi_bp_norms$bp_percentile/100, + male = nhlbi_bp_norms$male, + age = nhlbi_bp_norms$age, + height_percentile = nhlbi_bp_norms$height_percentile, + source = "nhlbi") > > np <- + p_bp( + q_sbp = nhlbi_bp_norms$sbp, + q_dbp = nhlbi_bp_norms$dbp, + male = nhlbi_bp_norms$male, + age = nhlbi_bp_norms$age, + height_percentile = nhlbi_bp_norms$height_percentile, + source = "nhlbi") > > flynn2017 <- + cbind(flynn2017, + pedbp_sbp = fq$sbp, + pedbp_dbp = fq$dbp, + pedbp_sbp_p = fp$sbp_p * 100, + pedbp_dbp_p = fp$dbp_p * 100 + ) > > nhlbi_bp_norms <- + cbind(nhlbi_bp_norms, + pedbp_sbp = nq$sbp, + pedbp_dbp = nq$dbp, + pedbp_sbp_p = np$sbp_p * 100, + pedbp_dbp_p = np$dbp_p * 100 + ) > > # all estimates within 2 mmHg or 2 percentage points > stopifnot(max(abs(flynn2017$pedbp_sbp - flynn2017$sbp)) < 2) > stopifnot(max(abs(flynn2017$pedbp_dbp - flynn2017$dbp)) < 2) > stopifnot(max(abs(flynn2017$pedbp_sbp_p - flynn2017$bp_percentile)) < 2) > stopifnot(max(abs(flynn2017$pedbp_dbp_p - flynn2017$bp_percentile)) < 2) > stopifnot(max(abs(nhlbi_bp_norms$pedbp_sbp - nhlbi_bp_norms$sbp)) < 2) > stopifnot(max(abs(nhlbi_bp_norms$pedbp_dbp - nhlbi_bp_norms$dbp)) < 2) > > stopifnot(max(abs(nhlbi_bp_norms$pedbp_sbp_p - nhlbi_bp_norms$bp_percentile)) < 2) > stopifnot(max(abs(nhlbi_bp_norms$pedbp_dbp_p - nhlbi_bp_norms$bp_percentile)) < 2) > > if (interactive()) { + par(mfrow = c(1, 2)) + plot(flynn2017$sbp, flynn2017$pedbp_sbp); abline(0, 1) + plot(flynn2017$dbp, flynn2017$pedbp_dbp); abline(0, 1) + summary(flynn2017$pedbp_sbp - flynn2017$sbp) + summary(flynn2017$pedbp_dbp - flynn2017$dbp) + summary(flynn2017$pedbp_sbp_p*100 - flynn2017$bp_percentile) + summary(flynn2017$pedbp_dbp_p*100 - flynn2017$bp_percentile) + + qwraps2::qblandaltman(flynn2017[, c("sbp", "pedbp_sbp")]) + qwraps2::qblandaltman(flynn2017[, c("dbp", "pedbp_dbp")]) + qwraps2::qblandaltman(flynn2017[, c("bp_percentile", "pedbp_sbp_p")]) + qwraps2::qblandaltman(flynn2017[, c("bp_percentile", "pedbp_dbp_p")]) + + par(mfrow = c(1, 2)) + plot(nhlbi_bp_norms$sbp, nhlbi_bp_norms$pedbp_sbp); abline(0, 1) + plot(nhlbi_bp_norms$dbp, nhlbi_bp_norms$pedbp_dbp); abline(0, 1) + summary(nhlbi_bp_norms$pedbp_sbp - nhlbi_bp_norms$sbp) + summary(nhlbi_bp_norms$pedbp_dbp - nhlbi_bp_norms$dbp) + summary(nhlbi_bp_norms$pedbp_sbp_p*100 - nhlbi_bp_norms$bp_percentile) + summary(nhlbi_bp_norms$pedbp_dbp_p*100 - nhlbi_bp_norms$bp_percentile) + + qwraps2::qblandaltman(nhlbi_bp_norms[, c("sbp", "pedbp_sbp")]) + qwraps2::qblandaltman(nhlbi_bp_norms[, c("dbp", "pedbp_dbp")]) + qwraps2::qblandaltman(nhlbi_bp_norms[, c("bp_percentile", "pedbp_sbp_p")]) + qwraps2::qblandaltman(nhlbi_bp_norms[, c("bp_percentile", "pedbp_dbp_p")]) + } > > ################################################################################ > # Verify that the expected median is returned from q_bp calls for gemelli1990 > # and lo2013 > stopifnot( + isTRUE( + all.equal( + unname(q_bp(p_sbp = 0.5, p_dbp = 0.5, male = gemelli1990$male, age = gemelli1990$age, source = "gemelli1990")) + , + unname(as.list(gemelli1990[c("sbp_mean", "dbp_mean")])) + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + unname(q_bp(p_sbp = 0.5, p_dbp = 0.5, male = lo2013$male, age = lo2013$age, source = "lo2013")) + , + unname(as.list(lo2013[c("sbp_mean", "dbp_mean")])) + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + unname(p_bp(q_sbp = gemelli1990$sbp_mean, q_dbp = gemelli1990$dbp_mean, male = gemelli1990$male, age = gemelli1990$age, source = "gemelli1990")) + , + list(rep(0.5, nrow(gemelli1990)), rep(0.5, nrow(gemelli1990))) + , + check.attributes = FALSE + ) + ) + ) > > stopifnot( + isTRUE( + all.equal( + unname(p_bp(q_sbp = lo2013$sbp_mean, q_dbp = lo2013$dbp_mean, male = lo2013$male, age = lo2013$age, source = "lo2013")) + , + list(rep(0.5, nrow(lo2013)), rep(0.5, nrow(lo2013))) + , + check.attributes = FALSE + ) + ) + ) > > ################################################################################ > # End of file # > ################################################################################ > > proc.time() user system elapsed 0.20 0.06 0.26