Nothing
process_rq <- function(rq_obj, se.type = "boot",
conf.int = FALSE,
conf.level = 0.95) {
nn <- c("estimate", "std.error", "statistic", "p.value")
co <- as.data.frame(rq_obj[["coefficients"]])
if (se.type == "rank") {
# if only a single predictor is included, confidence interval not calculated
# set to NA to preserve dimensions of object
if (1 == ncol(co)) {
co <- cbind(co, NA, NA)
}
co <- setNames(co, c("estimate", "conf.low", "conf.high"))
conf.int <- FALSE
} else {
co <- setNames(co, nn)
}
if (conf.int) {
a <- (1 - conf.level) / 2
cv <- qt(c(a, 1 - a), df = rq_obj[["rdf"]])
co[["conf.low"]] <- co[["estimate"]] + (cv[1] * co[["std.error"]])
co[["conf.high"]] <- co[["estimate"]] + (cv[2] * co[["std.error"]])
}
co[["tau"]] <- rq_obj[["tau"]]
as.data.frame(co)
}
get_qemm = function(quan_mod,
df,
agree.l,
agree.u,
conf.level){
ref_med = ref_grid(quan_mod, se = "boot",
tau = .5,
at = list(mean = seq(min(df$mean, na.rm =TRUE),
max(df$mean, na.rm= TRUE),
length.out=100)))
quan_emm_med = as.data.frame(confint(emmeans(ref_med,
~ mean), level = conf.level))
df_coef_med = data.frame(at = quan_emm_med$mean,
estimate = quan_emm_med$emmean,
lower.ci = quan_emm_med$lower.CL,
upper.ci = quan_emm_med$upper.CL,
text = "Bias")
ref_lloa = ref_grid(quan_mod, se = "boot",
tau = agree.u,
at = list(mean = seq(min(df$mean, na.rm =TRUE),
max(df$mean, na.rm= TRUE),
length.out=100)))
quan_emm_lloa = as.data.frame(confint(emmeans(ref_lloa,
~ mean), level = conf.level))
df_coef_lloa = data.frame(at = quan_emm_lloa$mean,
estimate = quan_emm_lloa$emmean,
lower.ci = quan_emm_lloa$lower.CL,
upper.ci = quan_emm_lloa$upper.CL,
text = "Lower LoA")
ref_uloa = ref_grid(quan_mod, se = "boot",
tau = agree.l,
at = list(mean = seq(min(df$mean, na.rm =TRUE),
max(df$mean, na.rm= TRUE),
length.out=100)))
quan_emm_uloa = as.data.frame(confint(emmeans(ref_uloa,
~ mean), level = conf.level))
df_coef_uloa = data.frame(at = quan_emm_uloa$mean,
estimate = quan_emm_uloa$emmean,
lower.ci = quan_emm_uloa$lower.CL,
upper.ci = quan_emm_uloa$upper.CL,
text = "Upper LoA")
df_emm = rbind(df_coef_uloa,
df_coef_med,
df_coef_lloa)
df_emm$text = factor(df_emm$text,
levels = c("Upper LoA", "Bias", "Lower LoA"))
return(df_emm)
}
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