In fk506cni/uncoR:

knitr::opts_chunk$set(echo = TRUE, cache = TRUE,cache.lazy = FALSE, echo=TRUE)
set.seed("114514")

require(devtools)
install_github("fk506cni/uncoR")
require("uncoR")

model setup

if your model is like bellow,

$$ Var_{sum} = \beta_{1}Var_{1} + \beta_{2}Var_{2} \ Var_{sum} \ is \ ALPlat_index \ Var_{1} \ is \ Platet(10^9/L) \ Var_{2} \ is \ Alubmin(g/dL) \ \beta_1 = 1\ \beta_2 =85\ 100 \leq Var_1 \leq 300 \ 2 \leq Var_2 \leq 4 \

\ \ cutoff \ values\ in\ 415,\ 455,\ 512 $$

model_info <- list()
model_info$model_type <- "sum"
model_info$var_name <- c("'Plt '(10^9/L)","'Alb '(g/dL)")
model_info$outoput_name <- "'ALPlat index'"
model_info$betas <- c(1, 85)
model_info$constant <- 0
model_info$var_range <- list(Var1=c(100, 300), Var2=c(2, 4))
model_info$cutoff_val <- c(415, 455, 512)
model_info$formula <- "'ALPlat index '==' Plt'(10^9/L) + 85%*%'Alb'(g/dL)"

nomoV3 <- ggnomogramV3(model_info = model_info,main = "")
ggsave2(nomoV3,wid =18, hei=18, device = "png")

fk506cni/uncoR documentation built on May 17, 2019, 7:05 p.m.