library(DynNom) #加载包；
library(survival) #加载包
data(lung) #加载R内置数据集lung
str(lung)#显示lung数据集结构
newdata<-na.omit(lung)#删除缺失值
str(newdata)#显示新数据集
attach(newdata)
newdata$sex<-factor(newdata$sex,labels=c("male","female"))#因子化并设定标题
mod <-coxph(Surv(time, status) ~age +meal.cal+sex + wt.loss, data = newdata)
summary(mod)
DynNom(mod) #生成动态列线图（Dynamic Nomogram）
最终结果图示
以下为该包的帮助文件内容
Dynamic nomogram to visualise statistical models
Description
DynNom is a generic function to display the results of statistical model objects as a dynamic nomogram in an 'RStudio' panel or web browser. DynNom supports a large number of model objects from a variety of packages.
Usage
DynNom(model, data = NULL, clevel = 0.95, m.summary = c("raw", "formatted"),
covariate = c("slider", "numeric"), ptype = c("st", "1-st"),
DNtitle = NULL, DNxlab = NULL, DNylab = NULL, DNlimits = NULL,
KMtitle = NULL, KMxlab = NULL, KMylab = NULL)
DynNom.core(model, data, clevel, m.summary, covariate, DNtitle, DNxlab, DNylab, DNlimits)
DynNom.surv(model, data, clevel, m.summary, covariate,
ptype, DNtitle, DNxlab, DNylab, KMtitle, KMxlab, KMylab)
Arguments
model
an lm, glm, coxph, ols, Glm, lrm, cph, mgcv::gam or gam::gam model objects.
data
a dataframe of the accompanying dataset for the model (if required).
clevel
a confidence level for constructing the confidence interval. If not specified, a 95% level will be used.
m.summary
an option to choose the type of the model output represented in the 'Summary Model' tab. "raw" (the default) returns an unformatted summary of the model; "formatted" returns a formatted table of the model summary using stargazer package.
covariate
an option to choose the type of input control widgets used for numeric values. "slider" (the default) picks out sliderInput; "numeric" picks out numericInput.
ptype
an option for coxph or cph model objects to choose the type of plot which displays in "Survival plot" tab. "st" (the default) returns plot of estimated survivor probability (S(t)). "1-st" returns plot of estimated failure probability (1-S(t)).
DNtitle
a character vector used as the app's title. If not specified, "Dynamic Nomogram" will be used.
DNxlab
a character vector used as the title for the x-axis in "Graphical Summary" tab. If not specified, "Probability" will be used for logistic model and Cox proportional model objects; or "Response variable" for other model objects.
DNylab
a character vector used as the title for the y-axis in "Graphical Summary" tab (default is NULL).
DNlimits
a vector of 2 numeric values used to set x-axis limits in "Graphical Summary" tab. Note: This also removes the 'Set x-axis ranges' widget in the sidebar panel.
KMtitle
a character vector used as KM plot's title in "Survival plot" tab. If not specified, "Estimated Survival Probability" for ptype = "st" and "Estimated Probability" for ptype = "1-st" will be used.
KMxlab
a character vector used as the title for the x-axis in "Survival plot" tab. If not specified, "Follow Up Time" will be used.
KMylab
a character vector used as the title for the y-axis in "Survival plot" tab. If not specified, "S(t)" for ptype = "st" and "F(t)" for ptype = "1-st" will be used.
Value
A dynamic nomogram in a shiny application providing individual predictions which can be used as a model visualisation or decision-making tools.
The individual predictions with a relative confidence interval are calculated using the predict function, displaying either graphically as an interactive plot in the Graphical Summary tab or a table in the Numerical Summary tab. A table of model output is also available in the Model Summary tab. In the case of the Cox proportional hazards model, an estimated survivor/failure function will be additionally displayed in a new tab.
Please cite as:
Jalali, A., Roshan, D., Alvarez-Iglesias, A., Newell, J. (2019). Visualising statistical models using dynamic nomograms. R package version 5.0.
Author(s)
Amirhossein Jalali, Davood Roshan, Alberto Alvarez-Iglesias, John Newell
Maintainer: Amirhossein Jalali a.jalali2@nuigalway.ie
References
Banks, J. 2006. Nomograms. Encyclopedia of Statistical Sciences. 8.
Easy web applications in R. http://shiny.rstudio.com
Frank E Harrell Jr (2017). rms: Regression Modeling Strategies. R package version 4.5-0. https://CRAN.R-project.org/package=rms
See Also
DNbuilder, getpred.DN
Examples
## Not run:
# Simple linear regression models
fit1 <- lm(uptake ~ Plant + conc + Plant * conc, data = CO2)
DynNom(fit1)
t.data <- datadist(swiss)
options(datadist = 't.data')
ols(Fertility ~ Agriculture + Education + rcs(Catholic, 4), data = swiss) %>%
DynNom(clevel = 0.9, m.summary="formatted")
# Generalized regression models
fit2 <- glm(Survived ~ Age + Class + Sex,
data = as.data.frame(Titanic), weights = Freq, family = binomial("probit"))
DynNom(fit2, DNtitle="Titanic", DNxlab = "Probability of survival")
counts <- c(18, 17, 15, 20, 10, 20, 25, 13, 12)
outcome <- gl(3, 1, 9)
treatment <- gl(3, 3)
d <- datadist(treatment, outcome)
options(datadist = "d")
Glm((2 * counts) ~ outcome + treatment, family = poisson(),
data = data.frame(counts, outcome, treatment)) %>%
DynNom()
# Proportional hazard models
coxph(Surv(time, status) ~ age + strata(sex) + ph.ecog, data = lung) %>%
DynNom()
data.kidney <- kidney
data.kidney$sex <- as.factor(data.kidney$sex)
levels(data.kidney$sex) <- c("male", "female")
coxph(Surv(time, status) ~ age + strata(sex) + disease, data.kidney) %>%
DynNom(ptype = "1-st")
d <- datadist(veteran)
options(datadist = "d")
fit3 <- cph((Surv(time/30, status)) ~ rcs(age, 4) * strat(trt) + diagtime +
strat(prior) + lsp(karno, 60), veteran)
DynNom(fit3, DNxlab = "Survival probability",
KMtitle="Kaplan-Meier plot", KMxlab = "Time (Days)", KMylab = "Survival probability")
# Generalized additive models
mgcv::gam(Fertility ~ s(Agriculture) + Education + s(Catholic), data=swiss) %>%
DynNom(DNlimits = c(0, 110), m.summary="formatted")
fit4 <- gam::gam(Fertility ~ Education + Catholic + s(Agriculture), fit=FALSE, data=swiss)
DynNom(fit4)
## End(Not run)
if (interactive()) {
data(rock)
lm(area~I(log(peri)), data = rock) %>%
DynNom()
}
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