DynNom.glm: Dynamic Nomograms for Generalized Linear Models

In amirjll/DynNom-V3.1: Dynamic Nomograms for Linear, Generalized Linear and Proportional Hazard Models

Description

DynNom.glm displays the results of a glm model object as a dynamic nomogram in an 'RStudio' panel or web browser.

Usage

DynNom.glm(model, data,
           clevel = 0.95, covariate = c("slider", "numeric"))

Arguments

model	a glm model object
data	dataframe containing the accompanying data
clevel	confidence level required
covariate	The option to choose the type of covariate(s) input control widget for numeric values. If "slider" (the default) is chosen a shiny application with slider control widgets are used while if "numeric" is chosen numeric values input controls will be displayed.

Value

A dynamic nomogram in a shiny application which recognises all the predictors in the model and uses them to build a sidebar panel. It sets up drop down menus for factors and sliders set at the mean and bounded by the range for covariates.

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.

Author(s)

Amirhossein Jalali, Alberto Alvarez-Iglesias, John Newell

See Also

glm, predict.glm

Examples

## Not run: 
# a generilized linear model
model1 <- glm(Fertility ~ Agriculture + Education + Catholic, data = swiss)
DynNom(model1, swiss, clevel = 0.9)

# a logistic regression model
data1 =as.data.frame(Titanic)
model2 <- glm(Survived ~ Age + Class + Sex, data = data1, weights = Freq,
              family = binomial("probit"))
DynNom(model2, as.data.frame(Titanic), clevel = 0.9)

## End(Not run)

if (interactive()) {
# a poisson regression model
model3 <- glm(event ~ mag + dist + accel, data = attenu, family = poisson)
DynNom(model3, attenu, covariate = "numeric")
}

amirjll/DynNom-V3.1 documentation built on May 10, 2019, 1:17 a.m.