flexOR (version 1.0.0)

plot.OR: plot.OR: Plot Smooth Odds Ratios

Description

Plots smooth odds ratios along with confidence intervals for a specified predictor.

Usage

# S3 method for OR
plot(
  x,
  predictor,
  prob = NULL,
  ref.value = NULL,
  conf.level = 0.95,
  round.x = NULL,
  ref.label = NULL,
  col,
  col.area,
  main,
  xlab,
  ylab,
  lty,
  xlim,
  ylim,
  xx,
  ylog = TRUE,
  log = ifelse(ylog, "", "y"),
  ...
)

Value

This function doesn't return a value. It is used for generating a plot.

Arguments

x

An object of class "OR" generated by the flexOR function.

predictor

The name of the predictor variable for which to plot the smooth odds ratios.

prob

The probability level for the confidence interval. Default is NULL.

ref.value

The predicted value at which to calculate the smooth odds ratios. Default is NULL.

conf.level

The confidence level for the intervals. Default is 0.95.

round.x

The number of decimal places to round the predictor variable values. Default is NULL.

ref.label

The label for the reference value of the predictor variable. Default is NULL.

col

Vector of colors for plotting. Default is c("black", "black", "grey85").

col.area

Vector of colors for the confidence intervals.

main

The title of the plot. Default is generated based on the predictor variable.

xlab

Label for the x-axis. Default is the name of the predictor variable.

ylab

Label for the y-axis. Default is "Ln OR(Z,Zref)" if logarithmic scale is used, else "OR(Z,Zref)".

lty

Vector of line types for plotting. Default is c(1, 3).

xlim

Range of the x-axis. Default is NULL.

ylim

Range of the y-axis. Default is NULL.

xx

Values for tick marks on the x-axis. Default is NULL.

ylog

Logical. If TRUE, y-axis is on a logarithmic scale. Default is TRUE.

log

Use a logarithmic scale for the y-axis (alternative argument name).

...

Additional arguments passed to plotting functions.

Examples

library(gam);

# Load dataset
data(PimaIndiansDiabetes2, package="mlbench");

mod1 <- flexOR(
  data=PimaIndiansDiabetes2,
  response="diabetes",
  formula=~s(age, 3.3) + s(mass, 4.1) + pedigree
);