plot.RRlog: Plot Logistic RR Regression

In danheck/RRreg: Correlation and Regression Analyses for Randomized Response Data

Plot Logistic RR Regression

Description

Plot predicted logit values/probabilities of a randomized response logistic regression model.

Usage

## S3 method for class 'RRlog'
plot(
  x,
  predictor = NULL,
  type = c("link", "response", "attribute"),
  center.preds = TRUE,
  plot.mean = TRUE,
  ci = 0.95,
  xlim = NULL,
  steps = 50,
  ...
)

Arguments

x	a fitted RRlog object
predictor	character name of a predictor of the model to be fitted
type	"response" returns predicted probabilities for the (observable) RR responses, "link" returns predicted logit-values for the (latent) sensitive attribute, and "attribute" returns predicted probabilities of having the (latent) sensitive attribute.
center.preds	whether to compute predictions by assuming that all other predictors are at their respective mean values (if FALSE: all other predictors are set to zero)
plot.mean	whether to plot the mean of the predictor as a vertical line
ci	level for confidence intervals. Use ci=0 to omit.
xlim	if provided, these boundaries are used for the predictor on the x-axis
steps	number of steps for plotting
...	other arguments passed to the function plot (e.g., ylim=c(0,1)).

See Also

predict.RRlog

Examples

# generate data
n <- 500
x <- data.frame(x1 = rnorm(n))
pi.true <- 1 / (1 + exp(.3 + 1.5 * x$x1))
true <- rbinom(n, 1, plogis(pi.true))
dat <- RRgen(n, trueState = true, model = "Warner", p = .1)
x$response <- dat$response

# fit and plot RR logistic regression
mod <- RRlog(response ~ x1, data = x, model = "Warner", p = .1)
plot(mod, "x1", ci = .95, type = "attribute", ylim = 0:1)

danheck/RRreg documentation built on Dec. 3, 2022, 7:50 p.m.