# plot.RRlog: Plot Logistic RR Regression In danheck/RRreg: Correlation and Regression Analyses for Randomized Response Data

 plot.RRlog R Documentation

## 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,
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)`).

`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.