# boolprob: Calculate predicted probabilities In boolean3: Boolean Binary Response Models

## Description

This function calculates predicted probabilities for the selected covariate profiles.

## Usage

 ```1 2 3 4``` ```boolprob(obj, vars = NULL, newdata = NULL, k = 50, conf.int = FALSE, n = 100, as.table = TRUE, scales = list(x = list(relation = "free")), between = list(x = 1, y = 1), xlab = "x", ylab = "Predicted probability", ...) ```

## Arguments

 `obj` object of `boolean-class` containing a fit boolean model. `vars` vector selecting a set of covariates from the fitted model. This can be a character vector of covariate names (as output from `summary(obj)`), or a numeric vector indexing the desired covariates. `newdata` data.frame with the same structure as model.matrix(boolean). `k` integer indicating the number of points at which the predicted probability should be calculated. `conf.int` logical; should confidence intervals be simulated. `n` number of draws to take from the estimated parameter space. `as.table` logical (default `TRUE`), to be passed to `xyplot`. `scales` list of settings for the scales argument passed to `xyplot`. `between` numeric specifying the space between panels. `xlab` string, the `x`-axis label. `ylab` string, the `y`-axis label. `...` Additional arguments to pass to `xyplot`. See that documentation for details.

## Value

Returns an object of `boolprob-class`, the default action being to present the default plot.

## Author(s)

Jason W. Morgan (morgan.746@osu.edu)

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```## Not run: ## Note: This example assumes a boolean model has already been fit. ## Plot predicted probabilities for a fitted model. Either vars or ## newdata *must* be specified. boolprob(fit, vars = c("x1_a", "x4_b")) boolprob(fit, vars = c(2, 3, 4, 6)) ## Specifying conf.int = TRUE produces simulated confidence intervals. ## The number of samples to pull from the distribution of the estimated ## coefficients is controlled by n; n=100 is default. This can take a ## while. (prob <- boolprob(fit, vars = c(2, 3, 4, 6), n = 1000, conf.int = TRUE)) ## End(Not run) ```

boolean3 documentation built on May 30, 2017, 12:30 a.m.