The output of birdie() is an object of class birdie, which supports
many generic functions. Notably coef.birdie() returns the main model
estimates of outcome given race, and fitted.birdie() returns a table
analogous to the output of bisg() with updated race probabilities.
# S3 method for birdie
coef(object, subgroup = FALSE, ...)# S3 method for birdie
fitted(object, ...)
# S3 method for birdie
residuals(object, x_only = FALSE, ...)
# S3 method for birdie
predict(object, adj = NULL, ...)
# S3 method for birdie
simulate(object, nsim = 1, seed = NULL, ...)
# S3 method for birdie
plot(x, log = FALSE, ...)
# S3 method for birdie
tidy(x, subgroup = FALSE, ...)
# S3 method for birdie
glance(x, ...)
# S3 method for birdie
augment(x, data, ...)
# S3 method for birdie
formula(x, ...)
# S3 method for birdie
family(object, ...)
# S3 method for birdie
nobs(object, ...)
# S3 method for birdie
vcov(object, ...)
# S3 method for birdie
print(x, ...)
# S3 method for birdie
summary(object, ...)
Varies, depending on the method. See generic functions' documentation for details.
A birdie model object
If TRUE, return subgroup-level (rather than marginal)
coefficient estimates as a 3D array.
Potentially further arguments passed from other methods
if TRUE, calculate fitted values using covariates only (i.e.,
without using surnames).
A point in the simplex that describes how BISG probabilities
will be thresholded to produce point predictions. The probabilities are
divided by adj, then the racial category with the highest probability is
predicted. Can be used to trade off types of prediction error. Must be
nonnegative but will be normalized to sum to 1. The default is to make no
adjustment.
The number of vectors to simulate. Defaults to 1.
Used to seed the random number generator. See stats::simulate().
If TRUE, plot estimated probabilities on a log scale.
A data frame to augment with Pr(R | Y, X, S) probabilities
coef(birdie): Return estimated outcome-given-race distributions.
When subgroup=FALSE this always returns a finite-population estimate of
the outcome-given-race distribution for the observed sample.
fitted(birdie): Return an updated race probability table. bisg()
estimates Pr(R | G, X, S); this table is Pr(R | Y, G, X, S, Theta-hat).
residuals(birdie): Return the residuals for the outcome variable as a
matrix. Useful in sensitivity analyses and to get an idea of how well race,
location, names, etc. predict the outcome.
predict(birdie): Create point predictions of individual race. Returns
factor vector of individual race labels. Strongly not recommended for any
kind of inferential purpose, as biases may be extreme and in unpredictable
directions.
simulate(birdie): Simulate race from the posterior distribution
Pr(R | Y, G, X, S, Theta-hat). Does not account for uncertainty in model
parameters.
plot(birdie): Visualize the estimated conditional distributions
for a BIRDiE model. If available, marginal standard error estimates ($se)
will be visualized with 95% confidence-level error bars.
tidy(birdie): Put BIRDiE model coefficients in a tidy format.
glance(birdie): Glance at a BIRDiE model.
augment(birdie): Augment data with individual race predictions from a BIRDiE model.
formula(birdie): Extract the formula used to specify a BIRDiE model.
family(birdie): Return the BIRDiE complete-data model family.
nobs(birdie): Return the number of observations used to fit a BIRDiE model.
vcov(birdie): Return the estimated variance-covariance matrix for
the BIRDiE model estimates, if available.
print(birdie): Print a summary of the model fit.
summary(birdie): Print a more detailed summary of the model fit.
The internal structure of birdie objects is not designed to be accessed
directly. The generics listed here should be used instead.