Class "birdie" of BIRDiE ModelsSource:
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, ...)
- object, x
TRUE, return subgroup-level (rather than marginal) coefficient estimates as a 3D array.
Potentially further arguments passed from other methods
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
TRUE, plot estimated probabilities on a log scale.
A data frame to augment with
Pr(R | Y, X, S)probabilities
The internal structure of
birdie objects is not designed to be accessed
directly. The generics listed here should be used instead.
coef(birdie): Return estimated outcome-given-race distributions. When
subgroup=FALSEthis always returns a finite-population estimate of the outcome-given-race distribution for the observed sample.
fitted(birdie): Return an updated race probability table.
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.
methods(class="birdie") #>  augment coef family fitted formula glance nobs #>  plot predict print residuals simulate summary tidy #>  vcov #> see '?methods' for accessing help and source code