Generates univariate synthetic data for binary or binomial response variable using logistic regression model.
syn.logreg(y, x, xp, denom = NULL, denomp = NULL, proper = FALSE, ...)
an original data vector of length n
.
a matrix (n
x p
) of original covariates.
a matrix (k
x p
) of synthesised covariates.
an original denominator vector of length n
for a binomial
regression model.
a synthesised denominator vector of length k
for
a binomial regression model.
a logical value specifying whether proper synthesis should be conducted. See details.
additional parameters.
A vector of length k
with synthetic values (0
or 1
)
of y
.
Synthesis for binary response variables by the non-Bayesian or approximate Bayesian logistic regression model. The non-Bayesian method consists of the following steps:
Calculate predicted inverse logits for synthesied covariates.
Compare the inverse logits to a random (0,1) deviate and get synthetic values.
The Bayesian version (for proper synthesis) includes additional step before computing inverse logits, namely drawing coefficients from normal distribution with mean and variance estimated in step 1.
The method relies on the standard glm.fit
function.
Warnings from glm.fit
are suppressed. Perfect prediction
is handled by the data augmentation method.