Extract the posterior draws of the linear predictor, possibly transformed by
the inverse-link function. This function is occasionally useful, but it
should be used sparingly. Inference and model checking should generally be
carried out using the posterior predictive distribution (i.e., using
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A fitted model object returned by one of the
rstanarm modeling functions. See
Should the linear predictor be transformed using the
inverse-link function? The default is
Same as for
The default is to return a
matrix of simulations from the posterior distribution of the (possibly
transformed) linear predictor. The exception is if the argument
is set to
TRUE (see the
XZ argument description above).
For models estimated with
stan_clogit, the number of
successes per stratum is ostensibly fixed by the research design. Thus,
posterior_linpred with new data and
data.frame passed to the
newdata argument must
contain an outcome variable and a stratifying factor, both with the same
name as in the original
data.frame. Then, the probabilities will
condition on this outcome in the new data.
posterior_predict to draw from the posterior
predictive distribution of the outcome, which is typically preferable.
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if (!exists("example_model")) example(example_model) print(family(example_model)) # linear predictor on log-odds scale linpred <- posterior_linpred(example_model) colMeans(linpred) # probabilities probs <- posterior_linpred(example_model, transform = TRUE) colMeans(probs) # not conditioning on any group-level parameters probs2 <- posterior_linpred(example_model, transform = TRUE, re.form = NA) apply(probs2, 2, median)
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