Function to calculate predictions from a measurement model fitted to an endorsement experiment data.
# S3 method for endorse predict(object, newdata, type = c("prob.support", "linear.s"), standardize = TRUE, ...)
| object | a fitted object of class inheriting from |
|---|---|
| newdata | an optional data frame containing data that will be used to make predictions from. If omitted, the data used to fit the regression are used. |
| type | the type of prediction required. The default is on the
scale of the predicted probability of positive support; the
alternative |
| standardize | logical switch indicating if the predicted values on the scale of \(s_{ijk}\) are standardized so that its variance is one. |
| ... | further arguments to be passed to or from other methods. |
predict.endorse produces predicted support for political actors
from a fitted "endorse" object. If newdata is omitted
the predictions are based on the date used for the fit. Setting
type specifies the type of predictions. The default is
"prob.support", in which case the function computes the average
predicted probability of positive support:
$$
P(s_{ijk} > 0 \mid Z_i, \; \lambda_{j}, \; \omega_{j}) =
\Phi \left( \frac{ Z_i^{T} \lambda_{j} }{ \omega_{j} } \right)
$$
for each political group \(k\). If type is set to be
"linear.s", the output is the predicted mean of support
parameters:
$$
E(s_{ijk} \mid Z_i, \; \lambda_{j}) = Z_i^{T} \lambda_{j}.
$$
If the logical standardize is TRUE, the predicted mean
of support is standardized by dividing by \(\omega_j\).
A "mcmc" object for predicted values.
endorse for model fitting