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