| fitted.anchors.cpolr {anchors} | R Documentation |
Conditional and unconditional prediction for censored ordered
probit. Unconditional prediction returns the fitted values (predicted
probabilities) from the cpolr object. Conditional prediction
takes the observed range of the diff-corrected self-response output from
anchors and renormalizes the predicted
probabilities for each observation.
## S3 method for class 'anchors.cpolr' fitted(object, average = FALSE, unconditional = FALSE, ...)
object |
anchors.cpolr object |
average |
a logical value. See |
unconditional |
Set to TRUE if you submit an anchors.object AND want the unconditional probabilities returned. One case that you would submit a anchors.rank object is if you did subsetting for the anchors object but not for the cpolr object, and want the intersection of the two objects used for the unconditional probabilities. |
... |
required for S3, but any other options will be ignored. |
If average = FALSE, a matrix of predicted probabilities
with rows corresponding to observations, and columns corresponding to
categories.
If average = TRUE, the matrix of predicted probabilities
(conditional or unconditional) is summarized to a vector (summed by categories,
then renormalized to sum to 1).
If anchors object has been specified, then each observation is
renormalized to fall into the range of the diff-corrected
self-response for that observation. If there are no ties for a given
observation, then that observation is a
vector consisting of (k-1) zeros and 1 one. If there are ties, then
the predicted probabilities for that observation are renormalized to
fall within the diff-corrected range.
If anchors object is omitted, identical to the matrix of predicted
probabilities from the cpolr output.
Related materials and worked examples are available at http://wand.stanford.edu/anchors/
Jonathan Wand http://wand.stanford.edu
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. 4th edition. Springer.
Wand, Jonathan; Gary King; and Olivia Lau. (2007) “Anchors: Software for Anchoring Vignettes”. Journal of Statistical Software. Forthcoming. copy at http://wand.stanford.edu/research/anchors-jss.pdf
Wand, Jonathan and Gary King. (2007) Anchoring Vignetttes in R: A (different kind of) Vignette copy at http://wand.stanford.edu/anchors/doc/anchors.pdf
Gary King and Jonathan Wand. "Comparing Incomparable Survey Responses: New Tools for Anchoring Vignettes," Political Analysis, 15, 1 (Winter, 2007): Pp. 46-66, copy at http://gking.harvard.edu/files/abs/c-abs.shtml.
## see examples in anchors