boot.blackbox: Bootstrapping Blackbox Scaling Model
In davidaarmstrong/asmcjr: Analyzing Spatial Models of Choice and Judgment with R

boot.blackbox

R Documentation

Bootstrapping Blackbox Scaling Model

A wrapper to boot that applies bootstrap resampling to the Blackbox Scaling model.

boot.blackbox(data, missing, dims=1, minscale, verbose=FALSE,
  posStimulus = 1, R=100)

`data`	A data frame or matrix containing the data to be used in the Aldrich-McKelvey scaling.
`missing`	A vector of values that will be recoded to missing before the anaylsis.
`dims`	Number of dimensions to estimate in the scaling algorithm.
`minscale`	Minimum number of valid values for an observation to be included in the scaling.
`verbose`	Logical indicating whether or not output from the fitting procedure should be presented.
`posStimulus`	An observation number for a stimulus known to have positive values on the resulting scale. The first dimension will be multiplied by -1 if that observation has a negative scale value.
`R`	Number of bootstrap samples to retain.

A three-dimensional array (respondents x dimensions x bootstrap samples) of scaled scores.