boot.blackbox_transpose: Bootstrapping Blackbox_transpose Scaling Model

In davidaarmstrong/asmcjr: Analyzing Spatial Models of Choice and Judgment with R

Bootstrapping Blackbox_transpose Scaling Model

Description

A function that applies bootstrap resampling to the Blackbox_transpose Scaling model.

Usage

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

Arguments

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.

Value

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

See Also

blackbox_transpose

davidaarmstrong/asmcjr documentation built on June 29, 2024, 12:07 p.m.