basicspace (version 0.13)

blackbox_transpose: Blackbox transpose Scaling

Description

blackbox_transpose is a function that takes a matrix of perceptual data, such as liberal-conservative rankings of various stimuli, and recovers the true location of those stimuli in a spatial model. It differs from procedures such as wnominate, which instead use preference data to estimate candidate and citizen positions. The procedure here generalizes the technique developed by John Aldrich and Richard McKelvey in 1977, which is also included in this package as the aldmck function.

Usage

blackbox_transpose(data,missing=NULL,verbose=FALSE,dims=1,minscale)

Arguments

data

matrix of numeric values, containing the perceptual data. Respondents should be organized on rows, and stimuli on columns. It is helpful, though not necessary, to include row names and column names.

missing

vector or matrix of numeric values, sets the missing values for the data. NA values are always treated as missing regardless of what is set here. Observations with missing data are discarded before analysis. If input is a vector, then the ve

verbose

logical, indicates whether aldmck should print out detailed output when scaling the data.

dims

integer, specifies the number of dimensions to be estimated.

minscale

integer, specifies the minimum number of responses a respondent needs needs to provide to be used in the scaling.

Value

• An object of class blackbt.
• stimuli
  vector of data frames of length dims. Each data frame presents results for estimates from that dimension (i.e. x$stimuli[[2]] presents results for dimension 2). Each row contains data on a separate stimulus, and each data frame includes the following variables:

  • N

  {Number of respondents who ranked this stimulus.} coord1D{Location of the stimulus in the first dimension. If viewing the results for a higher dimension, higher dimension results will appear as coord2D, coord3D, etc.} R2{The percent variance explained for the stimulus. This increases as more dimensions are estimated.}

item

• individuals
• w1
• R2
• fits
• SSE.explained
• percent
• SE
• singular
• Nrow
• Ncol
• Ndata
• Nmiss
• SS_mean
• dims

itemize

• SSE

References

Keith T. Poole (1998) ``Recovering a Basic Space From a Set of Issue Scales.'' American Journal of Political Science. 42(3), 954-993.

See Also

'plotcdf.blackbt', 'LC1980', 'plot.blackbt', 'summary.blackbt', 'LC1980_bbt'.

Examples

### Loads and scales the Liberal-Conservative scales from the 1980 NES.
data(LC1980)
LCdat=LC1980[,-1]	#Dump the column of self-placements

### This command conducts estimates, which we instead load using data()
#LC1980_bbt <- blackbox_transpose(LCdat,missing=c(0,8,9),dims=3,minscale=5,verbose=TRUE)
data(LC1980_bbt)

plot(LC1980_bbt)
par(ask=TRUE)
plotcdf.blackbt(LC1980_bbt)
summary(LC1980_bbt)