LC1980_bbt {basicspace}  R Documentation 
BlackboxTranspose estimates from LiberalConservative 7point scales from the 1980 National Election Study. Estimates in 3 dimensions.
data(LC1980_bbt)
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:

individuals 
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). Individuals that are discarded from analysis due to the minscale constraint are NA'd out. Each row contains data on a separate stimulus, and each data frame includes the following variables:

fits 
A data frame of fit results, with elements listed as follows: 
SSE
Sum of squared errors.
SSE.explained
Explained sum of squared error.
percent
Percentage of total variance explained.
SE
Standard error of the estimate, with formula provided in the article cited below.
singular
Singluar value for the dimension.
Nrow 
Number of rows/stimuli. 
Ncol 
Number of columns used in estimation. This may differ from the data set due to columns discarded due to the minscale constraint. 
Ndata 
Total number of data entries. 
Nmiss 
Number of missing entries. 
SS_mean 
Sum of squares grand mean. 
dims 
Number of dimensions estimated. 
Keith Poole ktpoole@uga.edu
Howard Rosenthal hr31@nyu.edu
Jeffrey Lewis jblewis@ucla.edu
James Lo lojames@usc.edu
Royce Carroll rcarroll@rice.edu
American national Election Study. http://www.electionstudies.org/
'plotcdf.blackbt', 'LC1980', 'plot.blackbt', 'summary.blackbt', 'blackbox_transpose'.
### Loads and scales the LiberalConservative scales from the 1980 NES.
data(LC1980)
LCdat=LC1980[,1] #Dump the column of selfplacements
### 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)