basicspace (version 0.24)

Issues1980_bb: Blackbox Estimate, 1980 NES Issue Scales.

Description

Blackbox estimates from issues scales from the 1980 National Election Study.

Usage

data(Issues1980_bb)

Value

An object of class blackbox.

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:

• NNumber of respondents who provided a response to this stimulus.

• cStimulus intercept.

• w1Estimate of the stimulus weight on the first dimension. If viewing the results for a higher dimension, higher dimension results will appear as w2, w3, etc.

• R2The percent variance explained for the stimulus. This increases as more dimensions are estimated.

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:

• c1Estimate of the individual intercept on the first dimension. If viewing the results for a higher dimension, higher dimension results will appear as c2, c3, etc.

fits

A data frame of fit results, with elements listed as follows:

SSESum of squared errors. SSE.explainedExplained sum of squared error. percentPercentage of total variance explained. SEStandard error of the estimate, with formula provided on pg. 973 of the article cited below. singularSingluar 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.

See Also

'Issues1980', 'summary.blackbox', 'plot.blackbox'.

Examples

# NOT RUN {
### Loads issue scales from the 1980 NES.
data(Issues1980)
Issues1980[Issues1980[,"abortion1"]==7,"abortion1"] <- 8	#missing recode
Issues1980[Issues1980[,"abortion2"]==7,"abortion2"] <- 8	#missing recode

### This command conducts estimates, which we instead load using data()
#Issues1980_bb <- blackbox(Issues1980,missing=c(0,8,9),verbose=FALSE,dims=3,minscale=8)
data(Issues1980_bb)

summary(Issues1980_bb)

# }