basicspace (version 0.13)

aldmck: Aldrich-McKelvey Scaling

Description

aldmck 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, developed by John Aldrich and Richard McKelvey in 1977, is restricted to estimating data with no missing values and only in one dimension. Please refer to the blackbox and blackbox_transpose functions in this package for procedures that accomodate missing data and multidimensionality estimates.

Usage

aldmck(data, respondent = 0, missing=NULL, polarity, verbose=FALSE)

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.

respondent

integer, specifies the column in the data matrix of the stimuli that contains the respondent's self-placement on the scale. Setting respondent = 0 specifies that the self-placement data is not available. Self-placement data is not required to estim

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 vec

polarity

integer, specifies the column in the data matrix of the stimuli that is to be set on the left side (generally this means a liberal)

verbose

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

Value

• An object of class aldmck.
• legislators
  vector, containing the recovered locations of the stimuli. The names of the stimuli are attached if provided as column names in the argument data, otherwise they are generated sequentiall as 'stim1', 'stim2', etc.
• respondents
  matrix, containing the information estimated for each respondent. Observations which were discarded in the estimation for missing data purposes have been NA'd out:

  • intercept

  {Intercept of perceptual distortion for respondent.} weight{Weight of perceptual distortion for respondent.} idealpt{Estimated location of the respondent. Note that these positions are still calculated for individuals with negative weights, so these may need to be discarded. Note that this will not be calculated if self-placements are not provided in the data.} selfplace{The self-reported location of the individual, copied from the data argument if respondent is not set to 0. } polinfo{Estimated political information of respondent, calculated as the correlation between the true and reported stimulus locations. The validation of this measure is provided in the article by Palfrey and Poole in the references. Note that this measure is included even for respondents that were not used in the estimation. Individuals with negative weights have also been assigned a political information score of 0, rather than negative scores.}

item

• eigenvalues
• AMfit
• N
• N.neg
• N.pos

References

John H. Aldrich and Richard D. McKelvey (1977) ``A Method of Scaling with Applications to the 1968 and 1972 Presidential Elections.'' American Political Science Review. 71(1), 111-130. Thomas R. Palfrey and Keith T. Poole (1987) ``The Relationship between Information, Ideology, and Voting Behavior.'' American Journal of Political Science. 31(3), 511-530. Keith Poole. http://voteview.ucsd.edu/aldmck.htm

See Also

'LC1980', 'summary.aldmck', 'plot.aldmck', 'plot.cdf'.

Examples

### Loads and scales the Liberal-Conservative scales from the 1980 NES.
data(LC1980)
result <- aldmck(data=LC1980, polarity=2, respondent=1, missing=c(0,8,9),verbose=TRUE)
summary(result)
plot.aldmck(result)