R: summary of an ideal object

summary.ideal {pscl} | R Documentation

## summary of an ideal object

### Description

Provides a summary of the output from ideal point estimation contained in an object of class `ideal`.

### Usage

    ## S3 method for class 'ideal'
    summary(object, prob=.95,
                  burnin=NULL,
                  sort=TRUE,
                  include.beta=FALSE,...)

### Arguments

`object` | an object of class `ideal`.
`prob` | scalar, a proportion between 0 and 1, the content of the highest posterior density (HPD) interval to compute for the parameters
`burnin` | of the recorded MCMC samples, how many to discard as burnin? Default is `NULL`, in which case the value of `burnin` in the `ideal` object is used.
`sort` | logical, default is `TRUE`, indicating that the summary of the ideal points be sorted by the estimated posterior means (lowest to highest)
`include.beta` | whether or not to calculate summary statistics of beta, if beta is available. If the item parameters were not stored in the `ideal` object, then `include.beta` is ignored.
`...` | further arguments passed to or from other functions

### Details

The test of whether a given discrimination parameter is distinguishible from zero first checks to see if the two most extreme `quantiles` are symmetric around .5 (e.g., as are the default value of .025 and .975). If so, the corresponding quantiles of the MCMC samples for each discrimination parameter are inspected to see if they have the same sign. If they do, then the corresponding discrimination parameter is flagged as distinguishible from zero; otherwise not.

### Value

An item of class `summary.ideal` with elements:

`object` | the name of the ideal object as an `unevaluated` `expression`, produced by `match.call()$object`
`xm` | `n` by `d` matrix of posterior means for the ideal points
`xsd` | `n` by `d` matrix of posterior means for the ideal points
`xHDR` | `n` by 2 by `d` array of HDRs for the ideal points
`bm` | `m` by `d+1` matrix of posterior means for the item parameters
`bsd` | `m` by `d+1` matrix of posterior standard deviation for the item parameters
`bHDR` | `m` by 2 by `d+1` array of HDRs for the item parameters
`bSig` | a `list` of length `d`, each component a vector of length `m`, of mode `logical`, equal to `TRUE` if the corresponding discrimination parameter is distinguishible from zero; see Details. If `store.item` was set to `FALSE` when `ideal` was invoked, then `bSig` is a list of length zero.
`party.quant` | if party information is available through the `rollcall` object that was used to run `ideal`, then `party.quant` gives the posterior mean of the legislators' ideal points by party, by dimension. If no party information is available, then `party.quant=NULL`.

### Note

When specifying a value of `burnin` different from that used in fitting the `ideal` object, note a distinction between the iteration numbers of the stored iterations, and the number of stored iterations. That is, the `n`-th iteration stored in an `ideal` object will not be iteration `n` if the user specified `thin>1` in the call to `ideal`. Here, iterations are tagged with their iteration number. Thus, if the user called `ideal` with `thin=10` and `burnin=100` then the stored iterations are numbered `100, 110, 120, ...`. Any future subsetting via a `burnin` refers to this iteration number.

### Author(s)

Simon Jackman simon.jackman@sydney.edu.au

### See Also

`ideal`

### Examples

    f <- system.file("extdata","id1.rda",package="pscl")
    load(f)
    summary(id1)

    ## Not run:
    data(s109)
    cl2 <- constrain.legis(s109,
                           x=list("KENNEDY (D MA)"=c(-1,0),
                             "ENZI (R WY)"=c(1,0),
                             "CHAFEE (R RI)"=c(0,-.5)),
                           d=2)
    id2Constrained <- ideal(s109,
                            d=2,
                            priors=cl2,      ## priors (w constraints)
                            startvals=cl2,   ## start value (w constraints)
                            store.item=TRUE,
                            maxiter=5000,
                            burnin=500,
                            thin=25)

    summary(id2Constrained,
            include.items=TRUE)

    ## End(Not run)

[Package pscl version 1.5.2 Index]