Description Usage Arguments Details Value See Also Examples

View source: R/restrict.ideal.r

Sets constraints on specified item parameters in Bayesian analysis of roll call data by generating appropriate priors and start values for Markov chain Monte Carlo iterations.

1 2 | ```
constrain.items(obj, dropList = list(codes = "notInLegis", lop = 0),
x, d = 1)
``` |

`obj` |
an object of class |

`dropList` |
a |

`x` |
a |

`d` |
numeric, positive integer, the number of dimensions for which to set up the priors and start values. |

`constrain.items`

and its cousin,
`constrain.legis`

are usefully thougt of as
“pre-processor” functions, generating priors *and* start
values for both the item parameters and the ideal points. For the
items specified in `x`

, the prior mean for each dimension is set
to the value given in `x`

, and the prior precision for each
dimension is set to `1e12`

(i.e., a near-degenerate
“spike” prior). For the other items, the priors are set to a
mean of 0 and precision 0.01. All of the ideal points are given
normal priors with mean 0, precision 1.

Start values are also generated for both ideal points and item
parameters. The start values for the items specified in `x`

are
set to the values specified in `x`

. The list resulting from
`constrain.items`

can then be given as the value for the
parameters `priors`

and `startvals`

when `ideal`

is run. The user is responsible for ensuring that a sufficient number
of items are constrained such that when `ideal`

is run,
the model parameters are identified.

`dropRollCall`

is first called to generate the desired
roll call matrix. The entries of the roll call matrix are mapped to
`c(0,1,NA)`

using the `codes`

component of the
`rollcall`

`object`

. See the discussion in the
documentation of `ideal`

for details on the generation of
start values.

a list with elements:

`xp` |
prior means for ideal points. A matrix of dimensions number
of legislators in |

`xpv` |
prior meansprecisions for ideal points. A matrix of dimensions number
of legislators in |

`bp` |
prior means for item parameters. A matrix of dimensions number
of items or votes in |

`bpv` |
prior meansprecisions for item parameters. A matrix of dimensions number
of items or votes in |

`xstart` |
start values for ideal points. A matrix of dimensions number
of legislators in |

`bstart` |
start values for ideal points. A matrix of dimensions number
of items or votes in |

`rollcall`

, `ideal`

,
`constrain.legis`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | ```
## Not run:
data(s109)
f <- system.file("extdata","id1.rda",package="pscl")
load(f)
id1sum <- summary(id1,include.beta=TRUE)
suspect1 <- id1sum$bSig[[1]]=="95
close60 <- id1sum$bResults[[1]][,"Yea"] < 60
close40 <- id1sum$bResults[[1]][,"Yea"] > 40
suspect <- suspect1 & close60 & close40
id1sum$bResults[[1]][suspect,]
suspectVotes <- dimnames(id1sum$bResults[[1]][suspect,])[[1]]
## constraints on 2d model,
## close rollcall poorly fit by 1d model
## serves as reference item for 2nd dimension
cl <- constrain.items(s109,
x=list("2-150"=c(0,7),
"2-169"=c(7,0)),
d=2)
id1Constrained <- ideal(s109,
d=2,
meanzero=TRUE,
priors=cl,
startvals=cl,
maxiter=1e5,
burnin=1e3,
thin=1e2)
summary(id1Constrained,include.beta=TRUE)
## End(Not run)
``` |

pscl documentation built on Aug. 30, 2017, 5:08 p.m.

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