anchors (version 3.0-8)

chopit: Compound Hierarchical Ordered Probit (CHOPIT)

Description

Estimate Compound Hierarchical Ordered Probit (CHOPIT) model

Usage

chopit(formula, data, subset, options=anchors.options(), na.action = na.omit)

Arguments

formula

A list of named formulas giving a symbolic description of the model to be fit. See 'Details' below.

data

An anchors.data class object. See 'Details' below.

subset

Logical expression indicating elements or rows to keep: missing values are taken as false; equivalent to function subset.

options

An anchors.options class object. See 'Details' below.

na.action

Specify the "NA action" which should be applied to 'data'. Default is R standard option 'na.omit'; can also be set to 'na.fail'.

Value

options and anchors.options()

Invoking the chopit model without options, chopit(formula, data) is equivalent to,

chopit(formula, data,
                  options = anchors.options( normalize ="self",
                                             vign.var  = "hetero",
                                             linear    = TRUE,
                                             analytical= TRUE,
                                             optimizer= "optim"))
					   

To change an option setting, pass one or more of the following tagged values to the options argument via the anchors.options() function. Alternative vluaes for options are passed using the tag=new.value syntax (same with the par() function. To see all default values, type anchors.options() without arguments.

With optimizer = "optim", there are additional options for specifying how optim is invoked.

With optimizer = "genoud", there are additional options for specifying how genoud is invoked.

Details

The formula syntax is designed to allow the same list of formulas to be used for both anchors and chopit. If a user would like to use exactly the same cases with chopit as with anchors (i.e., drop cases with any missing responses or missing cpolr values), and vise versa (i.e., also drop any case with missing values in the tau=, tau1= formulae), then the user should use the same list of formula for all methods and use the option anchors.options(delete="maximal"). See example below.

Only options relevant to chopit are discussed here.

The named list() of formulas may include

self: self-response variable and linear predictors.

vign: vignette responses, bound together by cbind (as in glm binomial syntax), with ONLY '~ 1' as RHS of equation (formulas must have RHS). Must be present for all methods.

tau : linear predictors of cutpoints, NO LHS variable.

tau1 : Optional. linear predictors of only the mean shift of all cutpoints NO LHS variable. Default: if omitted, set equal to formula specified in 'tau='. Example:

    fo <- list(self = xsayself ~ age,
              vign = cbind(xsay3,xsay1)    ~ 1,
              tau  = ~ age + china,
              tau1 = ~ age + china + male  )
	      

One can also use a single formula as a short hand: specifying

fo <- self ~ vign1 + vign2

is equivalent to

    fo <- list(self = self ~ 1
               vign = cbind(vign1,vign2) ~ 1,
               tau  = ~ 1,
               tau1 = ~ 1,
               cpolr= ~ 1)
	     

All of the response variables must be in the form of consequetive non-negative numeric integers, i.e., 1, 2, ... K. ** anchors currently does not support factor responses.**

The chopit model does *not* by default require that every respondent answer all vignette or the self questions to be included in the model; only answers that are non-missing are used in the likelihood function.

References

Wand, Jonathan; Gary King; and Olivia Lau. (2007) ``Anchors: Software for Anchoring Vignettes''. Journal of Statistical Software. Forthcoming. copy at http://wand.stanford.edu/research/anchors-jss.pdf

Wand, Jonathan and Gary King. (2007) Anchoring Vignetttes in R: A (different kind of) Vignette copy at http://wand.stanford.edu/anchors/doc/anchors.pdf

King, Gary; Christopher J.L. Murray; Joshua A. Salomon; and Ajay Tandon. "Enhancing the Validity and Cross-cultural Comparability of Survey Research," American Political Science Review, Vol. 98, No. 1 (February, 2004): 191-207, copy at http://gking.harvard.edu/files/abs/vign-abs.shtml

See Also

anchors, anchors.data, anchors.options, optim, genoud

Examples

##
data(mexchn)
fo <- list(self = xsayself ~ 1,
           vign = xsay3    ~ 1,
           tau  =           ~1 )
out1  <- chopit( fo, mexchn)
summary(out1)