Learn R Programming

anchors (version 3.0-8)

anchors.order: Calculate frequency of vignette orderings

Description

Calculate frequency of vignette orderings

Usage

anchors.order(formula, data, ties = c("set", "nominal", "random", "mset"), subset, 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
A data frame or matrix. See Details below.
ties
"set": Groups ties as sets "nominal": Breaks ties by order of vignettes given "random": Breaks ties randomly
subset
Logical expression indicating elements or rows to keep: missing values are taken as false; equivalent to function subset.
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

Each vignette is represented by the integer indexing it's place as passed to the function. For example, letfo <- list(vign = cbind(vign1,vign2,vign3))then 1=vign1, 2=vign2, 3=vign3. In the case of an anchors.order object produced with the option ties="set", tied variables are represented by being included in brackets.
   anchors.order( fo, data, ties="set")
   
then a row with "{1,3},2" indicates that vign1 and vign3 are tied, and vign2 has a higher value than both of them.

Details

The formula syntax is designed to allow the same list of formulas to be used for both anchors and chopit and anchors.order. If a user would like to use exactly the same cases with chopit as with anchors.order (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 anchors.order are discussed here.

The named list() of formulas may include

self: LHS self-response variable; RHS is simply 1 (needed to define a formula); actually anything can be put on the RHS, and it will not by default be used.

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

Example:

    fo <- list(self = xsayself ~ 1,
              vign = cbind(xsay3,xsay1)    ~ 1)
	      

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)
	     

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 method="B" and "C" requires that cases with any response that is missing be dropped. Any cases with missing values the covariates specified in the cpolr= formula are also dropped. BUT by default these methods ignore missing values in the covariates specified by tau=, tau1=, or the right hand side of self=.

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

Gary King and Jonathan Wand. "Comparing Incomparable Survey Responses: New Tools for Anchoring Vignettes," Political Analysis, 15, 1 (Winter, 2007): Pp. 46-66, copy at http://gking.harvard.edu/files/abs/c-abs.shtml.

See Also

anchors,barplot.anchors.order

Examples

Run this code
data(mexchn)
z <- anchors.order( ~ xsay1 + xsay2 + xsay3 + xsay4 + xsay5, mexchn, ties  = "set")
summary(z,top=10,digits=3)
barplot(z)

z <- anchors.order( ~ xsay5 + xsay4 + xsay3 + xsay2 + xsay1, mexchn, ties  = "set")
summary(z,top=10,digits=3)

## other option
z <- anchors.order( ~ xsay5 + xsay4 + xsay3 + xsay2 + xsay1, mexchn, ties  = "nominal")
summary(z,top=10,digits=3)
barplot(z)


Run the code above in your browser using DataLab