repl {Zelig}R Documentation

Replicating Analyses

Description

The generic function repl command takes zelig or sim output objects and replicates (literally, re-runs) the entire analysis. The results should be an output object identical to the original input object in the case of zelig output. In the case of sim output, the replicated analyses may differ slightly due to stochastic randomness in the simulation procedure.

Usage

repl(object, data, ...)
## Default S3 method:
repl(object, data = NULL, ...)
## S3 method for class 'zelig':
repl(object, data = NULL, prev = NULL, x = NULL, x1 = NULL,
     bootfn = NULL, ...) 

Arguments

object Stored output from either zelig or sim.
data You may manually input the data frame name rather than allowing repl to draw the data frame name from the object to be replicated.
prev When replicating sim output, you may optionally use the previously simulated parameters to calculate the quantities of interest rather than simulating a new set of parameters. For all models, this should produce identical quantities of interest. In addition, for if the parameters were bootstrapped in the original analysis, this will save a considerable amount of time.
x When replicating sim output, you may optionally use an alternative setx value for the x input.
x1 When replicating sim output, you may optionally use an alternative setx object for the x1 input to replicating the sim object.
bootfn When replicating sim output with bootstrapped parameters, you should manually specify the bootfn if a non-default option was used.
... Additional arguments passed to either zelig or sim.

Value

For zelig output, repl will create output that is in every way identical to the original input. You may check to see whether they are identical by using the identical command.
For sim output, repl output will be will be identical to the original object if you choose not to simulate new parameters, and instead choose to calculate quantities of interest using the previously simulated parameters (using the prev option. If you choose to simulate new parameters, the summary statistics for each quantity of interest should be identical, up to a random approximation error. As the number of simulations increases, this error decreases.

Author(s)

Kosuke Imai <kimai@princeton.edu>; Gary King <king@harvard.edu>; Olivia Lau <olau@fas.harvard.edu>

See Also

zelig, setx, and sim. In addition, the full Zelig manual may be accessed online at http://gking.harvard.edu/zelig.

Examples

data(turnout)
z.out <- zelig(vote ~ race + educate, model = "logit", data = turnout[1:1000,])
x.out <- setx(z.out)
s.out <- sim(z.out, x = x.out)
z.rep <- repl(z.out)
identical(z.out$coef, z.rep$coef)
z.alt <- repl(z.out, data = turnout[1001:2000,])
s.rep <- repl(s.out, prev = s.out$par)
identical(s.out$ev, s.rep$ev)

[Package Zelig version 3.1-0 Index]