Simulated data file = ""

A file of simulated data can be constructed from the measures estimated (or anchored) for the main analysis. It will have one simulated observation for each observation in the original data file. Each simulation is unique, so that multiple different simulations can be obtained with the Output Files menu clicking on Simulated Data file.

Simulated data file = filename

The simulated data can be analyzed using Data=filename in the original specification file (or enter at Extra specifications? prompt). Comment out any Dvalues= specifications in the original specification file.

The simulated data file has the basic Facets data format:

; Simulated data matching the empirical data structure

; Ratings of Scientists (edited to illustrate ambiguity in measurement)

; matching: C:\FACETS\examples\subsets.txt

1,2,1,7 ; 9 ; 1,2,1 are facet elements. 7 is simulated. 9 is the original data value.

1,2,2,7 ; 7

1,2,3,4 ; 5

1,2,4,9 ; 8

1,2,5,3 ; 5

Example 1: Simulate and analyze 1000 Facets data sets from lfs.txt in one folder.

Save the following as x.bat in c:\Facets\examples, and then double-click on x.bat.

If you are using Minifac, then change \Facets to \Minifac -

SET /A COUNT=1

:LOOP

echo Loop number %COUNT%

rem do this 1000 times

IF %COUNT% == 1001 GOTO END

rem generate simulate data file from lfs.txt

START /WAIT ..\Facets BATCH=YES lfs.txt specfile.out.txt simul=s%COUNT%.txt

rem analyze simulated file

START /WAIT ..\Facets BATCH=YES lfs.txt s%COUNT%.out.txt data=s%COUNT%.txt

SET /A COUNT=COUNT+1

GOTO LOOP

:END

PAUSE

Example 2: Simulate data corresponding to various types of rater behavior.

1. We conceptualize the rater effects we want to investigate, for instance "halo effect".

2. We formulate statistical models corresponding to each of the rater effects, for instance "halo effect" = all observations by a rater of a person are the same as the first observation.

3. We propose the parameter values which would correspond to each of those rater effects.

4. We use the statistical models of 2. and the parameter values of 3. to generate the data.

If the models in 2. are Rasch models that can be simulated by Facets, then we can use the parameter values in 3. as anchor values in Facets analyses. Then generate data in 4. using the "simulate data file" option in Facets. In order to make the Facets program run, we give it some data, but it does not matter what the data are, because Facets will use the anchor values, not values estimated from the data, to generate the new data.

If the models in 2. are not models that can be simulated by Facets, then we can formulate the data directly that match what we intend, for instance 3 3 3 3 3 3 could be one rater-person data string for "halo effect", and 4 4 4 4 4 4 could be another data string. Or we can use general-purpose simulation software, such as Simfit, www.simfit.man.ac.uk