Run EQS from R
Description
Calls an EQS script file from R, executes EQS, and imports the results into R. Basically
it is a wrapper function of call.eqs
and the subsequent read.eqs
.
Usage
1 2  semdiag.run.eqs(EQSpgm, EQSmodel, serial, Rmatrix = NA, datname = NA, LEN = 2000000)
semdiag.call.eqs(EQSpgm, EQSmodel, serial, Rmatrix = NA, datname = NA, LEN = 2000000)

Arguments
EQSpgm 
String containing path where EQS is located (see details) 
EQSmodel 
String containing path where .eqs script file is located (see details) 
serial 
EQS serial number as integer value 
Rmatrix 
Optional matrix argument if data or covariances are stored in R 
datname 
If 
LEN 
Integer containing number of working array units. By default, it is 2000000 8 bytes units 
Details
If the path in EQSpgm
and EQSmodel
contains a blank, single quotes and double quotes
are required in argument. See EQSpgm
argument in examples. The last statement in the EQSpgm
argument refers
to the name of the executable program file. Under Windows it is ".../WINEQS"
(referring to WINEQS.exe), under Mac ".../MACEQS"
and
under Linux ".../EQS"
. When specifying the path, use slash instead of backslash.
The .ETS, .CBK and .ETP files are written in the directory where the .eqs file is located. Note that these 3 files must be in the same directory than the .eqs file.
The argument datname
must match with the input data specified in the corresponding .eqs file.
This option can be used for simulations: Generate data in R, run.eqs()
on with the corresponding
data
argument, pick out the relevant return values.
The value list below provides objects for the full EQS output. If in EQS some objects are not computed, the corresponding values in R are NA
.
Value
Returns a list with the following objects:
success 

model.info 
General model information 
pval 
pvalues for various test statistics 
fit.indices 
Variuos fit indices 
model.desc 
Descriptive measures 
Phi 
Phi matrix 
Gamma 
Gamma matrix 
Beta 
Beta matrix 
par.table 
Parameter table (with standard errors) 
sample.cov 
Sample covariance matrix 
sigma.hat 
Model covariance matrix 
inv.infmat 
Inverse information matrix 
rinv.infmat 
Robust inverse information matrix 
cinv.infmat 
Corrected inverse information matrix 
derivatives 
First derivatives 
moment4 
Matrix with 4th moments 
ssolution 
Standardized elements 
Rsquared 
Rsquared measures 
fac.means 
Factor means 
var.desc 
Descriptive measures for the variables (univariate statistics) 
indstd 
Independent variable standardization vector 
depstd 
Dependent variable standardization vector 
Author(s)
Patrick Mair, Eric Wu
References
Bentler, P. M. (1995). EQS Program Manual. Encino, CA: Multivariate Software Inc.
See Also
semdiag.read.eqs
, semdiag.call.eqs