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

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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 data is specified, a filename (string) must be provided for saving the data in text format (blank separated; see details)

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

TRUE if estimation was successful, FALSE otherwise

model.info

General model information

pval

p-values 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

R-squared 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