Eqs 6.1
Eqs 6.4 User Guide
Update On Mexico Eqs.6-23-20

EQS 6, have been unparalleled in the recent history of statistical psychometrics. Equally invaluable programming contributions to this research were made by Eric J. Wu and, more recently, David Sookne, who also updated several chapters of this Manual. Valuable drafts of Chapters 10-13 were provided by Seongeun Kim. The EQS 450+ will launch from 0-62mph (0-100km/h) in 6.2 seconds whilst the EQS 580 4MATIC will manage the same sprint in 4.3 seconds. Both models will reach a limited top speed of 126mph (203km/h). If technology changes the world, there is only one way to find out what the future holds - bringing tomorrow’s technology to life, today.

EQS 6.2 for Windows (Build 105) zip file (2013 version, ) EQS 6.2 for Windows (Build 107) zip file (2014 version, ) EQS 6.2 Bu'ld 107 fixes a bug on Diagrammer. When you create a model with Diagrammer and choose AGLS as estimation method.
Trusted Windows (PC) download EQS for Windows 6.2. Virus-free and 100% clean download. Get EQS for Windows alternative downloads.
Trusted Windows (PC) download EQS for Windows 6.2. Virus-free and 100% clean download. Get EQS for Windows alternative downloads.

New Features in EQS 6.1 and Added Features in 6.2

EQS 6.1 is available in a downloadable program with Program Manual and User's Guide in PDF format. Please note that we provide free Technical Support to all of our Licensed users. We would like to encourage EQS 6.1 users to periodically go back to their download instructions and use the Web address to update their program to the latest Build.

Click on any of the following new features available on EQS 6.1 to learn more:

Eqs 6.1

New and Improved Normal Theory and Missing Data Methods
Arbitrary Distribution Methods
Resampling and Simulation Methods and Statistics

Added Features in 6.2

1. Nesting and Equivalence Tests

2. Automatic Difference Tests

3. Exploratory Factor Analysis (with Bifactor Rotation)

4. Smoothing a Correlation Matrix

5. New Categorical Data Handling Options

6. New Formula for Robust RMSEA

7. Satorra-Bentler Mean and Variance adjusted

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NEW AND IMPROVED NORMAL THEORY (EM-TYPE MISSING DATA) METHODS

Jamshidian-Bentler EM-type missing data procedures for one or multiple samples.
Kim-Bentler test of missing completely at random (MCAR), including homogeneity of means and covariances.
LM and Wald tests in multi-sample analysis.
Bentler-Yuan test for potential structured mean models.
Bentler-Raykov corrected R-square for nonrecursive models.
Regression and Bentler-Yuan optimal GLS factor scores computed and saved.
Advanced start values for structured mean analysis.
Standard errors for total effects.
Internal consistency reliability and maximal reliability coefficients for composite based on a 1-factor model.
Reliability coefficient rho for a factor model.
Cronbach’s alpha, greatest lower bound reliability, Bentler’s dimension-free lower bound reliability and Shapiro’s lower bound reliability for a weighted composite.

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Eqs 6.4 User Guide

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CORRECTED NORMAL THEORY METHODS FOR NON-NORMAL & MISSING DATA

Satorra-Bentler statistic for multiple methods and multi-sample analysis.
Correct (including Satorra-Bentler robust) standard errors for indirect and total effects.
Satorra-Bentler information matrix for LM test.
Yuan-Bentler F-test and Yuan-Bentler-Browne residual-based statistics.
Yuan-Bentlercorrect statistics for non-normal missing data.

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HETEROGENEOUS KURTOSIS METHODS

Bentler, Berkane and Kano statistics for heterogeneous kurtoses.
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ARBITRARY DISTRIBUTION METHODS

Asymptotically distribution free (ADF) mean and covariance structure methodology.
Yuan-Bentler corrected chi-square and F-tests.
Yuan-Bentler corrected ADF standard errors.
ADF analysis of correlation structures.

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CASE (SUBJECT) WEIGHTING METHODS

A priori case weights for weighted mean and covariance structure analysis (e.g., for complex sample surveys).
Yuan-Bentler case-robust methodology for outliers and influential observations.

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Update On Mexico Eqs.6-23-20

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MULTI-LEVEL MODELS

HLM-like (Chou, Bentler and Pentz) multilevel methodology for latent variables.
Bentler-Liang maximum likelihood multilevel methodology.
Muthén’s MUML multilevel methodology.

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RESAMPLING AND SIMULATION METHODS AND STATISTICS

Standard errors for standardized solution etc via bootstrap.
Model based bootstrapping (extended Beran-Bollen-Stine methodology).
Expanded simulation capacities: multiple group and MCAR data generation.
Deng-Lin FMRG random number generator.

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MODELING FEATURES AND APPROACHES

/MODEL paragraph for simple model specification (virtually eliminates the need for /EQUATION, /VARIANCE, and /COVARIANCE sections). Many equations are built with a few simple script commands.
Command script for building many constraints simply.
Maximum number of model variables (including categorical) raised to 200.
SAVE paragraph for saving imputed data and factor scores.
Statistics and indexes for Satorra-Bentler 'robust' statistics reportable separately.
EQS output optional in HTML format.
EQS output optional in matrix format or compact format (instead of equation format).

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DIAGRAMMER

Advanced Diagrammer for creating and reporting a model.
Wizard system to create path, factor, structural equation, and latent growth curve models.
Polynomial-orthogonal coefficients computed for latent growth curve model.

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USER INTERFACE IMPROVEMENTS

Project manager for organizing and retrieving all analyses from a treeview outline.
Transporter for moving a project and its related analyses with a simple drag and drop operation.
Mo

Eqs 6.2