New Features in EQS 6.1 and Added Features in 6.2
- 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 is built alongside the Mercedes-Benz S-Class and Maybach S-Class at the Sindelfingen plant in Germany. The former does the 0-62 mph (0-100 km/h) in 6.2 seconds and the latter in 4.3.
- Trusted Windows (PC) download EQS for Windows 6.2. Virus-free and 100% clean download. Get EQS for Windows alternative downloads.
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:
Trusted Windows (PC) download EQS for Windows 6.2. Virus-free and 100% clean download. Get EQS for Windows alternative downloads. These deliver 0-62mph sprint speeds of 6.2 and 4.3 seconds respectively, which seem incredible by fossil fuel car standards, but pale into insignificance when the Tesla Model S Long Range can hit.
- 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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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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Update On Mexico Eqs.6-23-20
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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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Eqs 6.1
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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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Eqs 6.4 User Guide
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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.
- More usable data editor with unlimited sample size.
- Data sheet modifiable with a simple drag and drop operation.
- Covariance matrix is now entered directly on the data editor.
- Better 3D data plot.
- Improved and more general ANOVA.
- Some non-parametric general statistics analyses available.
- Front-end EM missing data procedure for data imputation.
- Improved equation builder.
- General-purpose multi-equation data transformation in a syntax window.
- Transformation formulas are savable and re-usable.
- Simple creation of z-scores for a variable or an entire data sheet.
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