ADDED FEATURES IN 6.4

NEW FEATURES

EQS 6.4 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 all users with an older version to 6.4 to update their program to the latest version.

New and Improved Normal Theory and Missing Data Methods

Corrected Normal Theory Methods for Non Normal and Missing Data

Heterogeneous Kurtosis Methods

Arbitrary Distribution Methods

Case (Subject) Weighting Methods

Multi-Level Models

Resampling and Simulation Methods and Statistics

Modeling Features and Approaches

Diagrammer

Resampling and Simulation Methods and Statistics

New And Improved Normal Theory And 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.

Corrected Normal Theory Methods For Non Normal And 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-Bentler correct statistics for non-normal missing data.

Heterogeneous Kurtosis Methods

  • BentlerBerkane and Kano statistics for heterogeneous kurtoses.

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.

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

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.

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.

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).

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.

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.