EQS FOR WINDOWS
Already known for combining technical sophistication
with ease of use, EQS for Windows makes structural equations modeling even easier with Diagrammer, EQS' new model drawing tool.
Make just a few clicks on the mouse and you can draw a diagram. Once your model is
drawn, choose Build EQS from the scroll-down menu and EQS runs your model based on the
diagram. Use of command language is no longer necessary!
When you are ready to present results, simply print the diagram directly or cut and paste
into your favorite word processor for final production.
Click On A Feature Below To Learn More:
- Spreadsheet Type Data Editor and Flexible
Data Import Options
- Missing Data Handling and Missing Data
Imputation
- Comprehensive Data Manager
- Data Exploration Tools With Point-and-Click Data
Plots
- Basic Statistics Including Multiple Regression
and Factor Analysis
- Diagrammer - SEM Diagram Drawing Tool to
Create and Report A Model
- Modeling Features
- Hardware and Software Requirements
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SPREADSHEET TYPE DATA EDITOR AND FLEXIBLE DATA
IMPORT OPTIONS

- Spread-sheet type data editor with data entry
function
- Cut and paste to and from other data sheet
- Support DDE (Dynamic Data Exchange)
- Read EQS system ESS files
- Read free field data using a space, tab, or comma as
delimiter
- Import variable names if they are embedded in the
first case
- Read fixed field data using convenient column
specifications
- Read fixed field data using visual tool to define
variable boundary
- Read BMDP PC or 386/Dynamic Save files
- Read Lotus 1-2-3 WK1 files
- Read dBASE III plus DBF files
- Write data file with space or tab delimiter with
variable labels
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MISSING DATA HANDLING AND MISSING DATA IMPUTATION
- Print out missing data diagnosis information
- Print out dichotomized correlation matrix for missing
data
- Support global missing and variable missing value
- Provide interactive and visual missing data map
- Provide Z-score map
- Allow exclusion of cases based on the percentile of
missing variables
- Impute missing variable using its mean
- Impute missing variable using group mean
- Impute missing variable using regression estimator
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COMPREHENSIVE DATA MANAGER
- Simple method to define variable name and category
labels
- Case selection function to split cases and
conditional selection of cases
- Save a subset of data file bases on selected cases
- Save a subset of data by selecting variables
- Transform data
- Join two or more files side by side
- Merge to or more files end to end
- Recode or collapse data using a visual tool
- Point and click to reverse coding of a variable
- Sort records
- Compute moving average and differences of time lag
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DATA EXPLORATION TOOLS WITH POINT
AND CLICK DATA PLOTS
- Line Plot
- Area Plot
- Histogram with a grouping
variable
- Pie Chart
- Bar Chart
- Quantile Plot
- Quantile-Normal Plot (Normal Probability Plot)
- Quantile-Quantile Plot
- Scatter Plot and Matrix Plot with brushing function
- Box Plot
- Error Bar Chart
- Multiple Plot (Combine several plots in on window)
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BASIC STATISTICS INCLUDING MULTIPLE
REGRESSION AND FACTOR ANALYSIS
- Descriptive Statistics
- Frequency Tables
- t-Test
- One-Way and Two-Way ANOVA
- CrossTab
- Multiple Regression and Stepwise
Regression
- Covariance and Correlation with
list-wise or pair-wise deletion
- Factor Analysis with capable of
exporting the factor loading matrix to EQS
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DIAGRAMMER
- EQS' DRAWING TOOL TO CREATE AND
REPORT A MODEL
- Very flexible drawing tool
- Useful editing tool such as flip, rotation,
alignment, group, and break group options
- Point and drag to resize a diagram
- View starting value, parameter estimates, and
standardized solutions in a path
- View a subset of diagram and print out only what is
visible on the screen
- Point and click to build a complex factor structure
- Build EQS model automatically without having a syntax
error message
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MODELING FEATURES
Data Handling:
- Raw data files (both ASCII and ESS formats)
- Covariance matrix (both ASCII and ESS formats)
- Automatic listwise deletion of cases
- Moment matrix (covariance matrix and mean)
- Outlier detection
- Test of multivariate normality
Model Specification:
- Symbols of model notation (V, F, E, D)
- Intuitive equation type model specification
- Simple equality constraints
- General equality constraints
- Inequality constraints
- Automatic starting values
Methods of Estimation and Statistics:
- Least squares
- Generalized least squares
- Maximum likelihood
- Multiple sample analysis
- Analysis of means and covariances
- Asymptotic distribution free
- Elliptical corrections
- Satorra-Bentler scaling correction
- Robust standard errors
- Akaike Information Criterion
- Bentler-Bonnet fit indices
- Comparative fit index
- Other fit indices include:
GFI, AFGI, RMR, standardized RMR, IFI, MFI, and RMSEA
- Yaun-Bentler distributed-free statistics
- Wright-type standardized solution
- Categorical dependent variables
Simulation:
- Easy-to-use Monte Carlo simulation
- Bootstrap, jackknife
- Generate non-normal and categorical data
- Generate normal & contaminated normal data
Model Modifications:
- Wald test
- Wald test against any constants
- Rank correlation between two model estimates
- Univariate modification indices
- Multivariate Lagrange Multiplier (LM) test
- LM tests on constraints
- LM tests of cross-group equality constraints
- LM test on individual fixed parameters
- Control sets of fixed parameters in LM test
- Exclusion of meaningless paths in LM
Output Control:
- Correlations of parameter estimates
- Effect decomposition
- Standardized effect decomposition
- Model covariance/correlation matrices
- New model setup with optimal starting values
- New model setup with consideration of Wald and LM
results
- Summary statistics on an output file for further
analysis
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HARDWARE AND SOFTWARE REQUIREMENTS
FOR WINDOWS
- IBM PC 386, 486, Pentium, or compatibles
- A math co-processor
- At least 8 MB of RAM
- At least 5 MB of free disk space
- MS Windows 3.1(enhanced mode), Windows 95, 98, 2000
or Win NT
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