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New in GAUSS 25

GAUSS 25 will transform your workflow with intuitive tools for data exploration, advanced diagnostics, and seamless model comparison.

Comprehensive Panel Data Tools

GAUSS 25 transforms the way you load, analyze, and explore your data, giving you the intuitive tools you need.

Comprehensive Panel Data Tools in GAUSS 25

Explore Panel Data Characteristics

  • Explore overall, within-group, and between group summary statistics with pdSummary.

Code Example for <code>pdSummary</code> in GAUSS 25
Example of output of <code>pdSummary</code> in GAUSS 25

Code Example for <code>pdSize</code> in GAUSS 25
Example of output of <code>pdSize</code> in GAUSS 25

Prepare Panel Data for Modeling

  • Automated and intelligent detection of group and time variables for seamless workflows.
  • Sort panel data instantly with detected group and time variables using pdSort.
  • New pdLag and pdDiff for calculating panel data lags and differences.

Code Example for <code>pdLag</code> in GAUSS 25
Example of output of <code>pdLag</code> in GAUSS 25

New Hypothesis Testing

The new waldTest procedure provides a powerful and intuitive tool for testing linear hypotheses after estimation.

  • Perform post-estimation hypothesis testing after OLS, GLM, GMM, and Quantile Regression.
  • Specify hypotheses effortlessly using variable names.
  • Comprehensive support for linear combination of variables in hypotheses.

Code Example for <code>waldTest</code> in GAUSS 25
Example of output of <code>waldTest</code> in GAUSS 25

Check for the equivalency of slopes across quantiles after Quantile Regression with the new qfitSlopeTest.

Code Example for <code>qfitSlopeTest</code> in GAUSS 25
Example of output of <code>qfitSlopeTest</code> in GAUSS 25

Enhanced Result Printouts

GAUSS 25 now offers expanded model diagnostics and consistent printouts across all estimation procedures.

Code Example for an enhanced result printout in GAUSS 25
Example for an enhanced result printout in GAUSS 25

These enhancements make it easier than ever to compare models, explore results, and gain deeper insights with confidence.

Improved Performance and Speed-ups

  • Expanded two-way tabulation using tabulate to find row or column percentages.
  • The gmmFitIV unction now uses metadata from dataframes to identify and report variable names and supports the "by" keyword.
  • Optional specification of sorted data provides speed improvements when using counts.
  • The plotFreq procedure now supports the "by" keyword for counting frequencies across groups.

Code Example for <code>plotFreq</code> in GAUSS 25
Example of output of <code>plotFreq</code> in GAUSS 25

  • saved now automatically detects and saves categorical and string variables using their labels for Excel files.

See the complete list of what's new in GAUSS 25 (Changelog)