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Informative Hypotheses


This site informs you about the research output with respect to two information criteria that can evaluate theory-based hypotheses: GORIC and GORICA.

 Theory-based hypotheses

Researchers are often interested in theory-based hypotheses: for example, medicine A works better than medicine B, which works better than a placebo (in an anova model: µA > µB > µPlacebo); or number of children is a stronger predictor for happiness than income (in a regression model with standardized parameters: βNC > βInc). These theory-driven hypotheses can be evaluated with generalizations of the Akaike information criterion (AIC): the GORIC (Generalized Order-Restricted Information Criterion) and the GORICA (an approximation of the GORIC). These AIC-like criteria can examine inequality constraints / order restrictions as in the examples. They evaluate a set of competing hypotheses (which are thus based on expectations as opposed to a set of all possible combinations which are examined when exploring for theories). The GORIC or GORICA then select the best model/hypothesis out of a set.



Currently, the GORIC is applicable to multivariate normal linear models .

In case you are interested in applying the GORIC to evaluate informative hypotheses (also in the context of replicating studies), you might be interested in the following Postgraduate course (in July): Theory Based Hypothesis Evaluation Using the P-value, Bayes Factor, and Information Criteria.

GORIC is also a software package that calculates the GORIC for traditional and order-restricted hypotheses.
GORIC is licensed under the GNU General Public License Version >=2

Click here to download the stand-alone version of  GORIC (of Rebecca M. Kuiper).
Click here to download GORIC with a Windows user interface  (of Rebecca M. Kuiper).
Click here to visit the download page of the R-package for GORIC (of Daniel Gerhard and Rebecca M. Kuiper). to visit the download page of the R-package for GORIC (of Daniel Gerhard and Rebecca M. Kuiper).
Click here to visit the tutorial page on using the GORIC with the R-package Restrictor (of Leonard Vanbrabant).

If you use GORIC, you give credits to the developers by referring to:

  • Kuiper, R. M., & Hoijtink, H. (2013). A Fortran 90 program for the generalization of the order restricted information criterion. Journal of Statistical Software, 54(8)1-19.

Other GORIC literature:



The GORICA can be applied to a broad range of models.

Upcoming GORICA literature:

  • Yasin Altınısık, Esther Nederhof, Herbert Hoijtink, Albertine J. Oldehinkel, and Rebecca M. Kuiper (unpublished). Evaluation of Inequality Constrained Hypotheses Using a Generalization of the AIC.
  • Yasin Altınısık, Roy Hessels, and Rebecca M. Kuiper (unpublished). An AIC-based Information Criterion Evaluating (In)equality Constrained Hypotheses for Contingency Tables.
  • Yasin Altınısık and Rebecca M. Kuiper (unpublished). The GORICA Applied: An AIC-Based Information Criterion for Evaluating Informative Hypotheses.