Computational Efficiency: Fast execution for binary
data
Technical Details
Test Statistic: Uses modified Pearson chi-square
with correction term
Distribution: Standard normal under null
hypothesis
Expected Value: G - 2 for grouped binary data
Variance: 2(G - 2) for grouped binary data
References
Farrington, C. P. (1996). On Assessing Goodness of Fit of
Generalized Linear Models to Sparse Data. Journal of the Royal
Statistical Society. Series B (Methodological), 58(2),
349-360.
Ebrahim, Khaled Ebrahim (2025). Goodness-of-Fits Tests and
Calibration Machine Learning Algorithms for Logistic Regression Model
with Sparse Data. Master’s Thesis, Alexandria University.