A cautionary note on goodness-of-fit statistics for models estimated by pseudo maximum likelihood
Nick Green () and
J. M. C. Santos Silva ()
Additional contact information
Nick Green: University of Surrey
J. M. C. Santos Silva: University of Surrey
Stata Journal, 2025, vol. 25, issue 2, 458-465
Abstract:
We argue that measures of goodness of fit based on the value of the likelihood function should not be used when models are estimated by pseudo maximum likelihood. We illustrate this point by showing that when the dependent variable is not a count, some measures of goodness of fit for Poisson regression routinely reported by Stata commands depend on the scale of the data and are therefore uninformative.
Keywords: glm; poisson; ppml; ppmlhdfe; AIC; BIC; R-squared (search for similar items in EconPapers)
Date: 2025
Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj25-2/st0778/
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.stata-journal.com/article.html?article=st0778 link to article purchase
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:tsj:stataj:v:25:y:2025:i:2:p:458-465
Ordering information: This journal article can be ordered from
http://www.stata-journal.com/subscription.html
Access Statistics for this article
Stata Journal is currently edited by Nicholas J. Cox and Stephen P. Jenkins
More articles in Stata Journal from StataCorp LLC
Bibliographic data for series maintained by Christopher F. Baum () and Lisa Gilmore ().