Comparing coefficients of nested nonlinear probability models

Research output: Contribution to journalJournal articleResearchpeer-review


In a series of recent articles, Karlson, Holm and Breen have developed a
method for comparing the estimated coeffcients of two nested nonlinear probability models. This article describes this method and the user-written program khb that implements the method. The KHB-method is a general decomposition method that is unaffected by the rescaling or attenuation bias that arise in cross-model comparisons in nonlinear models. It recovers the degree to which a control variable, Z, mediates or explains the relationship between X and a latent outcome variable, Y*, underlying the nonlinear probability model. It also decomposes effects of both discrete and continuous variables, applies to average partial effects, and provides analytically derived statistical tests. The method can be extended to other models in the GLM-family.
Original languageEnglish
JournalStata Journal
Issue number3
Pages (from-to)420-438
Number of pages19
Publication statusPublished - 2011
Externally publishedYes

Number of downloads are based on statistics from Google Scholar and

No data available

ID: 44258801