Comparing Coefficients of Nested Nonlinear Probability Models
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In a series of recent articles, Karlson, Holm, and Breen (Breen, Karlson, and Holm, 2011, http://papers.ssrn.com/sol3/papers.cfm?abstractid=1730065 ; Karlson and Holm, 2011, Research in Stratification and Social Mobility 29: 221– 237; Karlson, Holm, and Breen, 2010, http://www.yale.edu/ciqle/Breen Scaling %20effects.pdf) have developed a method for comparing the estimated coefficients of two nested nonlinear probability models. In this article, we describe this method and the user-written program khb, which implements the method. The KHB method is a general decomposition method that is unaffected by the rescaling or attenuation bias that arises 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 generalized linear model family.
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The KHB method always performs as well or better than other methods for recovering the degree of mediation net of the impact of rescaling.
“Monte Carlo studies have shown that the KHB method always performs as well or better than other methods that have been developed to address the problems of rescaling in terms of recovering the degree of mediation net of the impact of rescaling (Kohler et al., 2011).”
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- Authors
- Kohler, U., Karlson, K. B., & Holm, A.
- Affiliations
- Wissenschaftszentrum Berlin
- Aarhus University (DK)
- Corresponding author
- Karlson, Kristian Bernt
- Holm, Anders
- Venue
- The Stata Journal: Promoting communications on statistics and Stata
- Publisher
- SAGE Publications
- Published
- 2011-10
- Volume
- 11
- Issue
- 3
- Pages
- 420-438
- ISSN
- 1536-867X (ISSN-L)
- 1536-8734
- OpenAlex
- W2147660973
- Cited by
- 1,041
- References
- 1
- Citations by year
- 2026: 90 · 2025: 110 · 2024: 113 · 2023: 105 · 2022: 109 · 2021: 106 · 2020: 99 · 2019: 65 · 2018: 68 · 2017: 58 · 2016: 45 · 2015: 25 · 2014: 17 · 2013: 23 · 2012: 4
- FWCI
- 13.47
- Type
- journal article
- Language
- en
- Open access
- green
- ageconsearch.umn.edu
- Licence
- Locations
- The Stata Journal Promoting communications on statistics and Stata (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- AgEcon Search (University of Minnesota, USA) (submittedVersion, cc-by-nc-nd)
- AgEcon Search (University of Minnesota, USA)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Keywords
- mediation, attenuation bias, effect decomposition, average partial effects, generalized linear models
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