A Note on a Reformulation of the KHB Method

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A Note on a Reformulation of the KHB Method. / Breen, Richard; Karlson, Kristian Bernt; Holm, Anders.

In: Sociological Methods & Research, Vol. 50, No. 2, 05.2021, p. 901-912.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Breen, R, Karlson, KB & Holm, A 2021, 'A Note on a Reformulation of the KHB Method', Sociological Methods & Research, vol. 50, no. 2, pp. 901-912. https://doi.org/10.1177/0049124118789717

APA

Breen, R., Karlson, K. B., & Holm, A. (2021). A Note on a Reformulation of the KHB Method. Sociological Methods & Research, 50(2), 901-912. https://doi.org/10.1177/0049124118789717

Vancouver

Breen R, Karlson KB, Holm A. A Note on a Reformulation of the KHB Method. Sociological Methods & Research. 2021 May;50(2):901-912. https://doi.org/10.1177/0049124118789717

Author

Breen, Richard ; Karlson, Kristian Bernt ; Holm, Anders. / A Note on a Reformulation of the KHB Method. In: Sociological Methods & Research. 2021 ; Vol. 50, No. 2. pp. 901-912.

Bibtex

@article{43a814915f864ba990e7527f266696a0,
title = "A Note on a Reformulation of the KHB Method",
abstract = "The Karlson–Holm–Breen (KHB) method has rapidly become popular as a way of separating the impact of confounding from rescaling when comparing conditional and unconditional parameter estimates in nonlinear probability models such as the logit and probit. In this note, we show that the same estimates can be obtained in a somewhat different way to that advanced by Karlson, Holm, and Breen in their original article and implemented in the user-written Stata command khb. While the KHB method and this revised KHB method both work by holding constant the residual variance of the model, the revised method makes comparisons across multiple nested models easier than the original method.",
keywords = "Faculty of Social Sciences, nonlinear probability models, logit model, probit model, nested model comparisons, KHB method",
author = "Richard Breen and Karlson, {Kristian Bernt} and Anders Holm",
year = "2021",
month = "5",
doi = "10.1177/0049124118789717",
language = "English",
volume = "50",
pages = "901--912",
journal = "Sociological Methods & Research",
issn = "0049-1241",
publisher = "SAGE Publications",
number = "2",

}

RIS

TY - JOUR

T1 - A Note on a Reformulation of the KHB Method

AU - Breen, Richard

AU - Karlson, Kristian Bernt

AU - Holm, Anders

PY - 2021/5

Y1 - 2021/5

N2 - The Karlson–Holm–Breen (KHB) method has rapidly become popular as a way of separating the impact of confounding from rescaling when comparing conditional and unconditional parameter estimates in nonlinear probability models such as the logit and probit. In this note, we show that the same estimates can be obtained in a somewhat different way to that advanced by Karlson, Holm, and Breen in their original article and implemented in the user-written Stata command khb. While the KHB method and this revised KHB method both work by holding constant the residual variance of the model, the revised method makes comparisons across multiple nested models easier than the original method.

AB - The Karlson–Holm–Breen (KHB) method has rapidly become popular as a way of separating the impact of confounding from rescaling when comparing conditional and unconditional parameter estimates in nonlinear probability models such as the logit and probit. In this note, we show that the same estimates can be obtained in a somewhat different way to that advanced by Karlson, Holm, and Breen in their original article and implemented in the user-written Stata command khb. While the KHB method and this revised KHB method both work by holding constant the residual variance of the model, the revised method makes comparisons across multiple nested models easier than the original method.

KW - Faculty of Social Sciences

KW - nonlinear probability models

KW - logit model

KW - probit model

KW - nested model comparisons

KW - KHB method

U2 - 10.1177/0049124118789717

DO - 10.1177/0049124118789717

M3 - Journal article

VL - 50

SP - 901

EP - 912

JO - Sociological Methods & Research

JF - Sociological Methods & Research

SN - 0049-1241

IS - 2

ER -

ID: 197766713