Correlations and Non-Linear Probability Models

Research output: Contribution to journalJournal articlepeer-review

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Correlations and Non-Linear Probability Models. / Breen, Richard; Holm, Anders; Karlson, Kristian Bernt.

In: Sociological Methods & Research, Vol. 43, No. 4, 11.2014, p. 571-605.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Breen, R, Holm, A & Karlson, KB 2014, 'Correlations and Non-Linear Probability Models', Sociological Methods & Research, vol. 43, no. 4, pp. 571-605. https://doi.org/10.1177/0049124114544224

APA

Breen, R., Holm, A., & Karlson, K. B. (2014). Correlations and Non-Linear Probability Models. Sociological Methods & Research, 43(4), 571-605. https://doi.org/10.1177/0049124114544224

Vancouver

Breen R, Holm A, Karlson KB. Correlations and Non-Linear Probability Models. Sociological Methods & Research. 2014 Nov;43(4):571-605. https://doi.org/10.1177/0049124114544224

Author

Breen, Richard ; Holm, Anders ; Karlson, Kristian Bernt. / Correlations and Non-Linear Probability Models. In: Sociological Methods & Research. 2014 ; Vol. 43, No. 4. pp. 571-605.

Bibtex

@article{f5a378aac90b47caabce0d8938c4185c,
title = "Correlations and Non-Linear Probability Models",
abstract = "Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models.",
keywords = "Faculty of Social Sciences, logit , probit , nonlinear probability models , correlation , group comparisons",
author = "Richard Breen and Anders Holm and Karlson, {Kristian Bernt}",
year = "2014",
month = nov,
doi = "10.1177/0049124114544224",
language = "English",
volume = "43",
pages = "571--605",
journal = "Sociological Methods and Research",
issn = "0049-1241",
publisher = "SAGE Publications",
number = "4",

}

RIS

TY - JOUR

T1 - Correlations and Non-Linear Probability Models

AU - Breen, Richard

AU - Holm, Anders

AU - Karlson, Kristian Bernt

PY - 2014/11

Y1 - 2014/11

N2 - Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models.

AB - Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models.

KW - Faculty of Social Sciences

KW - logit

KW - probit

KW - nonlinear probability models

KW - correlation

KW - group comparisons

U2 - 10.1177/0049124114544224

DO - 10.1177/0049124114544224

M3 - Journal article

VL - 43

SP - 571

EP - 605

JO - Sociological Methods and Research

JF - Sociological Methods and Research

SN - 0049-1241

IS - 4

ER -

ID: 68078602