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Log-likelihood-based pseudo-R2 in logistic regression : deriving sample-sensitive benchmarks
Hemmert, Giselmar A. J.
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Edinger-Schons, Laura Marie
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Wieseke, Jan
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Schimmelpfennig, Heiko
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DOI:
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https://doi.org/10.1177/0049124116638107
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URL:
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http://journals.sagepub.com/doi/10.1177/0049124116...
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Weitere URL:
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https://www.researchgate.net/publication/298899419...
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Dokumenttyp:
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Zeitschriftenartikel
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Erscheinungsjahr:
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2018
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Titel einer Zeitschrift oder einer Reihe:
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Sociological Methods & Research : SMR
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Band/Volume:
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47
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Heft/Issue:
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3
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Seitenbereich:
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507-531
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Ort der Veröffentlichung:
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Thousand Oaks [u.a.]
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Verlag:
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Sage Publ.
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ISSN:
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0049-1241 , 1552-8294
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Sprache der Veröffentlichung:
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Englisch
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Einrichtung:
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Fakultät für Betriebswirtschaftslehre > Sustainable Business (Edinger-Schons 2015-2022)
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Fachgebiet:
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330 Wirtschaft
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Freie Schlagwörter (Englisch):
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pseudo-R2 , logistic regression , goodness-of-fit , benchmarks , reporting
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Abstract:
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The literature proposes numerous so-called pseudo-R2 measures for evaluating “goodness of fit” in regression models with categorical dependent variables. Unlike ordinary least square-R2, log-likelihood-based pseudo-R2s do not represent the proportion of explained variance but rather the improvement in model likelihood over a null model. The multitude of available pseudo-R2 measures and the absence of benchmarks often lead to confusing interpretations and unclear reporting. Drawing on a meta-analysis of 274 published logistic regression models as well as simulated data, this study investigates fundamental differences of distinct pseudo-R2 measures, focusing on their dependence on basic study design characteristics. Results indicate that almost all pseudo-R2s are influenced to some extent by sample size, number of predictor variables, and number of categories of the dependent variable and its distribution asymmetry. Hence, an interpretation by goodness-of-fit benchmark values must explicitly consider these characteristics. The authors derive a set of goodness-of-fit benchmark values with respect to ranges of sample size and distribution of observations for this measure. This study raises awareness of fundamental differences in characteristics of pseudo-R2s and the need for greater precision in reporting these measures.
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Suche Autoren in
BASE:
Hemmert, Giselmar A. J.
;
Edinger-Schons, Laura Marie
;
Wieseke, Jan
;
Schimmelpfennig, Heiko
Google Scholar:
Hemmert, Giselmar A. J.
;
Edinger-Schons, Laura Marie
;
Wieseke, Jan
;
Schimmelpfennig, Heiko
ORCID:
Hemmert, Giselmar A. J., Edinger-Schons, Laura Marie  ORCID: https://orcid.org/0000-0002-8981-3379, Wieseke, Jan and Schimmelpfennig, Heiko
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