Arbeitspapier

Bias of maximum-likelihood estimates in logistic and Cox regression models: a comparative simulation study

to related objects

Parameter estimates of logistic and Cox regression models are biased for finite samples. In a simulation study we investigated for both models the behaviour of the bias in relation to sample size and further parameters. In the case of a dichotomous explanatory variable x the magnitude of the bias is strongly influenced by the baseline risk defined by the constants of the models and the risk resulting for the high risk group. To conduct a direct comparison of the bias of the two models analyses were based on the same simulated data. Overall, the bias of the two models appear to be similar, however, the Cox model has less bias in situations where the baseline risk is high.

Language
Englisch

Bibliographic citation
Series: Discussion Paper ; No. 362

Event
Geistige Schöpfung
(who)
Langner, Ingo
Bender, Ralf
Lenz-Tönjes, Rebecca
Küchenhoff, Helmut
Blettner, Maria
Event
Veröffentlichung
(who)
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
(where)
München
(when)
2003

DOI
doi:10.5282/ubm/epub.1737
Handle
URN
urn:nbn:de:bvb:19-epub-1737-8
Last update
10.03.2025, 11:43 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Show original at data provider

Object type

  • Arbeitspapier

Associated

  • Langner, Ingo
  • Bender, Ralf
  • Lenz-Tönjes, Rebecca
  • Küchenhoff, Helmut
  • Blettner, Maria
  • Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen

Time of origin

  • 2003

Other Objects (12)

Maximum softly-penalized likelihood for mixed effects logistic regression

Maximum softly-penalized likelihood for mixed effects logistic regression

Modifications and extensions of the logistic regression and Cox model

Modifications and extensions of the logistic regression and Cox model

Bias in Tax Progressivity Estimates

Bias in Tax Progressivity Estimates

Starless bias and parameter-estimation bias in the likelihood-based phylogenetic method

Starless bias and parameter-estimation bias in the likelihood-based phylogenetic method

Selfinformative Limits of Bayes Estimates and Generalized Maximum Likelihood

Arbeitspapier

Selfinformative Limits of Bayes Estimates and Generalized Maximum Likelihood

Selfinformative Limits of Bayes Estimates andGeneralized Maximum Likelihood

Selfinformative Limits of Bayes Estimates andGeneralized Maximum Likelihood

A Flexible Adaptive Lasso Cox Frailty Model Based on the Full Likelihood

A Flexible Adaptive Lasso Cox Frailty Model Based on the Full Likelihood

Spatial aggregation of local likelihood estimates with applications to classification

Arbeitspapier

Spatial aggregation of local likelihood estimates with applications to classification

Spatial aggregation of local likelihood estimates with applications to classification

Spatial aggregation of local likelihood estimates with applications to classification

Maximum likelihood estimation of the Weibull distribution with reduced bias

Maximum likelihood estimation of the Weibull distribution with reduced bias

A likelihood ratio test for changes in homeolog expression bias

A likelihood ratio test for changes in homeolog expression bias

Maximum likelihood estimation for left-truncated log-logistic distributions with a given truncation point

Maximum likelihood estimation for left-truncated log-logistic distributions with a given truncation point

Related objects