Small-sample techniques for comparing several logistic regression slopes to a standard

DOI10.1080/00949650108812139zbMath1003.62061OpenAlexW2024393767MaRDI QIDQ4534196

John D. Spurrier, Nairanjana Dasgupta, Francis Pascual

Publication date: 2 February 2003

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650108812139

zbMATH Keywords

sufficient statisticspivotingmarginal powerlate blightminimum logit chi-square estimatorsnon-existence of maximum likelihood estimators

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Point estimation (62F10) Generalized linear models (logistic models) (62J12) Sufficient statistics and fields (62B05)

Related Items (3)

Many to one comparisons in a longitudinal binary data setup ⋮ Simultaneous confidence bands for restricted logistic regression models ⋮ Design considerations for small experiments and simple logistic regression

Cites Work

• Exact unconditional distributions for dichotomous data in many-to-one comparisons.
• A Multiple Comparison Procedure for Comparing Several Treatments with a Control
• On the existence of maximum likelihood estimates in logistic regression models
• Multiple Comparisons of Polynomial Distributions
• Computing Distributions for Exact Logistic Regression
• Prepivoting Test Statistics: A Bootstrap View of Asymptotic Refinements
• Optimal Designs for Comparing the Variances of Several Treatments with That of a Standard Treatment
• Multiple Comparisons with Dichotomous Data
• Comparison to control in logistic regression
• Linear and non-linear multiple comparisons in logit analysis
• Maximum Likelihood and Minimum | chi 2 Estimates of the Logistic Function

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