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ERIC Number: EJ973383
Record Type: Journal
Publication Date: 2012
Pages: 17
Abstractor: As Provided
Reference Count: 34
ISBN: N/A
ISSN: ISSN-0211-2159
Estimation of Logistic Regression Models in Small Samples. A Simulation Study Using a Weakly Informative Default Prior Distribution
Gordovil-Merino, Amalia; Guardia-Olmos, Joan; Pero-Cebollero, Maribel
Psicologica: International Journal of Methodology and Experimental Psychology, v33 n2 p345-361 2012
In this paper, we used simulations to compare the performance of classical and Bayesian estimations in logistic regression models using small samples. In the performed simulations, conditions were varied, including the type of relationship between independent and dependent variable values (i.e., unrelated and related values), the type of variable (i.e., binary and continuous), and different Binomial distribution values and symmetry (i.e., symmetry and positive asymmetry). Iteratively re-weighted least squares was used as the estimate method to fit the models in both the classical and Bayesian estimations. A weakly informative default distribution was chosen as the prior distribution for Bayesian estimation. The simulation results demonstrate that Bayesian estimations provide more stable distributions but are not able to solve problems generated by asymmetric distributions based on small samples. Additional research using different kinds of priors that is addressed at solving problems caused by asymmetry is needed. (Contains 2 tables, 2 figures and 1 footnote.)
University of Valencia. Dept. Metodologia, Facultad de Psicologia, Avda. Blasco Ibanez 21, 46010 Valencia, Spain. Tel: +34-96-386-4100; Web site: http://www.uv.es/revispsi/
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A