Alternative estimating procedures for multiple membership logit models with mixed effects: indirect inference and data cloning
Anna Gottard () and
Additional contact information
Anna Gottard: Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", Università di Firenze, http://www.disia.unifi.it
No 2014_07, Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti"
Multiple-membership logit models with random effects are logit models for clustered binary data, where each statistical unit can belong to more than one group. For these models, the likelihood function is analytically intractable. We propose two different approaches for parameter estimation: data cloning and indirect inference. Data cloning computes maximum likelihood estimates, through the posterior distribution of an adequate Bayesian model fitted on cloned data. We implement a data cloning algorithm specific for the case of multiple-membership models. Indirect inference is a non-likelihood based method which uses an auxiliary model to select sensible estimates. We propose an auxiliary model having the same dimension of parameter space as the target model, which is particularly convenient to reach good estimates very fast. A Monte Carlo experiment compares the two approaches on a set of simulated data. We report also Bayesian posterior mean and INLA hybrid data cloning estimates for comparison. Simulations show a negligible loss of efficiency for the indirect inference estimator, compensated by a relevant computational gain. The approaches are then illustrated with a real example on matched paired data.
Keywords: Binary data; Bradley Terry models; intractable likelihood; integrated nested Laplace approximation; non-hierarchical random effects models (search for similar items in EconPapers)
JEL-codes: C51 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://local.disia.unifi.it/wp_disia/2014/wp_disia_2014_07.pdf First version, 2014-07 (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:fir:econom:wp2014_07
Access Statistics for this paper
More papers in Econometrics Working Papers Archive from Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti" Viale G.B. Morgagni, 59 - I-50134 Firenze - Italy. Contact information at EDIRC.
Bibliographic data for series maintained by Francesco Calvori (). This e-mail address is bad, please contact .