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Reliable generalized linear latent variable models estimation via simulated maximum likelihood.
No full textLA VALUTAZIONE DEI CORSI DI FORMAZIONE PROFESSIONALE MEDIANTE MODELLI MULTILIVELLO IN PRESENZA DI POSSIBILE SELEZIONE NON CASUALE
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Efficient estimation of true fixed-effects stochastic frontier models
Full text linkFixed-effects modeling has become the method of choice in several panel data settings, including models for stochastic frontier analysis. A notable instance of stochastic frontier panel data models is the true fixed-effects model, which allows disentangling unit heterogeneity from efficiency evaluations. While such a model is theoretically appealing, its estimation is hampered by incidental parameters. This note proposes a simple and rather general estimation approach where the unit-specific intercepts are integrated out of the likelihood function. We apply the theory of composite group families to the model of interest and demonstrate that the resulting integrated likelihood is a marginal likelihood with desirable inferential properties. The derivation of the result is provided in full, along with some connections with the existing literature and computational details. The method is illustrated for three notable models, given by the normal-half normal model, the heteroscedastic exponential model, and the normal-gamma model. The results of simulation experiments highlight the properties of the methodology
Structural characteristics of young plantations with pedunculate oak and hornbeam in the Veneto region
Full text linkThe Asparago tenuifolii-Quercetum roboris Marincek 1994 is the forest climax association of Po Valley. Nowadays these forests, located on a few patches in Veneto, that totally cover about 60 hectares, show serious problems in stands structure and functions. They are very important for the nature conservation even if they are fragmented in small stands. Foresters manage them as an open museum, adopting particular forestry technique to preserve and maintain the overstorey vegetation, even through new plantations near the ancient woods. Since 1988, thanks to the CAP's strategy of set-aside, hundreds hectares of agricultural land were converted to forest in order to restore the ancient plain forest. These new forests have a lot of problems caused by errors in the projecting phase and by cultural lacks so they need a model for the management of the stands. The relationships between age and the most important tree variables, natural regeneration and herbs vegetation, were studied by a chronosequence approach over 10 forest sites. This article presents the results of the study about the diameter at breast height (henceforth: dbh) and the other tree variables relationships analyzed both at species and social class level. The authors suggested a new planting scheme aimed at promoting the natural restoration
Adjusted quasi-profile likelihoods from estimating functions
No full textWe discuss higher-order adjustments for a quasi-profile likelihood for a scalar parameter of interest, in order to alleviate some of
the problems inherent to the presence of nuisance parameters, such as bias and inconsistency. Indeed, quasi-profile score functions for the parameter of interest have bias of order O(1), and such bias can lead to poor inference on the parameter of interest. The higher-order adjustments are obtained so that the adjusted quasi-profile score estimating function is unbiased and its variance is the negative expected derivative matrix of the adjusted profile estimating equation. The modified quasi-profile likelihood is then obtained as the integral of the adjusted profile estimating function. We discuss two methods for the computation of the modified quasi-profile likelihoods: a bootstrap simulation method and a first-order asymptotic expression, which can be simplified under an orthogonality assumption. Examples in the context of generalized linear models and of robust inference are provided, showing that the use of a modified quasi-profile likelihood ratio statistic may lead to coverage probabilities more accurate than those pertaining to first-order Wald-type confidence intervals
Shrinkage estimation of the three-parameter logistic model
No full textThe three-parameter logistic model is widely used to model the responses to a proficiency test when the examinees can guess the correct response, as is the case for multiple-choice items. However, the weak identifiability of the parameters of the model results in large variability of the estimates and in convergence difficulties in the numerical maximization of the likelihood function. To overcome these issues, in this paper we explore various shrinkage estimation methods, following two main approaches. First, a ridge-type penalty on the guessing parameters is introduced in the likelihood function. The tuning parameter is then selected through various approaches: cross-validation, information criteria or using an empirical Bayes method. The second approach explored is based on the methodology developed to reduce the bias of the maximum likelihood estimator through an adjusted score equation. The performance of the methods is investigated through simulation studies and a real data example
Integrated Likelihood Inference in Small Sample Meta-analysis for Continuous Outcomes
Full text linkThis paper proposes the use of the integrated likelihood for inference on the mean effect in small-sample meta-analysis for continuous outcomes. The method eliminates the nuisance parameters given by variance components through integration with respect to a suitable weight function, with no need to estimate them. The integrated likelihood approach takes into proper account the estimation uncertainty of within-study variances, thus providing confidence intervals with empirical coverage closer to nominal levels than standard likelihood methods. The improve- ment is remarkable when either (i) the number of studies is small to moderate or (ii) the small sample size of the studies does not allow to consider the within-study variances as known, as common in applications. Moreover, the use of the integrated likelihood avoids numerical pitfalls related to the estimation of variance components which can affect alternative likelihood approaches. The proposed methodology is illustrated via simulation and applied to a meta-analysis study in nutritional science
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