A common problem in economics is to evaluate the effect of a treatment when individuals self-select whether to receive the treatment. This problem arises when trying to evaluate the union/nonunion wage differential, the effect of job training on earnings, and the returns to schooling, where being unionized or making a human capital investment is the treatment. One standard approach to this prob...

Department of Biostatistics, School of Medical Sciences, Tarbiat Modares University, P.O. Box: 14115-111, Tehran, Iran. Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Institute of Mathematical Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia. Department of Biostatistics and Epidemiology, Facul...

This paper reports the effect of functional roles on computer-supported collaborative learning. Thirtythree students in ten groups, equally distributed over two research conditions (role versus nonrole), returned an evaluation questionnaire assessing their computer-supported collaborative learning experience. Principal axis factoring revealed a latent variable interpreted as: perceived group ef...

In this paper we present a model that is capable of learning alignments between high-dimensional data by exploiting low-dimensional structures. Specifically, our method uses a Gaussian process latent variable model (GP-LVM) to learn alignments and latent representations simultaneously. The results show that our model performs alignment implicitly and improves the smoothness of the low dimension...

In this paper, we discuss the properties of a class of latent variable models that assumes each labeled sample is associated with set of different features, with no prior knowledge of which feature is the most relevant feature to be used. Deformable-Part Models (DPM) can be seen as good example of such models. While Latent SVM framework (LSVM) has proven to be an efficient tool for solving thes...

In this work, synthesis of facial animation is done by modelling the mapping between facial motion and speech using the shared Gaussian process latent variable model. Both data are processed separately and subsequently coupled together to yield a shared latent space. This method allows coarticulation to be modelled by having a dynamical model on the latent space. Synthesis of novel animation is...

Cognitive Diagnosis Models (CDMs) are useful statistical tools in cognitive diagnosis assessment. However, as many other latent variable models, the CDMs often suffer from the non-identifiability issue. This work gives the sufficient and necessary condition for the identifiability of the basic DINA model, which not only addresses the open problem in Xu and Zhang (2016, Psychomatrika, 81:625-649...

There haven’t been enough empirical evidences of orders’ impact on structural equation model and satisfaction index results. This study is conducted to figure out the problem by making a comparison between the first-order and high-order structural equation models building with the same sample from healthcare. As expected, results showed that the path coefficients and goodness-of-fit indices of ...

Distributions over matrices with exchangeable rows and infinitely many columns are useful in constructing nonparametric latent variable models. However, the distribution implied by such models over the number of features exhibited by each data point may be poorly-suited for many modeling tasks. In this paper, we propose a class of exchangeable nonparametric priors obtained by restricting the do...

1 In the credit risk analysis, the dependence of default times is one of most important issues, for the portfolio credit derivatives as basket default swaps and CDOs, and also for the contagious credit risks. In the literature, the modelling of multi credit names is diversified in various directions such as Markov models ([3, 4]), contagion models ([10]), latent variable models ([8]) and loss p...