Read e-book online Advances in Latent Variables: Methods, Models and PDF

By Maurizio Carpita, Eugenio Brentari, El Mostafa Qannari

ISBN-10: 3319029665

ISBN-13: 9783319029665

ISBN-10: 3319029673

ISBN-13: 9783319029672

The e-book, belonging to the sequence “Studies in Theoretical and utilized records– chosen Papers from the Statistical Societies”, offers a peer-reviewed choice of contributions on proper subject matters prepared through the editors at the get together of the SIS 2013 Statistical convention "Advances in Latent Variables. equipment, versions and Applications", held on the division of Economics and administration of the collage of Brescia from June 19 to 21, 2013.

The concentration of the publication is on advances in statistical equipment for analyses with latent variables. in truth, lately, there was expanding curiosity during this extensive learn zone from either a theoretical and an utilized perspective, because the statistical latent variable process permits the powerful modeling of complicated real-life phenomena in quite a lot of learn fields.

A significant target of the quantity is to assemble articles written via statisticians from varied study fields, which current assorted ways and reviews regarding the research of unobservable variables and the research of the relationships among them.

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Extra resources for Advances in Latent Variables: Methods, Models and Applications

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Soc. 75, 579–642 (1912) Modelling Job Satisfaction of Italian Graduates Stefania Capecchi and Silvia Ghiselli Abstract Different models have been implemented to observe worker conditions, abilities, leadership, decision-making attitudes and other related concerns. This paper aims to investigate the job satisfaction of a large sample of Italian graduates with a model-based approach derived by a mixture distribution. Sample data have been collected in the 2010 AlmaLaurea survey on graduates employment conditions, 5 years after their degree.

Grade/ be a score variable for the final grade; for convenience, we denote summa cum laude as 112. Then, the best estimated CUB model with score as a covariate implies the following relationship for the level of satisfaction: 1 i D logit 1 95:547 C 40:996 SCi 4:472 SC2i ; i D 1; 2; : : : ; n: 44 S. Capecchi and S. 87 negative effect, C positive effect, ı non statistically significant 80 90 100 110 Grades Fig. 2 Global satisfaction as a function of grades, estimated by a CUB model Gender is also a significant covariate for determining a shift in the uncertainty of the responses (women are more uncertain); however, the shape of the relationships between satisfaction and final grade is the same for both genders.

Statistica Applicazioni 5, 53–77 (2007) 5. : Modelling approaches for ordinal data: the case of orientation service evaluation. Quaderni di Statistica 12, 99–124 (2010) 6. : Modelling Job Satisfaction in AlmaLaurea Surveys, AlmaLaurea Working Papers n. 56 (2012) 7. : Modelling correlated bivariate ordinal data with CUB marginals. Quaderni di Statistica 13, 109–119 (2011) 8. : Job satisfaction as an economic variable. Am. Econ. Rev. 68, 135–141 (1978) 9. : Measuring job satisfaction with CUB models.

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Advances in Latent Variables: Methods, Models and Applications by Maurizio Carpita, Eugenio Brentari, El Mostafa Qannari


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