Download e-book for iPad: Advances in Latent Variables: Methods, Models and by Maurizio Carpita, Eugenio Brentari, El Mostafa Qannari

By Maurizio Carpita, Eugenio Brentari, El Mostafa Qannari

ISBN-10: 3319029665

ISBN-13: 9783319029665

ISBN-10: 3319029673

ISBN-13: 9783319029672

The ebook, belonging to the sequence “Studies in Theoretical and utilized facts– chosen Papers from the Statistical Societies”, provides a peer-reviewed collection of contributions on appropriate themes prepared via the editors at the social gathering of the SIS 2013 Statistical convention "Advances in Latent Variables. tools, types 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 ebook is on advances in statistical tools for analyses with latent variables. in truth, in recent times, there was expanding curiosity during this large learn sector from either a theoretical and an utilized viewpoint, because the statistical latent variable technique permits the potent modeling of advanced real-life phenomena in quite a lot of examine fields.

A significant aim of the amount is to assemble articles written by means of statisticians from various learn fields, which current various techniques and stories regarding the research of unobservable variables and the learn of the relationships among them.

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References 1. : Categorical Data Analysis, 3rd edn. Wiley, New York (2013) 2. it (2011) 3. : Well-being over time in Britain and the USA. J. Public Econ. 88, 1359–1386 (2004) 4. : Models for categorical data: A comparison between the Rasch model and nonlinear principal component analysis. 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.

O x ; ıO y / ; (5) i D1 is maximised to get ÁO and then O by means of the previous mentioned relationship. This two step procedure can be associated to the use of the jackknife method for estimation of the standard errors of the parameters and functions of the parameters. In such a way, the analytic derivatives to obtain the asymptotic covariance matrix of the vector of parameter estimates are not needed. Furthermore, since each inference function derives from some log-likelihood of a marginal distribution, the inference can be obtained by the existing EM algorithm implemented for the CUB models.

In addition, since all covariates have the same range, the estimated j parameters express the importance of a single component to contribute to the global job satisfaction. 004) Asymptotic standard errors in parentheses are significant to explain the global job satisfaction. 060). The facets are ordered according to their contribution to improve the log-likelihood function. Thus, “Acquisition of professionalism”, “Prestige”, “Independence or autonomy in the job”, “Connection with cultural interests”, “Involvement in the decisional processes”, “Relationships with co-workers” are the most relevant features whereas “Coherence with studies”, “Security of the job”, “Availability of free time” exert a minor (although significant) impact.

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

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