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Silvia Bacci

Personal Details

First Name:Silvia
Middle Name:
Last Name:Bacci
Suffix:
RePEc Short-ID:pba1040
http://www.ec.unipg.it/DEFS/silvia-bacci.html?lang=it

Affiliation

Dipartimento di Economia
Università degli Studi di Perugia

Perugia, Italy
http://www.econ.unipg.it/

: +39 075 5855200
+39 075 5855299
via Pascoli, 20 - 06123 Perugia
RePEc:edi:deperit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Silvia Bacci & Francesco Bartolucci & Giulia Bettin & Claudia Pigini, 2017. "A mixture growth model for migrants' remittances: An application to the German Socio-Economic Panel," Mo.Fi.R. Working Papers 145, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
  2. Francesco BARTOLUCCI & Silvia BACCI & Claudia PIGINI, 2015. "A Misspecification Test for Finite-Mixture Logistic Models for Clustered Binary and Ordered Responses," Working Papers 410, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  3. Bacci, Silvia & Bartolucci, Francesco & Pigini, Claudia & Signorelli, Marcello, 2014. "A finite mixture latent trajectory model for hirings and separations in the labor market," MPRA Paper 59730, University Library of Munich, Germany.
  4. Bacci, Silvia & Bartolucci, Francesco & Chiavarini, Manuela & Minelli, Liliana & Pieroni, Luca, 2014. "Differences in birth-weight outcomes: A longitudinal study based on siblings," MPRA Paper 55789, University Library of Munich, Germany.
  5. Bacci, Silvia & Bartolucci, Francesco & Pieroni, Luca, 2012. "A causal analysis of mother’s education on birth inequalities," MPRA Paper 38754, University Library of Munich, Germany.

Articles

  1. Silvia Bacci & Michela Gnaldi, 2015. "A classification of university courses based on students’ satisfaction: an application of a two-level mixture item response model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 927-940, May.
  2. Bacci, Silvia & Bartolucci, Francesco, 2014. "Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 262-272.
  3. S. Bacci & S. Pandolfi & F. Pennoni, 2014. "A comparison of some criteria for states selection in the latent Markov model for longitudinal data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(2), pages 125-145, June.
  4. Bartolucci, Francesco & Bacci, Silvia & Gnaldi, Michela, 2014. "MultiLCIRT: An R package for multidimensional latent class item response models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 971-985.
  5. Francesco Bartolucci & Silvia Bacci & Fulvia Pennoni, 2014. "Longitudinal analysis of self-reported health status by mixture latent auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(2), pages 267-288, February.
  6. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
  7. Silvia Bacci & Valeria Caviezel, 2011. "Multilevel IRT models for the university teaching evaluation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2775-2791, February.
  8. Feddag, M.-L. & Bacci, S., 2009. "Pairwise likelihood for the longitudinal mixed Rasch model," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1027-1037, February.
  9. Silvia Bacci & Bruno Chiandotto & Angelo Di Francia & silvia.ghiselli@almalaurea.it, 2008. "Graduates Job Mobility: A Longitudinal Analysis," Statistica, Department of Statistics, University of Bologna, vol. 68(3), pages 255-279.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Francesco BARTOLUCCI & Silvia BACCI & Claudia PIGINI, 2015. "A Misspecification Test for Finite-Mixture Logistic Models for Clustered Binary and Ordered Responses," Working Papers 410, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.

    Cited by:

    1. Shun Yu & Xianzheng Huang, 2017. "Random-intercept misspecification in generalized linear mixed models for binary responses," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 333-359, August.

  2. Bacci, Silvia & Bartolucci, Francesco & Pigini, Claudia & Signorelli, Marcello, 2014. "A finite mixture latent trajectory model for hirings and separations in the labor market," MPRA Paper 59730, University Library of Munich, Germany.

    Cited by:

    1. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.

  3. Bacci, Silvia & Bartolucci, Francesco & Chiavarini, Manuela & Minelli, Liliana & Pieroni, Luca, 2014. "Differences in birth-weight outcomes: A longitudinal study based on siblings," MPRA Paper 55789, University Library of Munich, Germany.

    Cited by:

    1. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.

  4. Bacci, Silvia & Bartolucci, Francesco & Pieroni, Luca, 2012. "A causal analysis of mother’s education on birth inequalities," MPRA Paper 38754, University Library of Munich, Germany.

    Cited by:

    1. Salmasi, Luca & Pieroni, Luca, 2015. "Immigration policy and birth weight: Positive externalities in Italian law," Journal of Health Economics, Elsevier, vol. 43(C), pages 128-139.

Articles

  1. Silvia Bacci & Michela Gnaldi, 2015. "A classification of university courses based on students’ satisfaction: an application of a two-level mixture item response model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 927-940, May.

    Cited by:

    1. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
    2. Marcella Corduas & Alfonso Piscitelli, 2017. "Modeling university student satisfaction: the case of the humanities and social studies degree programs," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 617-628, March.

  2. Bacci, Silvia & Bartolucci, Francesco, 2014. "Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 262-272.

    Cited by:

    1. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
    2. Lyubchich, Vyacheslav & Wang, Xingyu & Heyes, Andrew & Gel, Yulia R., 2016. "A distribution-free m-out-of-n bootstrap approach to testing symmetry about an unknown median," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 1-9.

  3. S. Bacci & S. Pandolfi & F. Pennoni, 2014. "A comparison of some criteria for states selection in the latent Markov model for longitudinal data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(2), pages 125-145, June.

    Cited by:

    1. Morgan, Grant B. & Hodge, Kari J. & Baggett, Aaron R., 2016. "Latent profile analysis with nonnormal mixtures: A Monte Carlo examination of model selection using fit indices," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 146-161.
    2. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
    3. Montanari, Giorgio E. & Doretti, Marco & Bartolucci, Francesco, 2017. "A multilevel latent Markov model for the evaluation of nursing homes' performance," MPRA Paper 80691, University Library of Munich, Germany.
    4. Antonello Maruotti, 2015. "Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 84-109, March.
    5. Bartolucci, Francesco & Farcomeni, Alessio & Pennoni, Fulvia, 2012. "Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," MPRA Paper 39023, University Library of Munich, Germany.
    6. Leonard Paas, 2014. "Comments on: Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 473-477, September.
    7. Bartolucci, Francesco & Pennoni, Fulvia & Vittadini, Giorgio, 2015. "Causal latent Markov model for the comparison of multiple treatments in observational longitudinal studies," MPRA Paper 66492, University Library of Munich, Germany.
    8. Silvia Bacci & Francesco Bartolucci & Giulia Bettin & Claudia Pigini, 2017. "A mixture growth model for migrants' remittances: An application to the German Socio-Economic Panel," Mo.Fi.R. Working Papers 145, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    9. Hans Jørn Juhl & Morten H. J. Fenger & John Thøgersen, 2017. "Will the Consistent Organic Food Consumer Step Forward? An Empirical Analysis," Journal of Consumer Research, Oxford University Press, vol. 44(3), pages 519-535.

  4. Bartolucci, Francesco & Bacci, Silvia & Gnaldi, Michela, 2014. "MultiLCIRT: An R package for multidimensional latent class item response models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 971-985.

    Cited by:

    1. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
    2. Francesco Bartolucci & Valentino Dardanoni & Franco Peracchi, 2013. "Ranking Scientific Journals via Latent Class Models for Polytomous Item Response," EIEF Working Papers Series 1313, Einaudi Institute for Economics and Finance (EIEF), revised May 2013.
    3. Michael Brusco & Hans-Friedrich Köhn & Douglas Steinley, 2015. "An Exact Method for Partitioning Dichotomous Items Within the Framework of the Monotone Homogeneity Model," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 949-967, December.
    4. Silvia Bacci & Michela Gnaldi, 2015. "A classification of university courses based on students’ satisfaction: an application of a two-level mixture item response model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 927-940, May.
    5. Michela Gnaldi & Silvia Bacci, 2016. "Joint assessment of the latent trait dimensionality and observed differential item functioning of students’ national tests," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(4), pages 1429-1447, July.
    6. Leonard Paas & Tammo Bijmolt & Jeroen Vermunt, 2015. "Long-term developments of respondent financial product portfolios in the EU: a multilevel latent class analysis," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 249-262, August.
    7. Michela Gnaldi & Silvia Bacci & Francesco Bartolucci, 2016. "A multilevel finite mixture item response model to cluster examinees and schools," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(1), pages 53-70, March.
    8. Chiara Dal Bianco & Omar Paccagnella & Roberta Varriale, 2016. "A multilevel latent class analysis of the purchasing channels among European consumers," METRON, Springer;Sapienza Università di Roma, vol. 74(3), pages 293-309, December.
    9. Michela Gnaldi, 2017. "A multidimensional IRT approach for dimensionality assessment of standardised students’ tests in mathematics," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1167-1182, May.

  5. Francesco Bartolucci & Silvia Bacci & Fulvia Pennoni, 2014. "Longitudinal analysis of self-reported health status by mixture latent auto-regressive models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(2), pages 267-288, February.

    Cited by:

    1. Bartolucci, Francesco & Bacci, Silvia & Pigini, Claudia, 2017. "Misspecification test for random effects in generalized linear finite-mixture models for clustered binary and ordered data," Econometrics and Statistics, Elsevier, vol. 3(C), pages 112-131.
    2. Francesco BARTOLUCCI & Silvia BACCI & Claudia PIGINI, 2015. "A Misspecification Test for Finite-Mixture Logistic Models for Clustered Binary and Ordered Responses," Working Papers 410, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    3. Cagnone, Silvia & Bartolucci, Francesco, 2013. "Adaptive quadrature for likelihood inference on dynamic latent variable models for time-series and panel data," MPRA Paper 51037, University Library of Munich, Germany.
    4. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
    5. Xia, Ye-Mao & Tang, Nian-Sheng & Gou, Jian-Wei, 2016. "Generalized linear latent models for multivariate longitudinal measurements mixed with hidden Markov models," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 259-275.
    6. Silvia Cagnone & Francesco Bartolucci, 2017. "Adaptive Quadrature for Maximum Likelihood Estimation of a Class of Dynamic Latent Variable Models," Computational Economics, Springer;Society for Computational Economics, vol. 49(4), pages 599-622, April.
    7. Francesca Bassi, 2016. "Dynamic segmentation with growth mixture models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(2), pages 263-279, June.
    8. Silvia Bianconcini, 2014. "Comments on: Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 466-468, September.
    9. Pennoni, Fulvia & Romeo, Isabella, 2016. "Latent Markov and growth mixture models for ordinal individual responses with covariates: a comparison," MPRA Paper 72939, University Library of Munich, Germany.

  6. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.

    Cited by:

    1. Marzio Galeotti & Yana Rubashkina & Silvia Salini & Elena Verdolini, 2014. "Environmental Policy Performance and its Determinants: Application of a Three-level Random Intercept Model," Working Papers 2014.90, Fondazione Eni Enrico Mattei.

  7. Silvia Bacci & Valeria Caviezel, 2011. "Multilevel IRT models for the university teaching evaluation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2775-2791, February.

    Cited by:

    1. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
    2. Marzio Galeotti & Yana Rubashkina & Silvia Salini & Elena Verdolini, 2014. "Environmental Policy Performance and its Determinants: Application of a Three-level Random Intercept Model," Working Papers 2014.90, Fondazione Eni Enrico Mattei.
    3. Silvia Bacci & Michela Gnaldi, 2015. "A classification of university courses based on students’ satisfaction: an application of a two-level mixture item response model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 927-940, May.
    4. Michele La Rocca & Maria Lucia Parrella & Ilaria Primerano & Isabella Sulis & Maria Prosperina Vitale, 2017. "An integrated strategy for the analysis of student evaluation of teaching: from descriptive measures to explanatory models," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 675-691, March.

  8. Feddag, M.-L. & Bacci, S., 2009. "Pairwise likelihood for the longitudinal mixed Rasch model," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1027-1037, February.

    Cited by:

    1. Silvia Bacci, 2012. "Longitudinal data: different approaches in the context of item-response theory models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(9), pages 2047-2065, June.
    2. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
    3. Vassilis Vasdekis & Silvia Cagnone & Irini Moustaki, 2012. "A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 425-441, July.
    4. Silvia Cagnone & Paola Monari, 2013. "Latent variable models for ordinal data by using the adaptive quadrature approximation," Computational Statistics, Springer, vol. 28(2), pages 597-619, April.
    5. M.-L. Feddag, 2016. "Pairwise likelihood estimation for the normal ogive model with binary data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(2), pages 223-237, April.
    6. Myrsini Katsikatsou & Irini Moustaki, 2016. "Pairwise Likelihood Ratio Tests and Model Selection Criteria for Structural Equation Models with Ordinal Variables," Psychometrika, Springer;The Psychometric Society, vol. 81(4), pages 1046-1068, December.

  9. Silvia Bacci & Bruno Chiandotto & Angelo Di Francia & silvia.ghiselli@almalaurea.it, 2008. "Graduates Job Mobility: A Longitudinal Analysis," Statistica, Department of Statistics, University of Bologna, vol. 68(3), pages 255-279.

    Cited by:

    1. Cattaneo, Mattia & Malighetti, Paolo & Paleari, Stefano & Redondi, Renato, 2016. "The role of the air transport service in interregional long-distance students’ mobility in Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 66-82.
    2. Zotti, Roberto & Barra, Cristian, 2014. "Human capital development, knowledge spillovers and local growth: Is there a quality effect of university efficiency?," MPRA Paper 60065, University Library of Munich, Germany.
    3. Ciriaci, Daria, 2009. "University quality, interregional brain drain and spatial inequality. The case of Italy," MPRA Paper 30015, University Library of Munich, Germany, revised 31 Mar 2011.
    4. Mattia Cattaneo & Paolo Malighetti & Stefano Paleari & Renato Redondi, 2015. "Evolution of long distance students? mobility: the role of transport infrastructures in Italy," ERSA conference papers ersa15p1231, European Regional Science Association.
    5. Pietro Giorgio Lovaglio & Gianmarco Vacca & Stefano Verzillo, 2016. "Human capital estimation in higher education," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 465-489, December.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 6 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-DEM: Demographic Economics (2) 2012-05-22 2014-05-17
  2. NEP-ECM: Econometrics (2) 2014-12-03 2015-05-16
  3. NEP-HEA: Health Economics (2) 2012-05-22 2014-05-17
  4. NEP-DCM: Discrete Choice Models (1) 2015-07-25
  5. NEP-EDU: Education (1) 2014-05-17
  6. NEP-EUR: Microeconomic European Issues (1) 2018-01-01

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