Abstract
In the evaluation of university quality, questionnaires with multi-item scales (Likert type) are often used in order to measure specific characteristics which are known to be relevant for the evaluation. The joint distribution of multiple responses provides a complete information in order to attach an overall measure of perceived quality to each student.
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References
Agresti A (2002) Categorical data analysis. Wiley-Intersciencie, Hoboken, NJ
Bartholomew DJ (1998) Scaling unobservable constructs in social science. Appl Stat 47:1–13
Bartholomew DJ, Knott M (1999) Latent variable models and factor analysis. Kendall’s Library of statistics. Hodder Arnold, London
Barholomew DJ, Steele F, Galbraith JI, Moustaki I (2002) The analysis and interpretation of multivariate analysis for social scientists. Chapman & Hall, Boca Raton, FL
Bayol MP, de la Foye A, Tellier C, Tenenhaus M (2000) Use of PLS path modelling to estimate the European consumer satisfaction index (ECSI) model. Stat Appl 12:361–375
Bernardi L, Capursi V, Librizzi L (2004) Measurement awareness: the use of indicators between expectations and opportunities. In: Atti XLII Convegno della Società Italiana di Statistica, Bari, 9–11 Giugno 2004. CLEUP, Padova
Capursi V, Porcu M (2001) La didattica universitaria valutata dagli studenti: un indicatore basato su misure di distanza fra distribuzioni di giudizi. In: Atti Convegno Intermedio della Societ Italiana di Statistica ‘Processi e Metodi Statistici di Valutazione’, Roma 4–6 Giugno 2001. Società Italiana di Statistica
Cronbach LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16:297–334
Hagenaars JA, McCutcheon AL (2002) Applied latent class analysis. Cambridge University Press, Cambridge
Joreskög KG, Sorbom D (1979) Advances in factor analysis and structural equation models. Abt Books, Cambridge, MA
Leti G (1983) Statistica Descrittiva. il Mulino, Bologna
Linzer DA, Lewis J (2007) poLCA: Polytomous variable latent class analysis. R package version 1.1. http://userwww.service.emory.edu/∼dlinzer/poLCA
Linzer DA, Lewis J (forthcoming) poLCA: An R Package for Polytomous variable latent class analysis. Journal of Statiscal Software
Moustaki I, Knott D (2000) Generalized latent trait models. Psychometrika 65:391–411
Rampichini C, Grilli L, Petrucci A (2004) Analysis of university course evaluations: from descriptive measures to multilevel models. Stat Methods Appl 13:357–371
Rasch G (1960) Probabilistic models for some intelligence and attainment tests. MESA Press, Chicago, IL
Sulis I (2007) Measuring students’ assessments of ‘university course quality’ using mixed-effects models. PhD thesis, Università degli Studi di Palermo, Palermo
Wold H (1966) Estimation of principal components and related models by iterative least squares. In: Krishnaiaah PR (ed) Multivariate analysis. Academic Press, New York, NY, pp 391–420
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Sulis, I., Porcu, M. (2011). Assessing the Quality of the Management of Degree Programs by Latent Class Analysis. In: Attanasio, M., Capursi, V. (eds) Statistical Methods for the Evaluation of University Systems. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2375-2_11
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DOI: https://doi.org/10.1007/978-3-7908-2375-2_11
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