Sfoglia per Autore
Analysis of pupils’ INVALSI achievements by means of bivariate multilevel models.
2016-01-01 Masci, Chiara; Paganoni, ANNA MARIA; Ieva, Francesca; Agasisti, Tommaso
Laboratorio di Statistica con R 2/Ed. con MyLab e eText
2016-01-01 Ieva, Francesca; Masci, Chiara; Paganoni, ANNA MARIA
Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students
2016-01-01 Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, ANNA MARIA
NONPARAMETRIC MIXED-EFFECTS MODEL FOR UNSUPERVISED CLASSIFICATION IN THE ITALIAN EDUCATION SYSTEM
2017-01-01 Masci, C.; Agasisti, T.; Ieva, F.; Paganoni, A. M.
Using statistical analytics to study school performance through administrative datasets
2017-01-01 Agasisti, Tommaso; Ieva, Francesca; Masci, Chiara; Paganoni, ANNA MARIA; Soncin, Mara
Bivariate multilevel models for the analysis of mathematics and reading pupils' achievements
2017-01-01 Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, ANNA MARIA
Unsupervised clustering of Italian schools via non-parametric multilevel models.
2018-01-01 Masci, C.; Ieva, F.; Paganoni, A. M.
Student and school performance across countries: A machine learning approach
2018-01-01 Masci, Chiara; Johnes, Geraint; Agasisti, Tommaso
The influence of school size, principal characteristics and school management practices on educational performance: An efficiency analysis of Italian students attending middle schools
2018-01-01 Masci, Chiara; De Witte, Kristof; Agasisti, Tommaso
Using regression tree ensembles to model interaction effects: a graphical approach
2018-01-01 Schiltz, Fritz; Masci, Chiara; Agasisti, Tommaso; Horn, Daniel
BIVARIATE SEMI-PARAMETRIC MIXED-EFFECTS MODELS FOR CLASSIFYING THE EFFECTS OF ITALIAN CLASSES ON MULTIPLE STUDENT ACHIEVEMENTS
2019-01-01 Masci, C.; Ieva, F.; Agasisti, T.; Paganoni, A. M.
Classification of Italian classes via bivariate semiparametric multilevel models
2019-01-01 Masci, C.; Agasisti, T.; Ieva, F.; Paganoni, A. M.
Semiparametric mixed-effects models for unsupervised classification of Italian schools
2019-01-01 Masci, Chiara; Paganoni, ANNA MARIA; Ieva, Francesca
Generalized Mixed Effects Random Forest: does Machine Learning help in predicting university student dropout?
2020-01-01 Pellagatti, M.; Masci, C.; Ieva, F.; Paganoni, A. M.
How Much Tutoring Activities May Improve Academic Careers of At-Risk Students? An Evaluation Study
2021-01-01 Cannistrà, M.; Agasisti, T.; Paganoni, A. M.; Masci, C.
Virtual biopsy in action: a radiomic-based model for CALI prediction
2021-01-01 Ieva, Francesca; Baroni, Giulia; Cavinato, Lara; Masci, Chiara; Costa, Guido; Fiz, Francesco; Chiti, Arturo; Viganò, Luca
Multinomial semiparametric mixed-effects model for profiling engineering university students
2021-01-01 Masci, C.; Ieva, F.; Paganoni, A. M.
Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques
2021-01-01 Cannistrà, M.; Masci, C.; Ieva, F.; Paganoni, A. M.; Agasisti, T.
Performing Learning Analytics via Generalised Mixed-Effects Trees
2021-01-01 Fontana, L.; Masci, C.; Ieva, F.; Paganoni, A. M.
Generalized mixed-effects random forest: A flexible approach to predict university student dropout
2021-01-01 Pellagatti, Massimo; Masci, Chiara; Ieva, Francesca; Paganoni, Anna M.
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