MASCI, CHIARA
A neural network approach to survival analysis with time-dependent covariates for modelling time to cardiovascular diseases
2022-01-01 Corso, F.; Lurani Cernuschi, A.; Galli, L.; Masci, C.; Muccini, C.; Paganoni, A. M.; Ieva, F.
A novel statistical-significance based semi-parametric GLMM for clustering countries standing on their innumeracy levels
2023-01-01 Ragni, A.; Masci, C.; Ieva, F.; Paganoni, A. M.
Analysis of pupils’ INVALSI achievements by means of bivariate multilevel models.
2016-01-01 Masci, Chiara; Paganoni, ANNA MARIA; Ieva, Francesca; Agasisti, Tommaso
Assessing the impact of hybrid teaching on students’ academic performance via multilevel propensity score-based techniques
2024-01-01 Ragni, A.; Ippolito, D.; Masci, C.
Bivariate multilevel models for the analysis of mathematics and reading pupils' achievements
2017-01-01 Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, ANNA MARIA
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.
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
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.
Evaluating class and school effects on the joint student achievements in different subjects: a bivariate semiparametric model with random coefficients
2021-01-01 Masci, C.; Ieva, F.; Agasisti, T.; Paganoni, A. M.
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.
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.
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.
Inferential Tools for Assessing Dependence Across Response Categories in Multinomial Models with Discrete Random Effects
2024-01-01 Masci, C.; Ieva, F.; Paganoni, A. M.
Laboratorio di Statistica con R 2/Ed. con MyLab e eText
2016-01-01 Ieva, Francesca; Masci, Chiara; Paganoni, ANNA MARIA
Modelling time to university dropout by means of time-dependent frailty COX PH models
2022-01-01 Giovio, M.; Mussida, P.; Masci, C.
Multinomial Multilevel Models with Discrete Random Effects: a Multivariate Clustering Tool
2022-01-01 Masci, C.; Ieva, F.; Paganoni, A. M.
Multinomial semiparametric mixed-effects model for profiling engineering university students
2021-01-01 Masci, C.; Ieva, F.; Paganoni, A. M.
NONPARAMETRIC MIXED-EFFECTS MODEL FOR UNSUPERVISED CLASSIFICATION IN THE ITALIAN EDUCATION SYSTEM
2017-01-01 Masci, C.; Agasisti, T.; Ieva, F.; Paganoni, A. M.
Performing Learning Analytics via Generalised Mixed-Effects Trees
2021-01-01 Fontana, L.; Masci, C.; Ieva, F.; Paganoni, A. M.