MASCI, CHIARA

MASCI, CHIARA  

DIPARTIMENTO DI MATEMATICA  

Mostra records
Risultati 1 - 20 di 34 (tempo di esecuzione: 0.027 secondi).
Titolo Data di pubblicazione Autori File
A neural network approach to survival analysis with time-dependent covariates for modelling time to cardiovascular diseases 1-gen-2022 F. CorsoA. Lurani CernuschiC. MasciA. M. PaganoniF. Ieva +
A novel statistical-significance based semi-parametric GLMM for clustering countries standing on their innumeracy levels 1-gen-2023 A. RagniC. MasciF. IevaA. M. Paganoni
Analysis of pupils’ INVALSI achievements by means of bivariate multilevel models. 1-gen-2016 MASCI, CHIARAPAGANONI, ANNA MARIAIEVA, FRANCESCAAGASISTI, TOMMASO
Assessing the impact of hybrid teaching on students’ academic performance via multilevel propensity score-based techniques 1-gen-2024 Ragni A.Masci C. +
Bivariate multilevel models for the analysis of mathematics and reading pupils' achievements 1-gen-2017 MASCI, CHIARAIEVA, FRANCESCAAGASISTI, TOMMASOPAGANONI, ANNA MARIA
BIVARIATE SEMI-PARAMETRIC MIXED-EFFECTS MODELS FOR CLASSIFYING THE EFFECTS OF ITALIAN CLASSES ON MULTIPLE STUDENT ACHIEVEMENTS 1-gen-2019 C. MasciF. IevaT. AgasistiA. M. Paganoni
Classification of Italian classes via bivariate semiparametric multilevel models 1-gen-2019 C. MasciT. AgasistiF. IevaA. M. Paganoni
Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students 1-gen-2016 MASCI, CHIARAIEVA, FRANCESCAAGASISTI, TOMMASOPAGANONI, ANNA MARIA
Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques 1-gen-2021 M. CannistràC. MasciF. IevaA. M. PaganoniT. Agasisti
Evaluating class and school effects on the joint student achievements in different subjects: a bivariate semiparametric model with random coefficients 1-gen-2021 C. MasciF. IevaT. AgasistiA. M. Paganoni
Generalized Mixed Effects Random Forest: does Machine Learning help in predicting university student dropout? 1-gen-2020 M. PellagattiC. MasciF. IevaA. M. Paganoni
Generalized mixed-effects random forest: A flexible approach to predict university student dropout 1-gen-2021 Massimo PellagattiChiara MasciFrancesca IevaAnna M. Paganoni
How Much Tutoring Activities May Improve Academic Careers of At-Risk Students? An Evaluation Study 1-gen-2021 M. CannistràT. AgasistiA. M. PaganoniC. Masci
Inferential Tools for Assessing Dependence Across Response Categories in Multinomial Models with Discrete Random Effects 1-gen-2024 C. MasciF. IevaA. M. Paganoni
Laboratorio di Statistica con R 2/Ed. con MyLab e eText 1-gen-2016 IEVA, FRANCESCAMASCI, CHIARAPAGANONI, ANNA MARIA
Modelling time to university dropout by means of time-dependent frailty COX PH models 1-gen-2022 M. GiovioP. MussidaC. Masci
Modelling time-to-dropout via shared frailty Cox models. A trade-off between accurate and early predictions 1-gen-2023 C. MasciM. CannistràP. Mussida
Multinomial Multilevel Models with Discrete Random Effects: a Multivariate Clustering Tool 1-gen-2022 C. MasciF. IevaA. M. Paganoni
Multinomial semiparametric mixed-effects model for profiling engineering university students 1-gen-2021 C. MasciF. IevaA. M. Paganoni
NONPARAMETRIC MIXED-EFFECTS MODEL FOR UNSUPERVISED CLASSIFICATION IN THE ITALIAN EDUCATION SYSTEM 1-gen-2017 C. MasciT. AgasistiF. IevaA. M. Paganoni