Chiara Masci
Chiara Masci
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Student and school performance across countries: A machine learning approach
C Masci, G Johnes, T Agasisti
European Journal of Operational Research 269 (3), 1072-1085, 2018
The influence of school size, principal characteristics and school management practices on educational performance: An efficiency analysis of Italian students attending middle …
C Masci, K De Witte, T Agasisti
Socio-Economic Planning Sciences 61, 52-69, 2018
Generalized mixed‐effects random forest: a flexible approach to predict university student dropout
M Pellagatti, C Masci, F Ieva, AM Paganoni
Statistical Analysis and Data Mining: The ASA Data Science Journal 14 (3 …, 2021
Using regression tree ensembles to model interaction effects: a graphical approach
F Schiltz, C Masci, T Agasisti, D Horn
Applied Economics 50 (58), 6341-6354, 2018
PET/CT-based radiomics of mass-forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival
F Fiz, C Masci, G Costa, M Sollini, A Chiti, F Ieva, G Torzilli, L Viganò
European journal of nuclear medicine and molecular imaging 49 (10), 3387-3400, 2022
Bivariate multilevel models for the analysis of mathematics and reading pupils' achievements
C Masci, F Ieva, T Agasisti, AM Paganoni
Journal of Applied Statistics 44 (7), 1296-1317, 2017
Does class matter more than school? Evidence from a multilevel statistical analysis on Italian junior secondary school students
C Masci, F Ieva, T Agasisti, AM Paganoni
Socio-Economic Planning Sciences 54, 47-57, 2016
Early-predicting dropout of university students: an application of innovative multilevel machine learning and statistical techniques
M Cannistrà, C Masci, F Ieva, T Agasisti, AM Paganoni
Studies in Higher Education 47 (9), 1935-1956, 2022
Virtual biopsy for diagnosis of chemotherapy-associated liver injuries and steatohepatitis: a combined radiomic and clinical model in patients with colorectal liver metastases
G Costa, L Cavinato, C Masci, F Fiz, M Sollini, LS Politi, A Chiti, ...
Cancers 13 (12), 3077, 2021
Performing learning analytics via generalised mixed-effects trees
L Fontana, C Masci, F Ieva, AM Paganoni
Data 6 (7), 74, 2021
Semiparametric mixed effects models for unsupervised classification of Italian schools
C Masci, AM Paganoni, F Ieva
Journal of the Royal Statistical Society Series A: Statistics in Society 182 …, 2019
Evaluating class and school effects on the joint student achievements in different subjects: a bivariate semiparametric model with random coefficients
C Masci, F Ieva, T Agasisti, AM Paganoni
Computational Statistics 36 (4), 2337-2377, 2021
Not the magic algorithm: modelling and early-predicting students dropout through machine learning and multilevel approach
M Cannistrà, C Masci, F Ieva, T Agasisti, A Paganoni
MOX-Modelling and Scientific Computing, Department of Mathematics …, 2020
Semiparametric multinomial mixed-effects models: A university students profiling tool
C Masci, F Ieva, AM Paganoni
The Annals of Applied Statistics 16 (3), 1608-1632, 2022
Using machine learning to model interaction effects in education: A graphical approach
F Schiltz, C Masci, T Agasisti, D Horn
Budapest Working Papers on the Labour Market, 2017
The determinants of mathematics achievement: a gender perspective using multilevel random forest
A Bertoletti, M Cannistrà, M Diaz Lema, C Masci, A Mergoni, L Rossi, ...
Economies 11 (2), 32, 2023
Laboratorio di statistica con R. Eserciziario
AM Paganoni, F Ieva, V Vitelli
Using statistical analytics to study school performance through administrative datasets
T Agasisti, F Ieva, C Masci, AM Paganoni, M Soncin
Data Analytics Applications in Education, 183-209, 2017
Clustering Hierarchies via a Semi-Parametric Generalized Linear Mixed Model: a statistical significance-based approach
A Ragni, C Masci, F Ieva, AM Paganoni
arXiv preprint arXiv:2302.12103, 2023
Survival models for predicting student dropout at university across time
C Masci, M Giovio, P Mussida
Education and new developments, 203, 2022
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