Formazione e ricerca

Attività Formative della Scuola di Dottorato - 2023/2024

Please note: Additional information will be added during the year. Currently missing information is labelled as “TBD” (i.e. To Be Determined).

PhD students must obtain a specified number of CFUs each year by attending teaching activities offered by the PhD School.
First and second year students must obtain 8 CFUs. Teaching activities ex DM 226/2021 provide 5 CFUs; free choice activities provide 3 CFUs.
Third year students must obtain 4 CFUs. Teaching activities ex DM 226/2021 provide 2 CFUs; free choice activities provide 2 CFUs.

Registering for the courses is not required unless explicitly indicated; please consult the course information to verify whether registration is required or not. When registration is actually required, no confirmation e-mail will be sent after signing up.

Teaching Activities ex DM 226/2021: Linguistic Activities

Teaching Activities ex DM 226/2021: Research management and Enhancement

Teaching Activities ex DM 226/2021: Statistics and Computer Sciences

Teaching Activities: Free choice

Generalized linear models: logistic regression, loglinear model, Poisson model  (2023/2024)

Docente

Lucia Cazzoletti

Referente

Lucia Cazzoletti

Crediti

2

Lingua di erogazione

English

Frequenza alle lezioni

Scelta Libera

Sede

VERONA

MoodleMoodle Seminari 0

Obiettivi di apprendimento

An introduction to the fundamentals of generalized regression models will be given in this course, with a focus on models for count, binary, and categorical data. These types of response variables are widely used in industrial applications as well as observational and experimental research.
Upon successful completion of the course, students will be able to:
• Describe the general structure of a GLM and similarities and differences with linear models
• Estimate and interpret a logistic regression model
• Estimate and interpret a Poisson regression model
• Know of issues and some strategies for dealing with overdispersion in some generalised linear models (GLMs)

Prerequisiti e nozioni di base

This course assumes a good understanding of probability and mid-level knowledge of linear regression theory.

Programma

The course covers methods for regression analysis of responses that do not follow the normal distribution, especially of discrete responses. We will learn to understand some of the common statistical methods for fitting regression models to such data. In particular, we will consider logistic regression, Poisson regression and log-linear models. The lecture focuses on the development, theoretical justification, and interpretation of these methods.

Quando e Dove

This course assumes a good understanding of probability and mid-level knowledge of linear regression theory.
Teaching forms mainly consist of lectures (8h) and exercises proposed by the teacher. The teaching material (slides of the theoretical lessons) is made available to the students on the e-learning web page of the course (Moodle platform). Lessons will be delivered via Zoom. Full attendance is required.
19 March 2024, 14.30-16.30
26 March 2024, 14.30-16.30
3 April 2024, 14.30-16.30
24 April 2024, 14.30-16.30
Zoom link

Modalità di verifica dell'apprendimento

There is no exam

Le/gli studentesse/studenti con disabilità o disturbi specifici di apprendimento (DSA), che intendano richiedere l'adattamento della prova d'esame, devono seguire le indicazioni riportate QUI

Valutazione

There is no exam, hence there is also no definition of the evaluation criteria.

Criteri di composizione del voto finale

There is no grade because there is no exam.

Lezioni Programmate

Quando Aula Docente Argomenti
martedì 19 marzo 2024
14:30 - 16:30
Durata: 2.00 		Da definire Lucia Cazzoletti Introduction to generalised linear models. Review of the general linear model: assumptions of the linear model (independence of observations, homoskedasticity of errors, linearity of coeffiicents) , least squares estimation and maximum likelihood estimation. Main features of the genralised linear model: i) the probability distribution function of the random component of the response variable belongs to the exponential family, ii) a differentiable and monotonic link function relates the mean of the response variable to the linear predictor, a linear combination of coefficients and explanatory variables.
martedì 26 marzo 2024
14:30 - 16:30
Durata: 2.00 		Da definire Lucia Cazzoletti Introduction to the theoretical basis of logistic regression model, commonly used for binary (proportion/percentage) data, as a generalised linear model. Binomial distribution for the outcome binary variable. The link between probability and logodds. Maximum likelihood estimation of the coefficients of the model. Interpretation of the meaning of the regression coefficients and their statistical significance.
mercoledì 03 aprile 2024
14:30 - 16:30
Durata: 2.00 		Da definire Lucia Cazzoletti Introduction to the theoretical basis of Poisson regression model, commonly used for count data, as a generalised linear model. Poisson distribution for the outcome variable. Maximum likelihood estimation of the coefficients of the model. Interpretation of the meaning of the regression coefficients and their statistical significance. Use of the offset to take into account the different exposure of subjects. Extensions of the Poisson Regression Model: Negative binomial regression model (NBRM), Zero-inflated poisson (ZIP) model, Zero-truncated count data model.
mercoledì 24 aprile 2024
14:30 - 16:30
Durata: 2.00 		Aula virtuale - Lezione online Lucia Cazzoletti Using Deviances to Compare Models for Logistic and for Poisson Regression Models. Use of the Likelihood Ratio Test to assess the presence of overdispersion. Some hints about the log-linear model in the presence of contingency tables

Docenti

B C F G K L M R S T V Z
Foto Battaglia, 31 agosto 2022

Battaglia Yuri

symbol email yuri.battaglia@univr.it
foto bertoldo, 4 aprile 2018

Bertoldo Francesco

symbol email francesco.bertoldo@univr.it symbol phone-number +39 045 812 6485
s, 15 maggio 2018

Carrara Elena

symbol email elena.carrara@univr.it
Foto tessera, 5 dicembre 2017

Ciccocioppo Rachele

symbol email rachele.ciccocioppo@univr.it symbol phone-number 045 8124466
CravediPaolo

Cravedi Paolo

Foto profilo, 7 luglio 2021

Crisafulli Ernesto

symbol email ernesto.crisafulli@univr.it symbol phone-number +39 045 812 8146
Foto, 17 marzo 2018

Fantin Francesco

symbol email francesco.fantin@univr.it symbol phone-number +39 045 812 3577
FavaCristiano

Fava Cristiano

symbol email cristiano.fava@univr.it symbol phone-number +39 045 8124732
foto, 22 febbraio 2018

Fratta Pasini Anna Maria

symbol email annamaria.frattapasini@univr.it symbol phone-number +39 045 8124749
Luca Frulloni, 13 maggio 2016

Frulloni Luca

symbol email luca.frulloni@univr.it symbol phone-number 045 8124466
foto, 10 marzo 2018

Gatti Davide

symbol email davide.gatti@univr.it
foto, 4 luglio 2022

Girolomoni Giampiero

symbol email giampiero.girolomoni@univr.it symbol phone-number +39 045 812 2547
Paolo Gisondi, 5 aprile 2018

Gisondi Paolo

symbol email paolo.gisondi@univr.it symbol phone-number +39 045 812 2547
Foto Prof. Krampera, 5 luglio 2017

Krampera Mauro

symbol email mauro.krampera@univr.it symbol phone-number 0458124034
Foto Massimo Lanza, 21 settembre 2017

Lanza Massimo

symbol email massimo.lanza@univr.it symbol phone-number +39 0458425118
Foto, 14 dicembre 2022

Mantovani Alessandro

symbol email alessandro.mantovani@univr.it symbol phone-number 0458127672
MazzaliGloria

Mazzali Gloria

symbol email gloria.mazzali@aovr.veneto.it symbol phone-number +39 045 807 3577
Foto Pietro Minuz, 14 novembre 2017

Minuz Pietro

symbol email pietro.minuz@univr.it symbol phone-number +39 045 812 4414
Foto, 25 luglio 2018

Romano Simone

symbol email simone.romano@univr.it symbol phone-number 0458124414
Prof. M.Rossini, 13 dicembre 2016

Rossini Maurizio

symbol email maurizio.rossini@libero.it symbol phone-number +39 045 8126338
foto, 15 ottobre 2020

Sacerdoti David

symbol email DAVID.SACERDOTI@UNIVR.IT symbol phone-number 0458128159
foto, 3 marzo 2015

Targher Giovanni

symbol email giovanni.targher@univr.it symbol phone-number +39 045 6014530
foto, 25 giugno 2021

Trifirò Gianluca

symbol email gianluca.trifiro@univr.it symbol phone-number 0458027612
foto, 16 marzo 2018

Viapiana Ombretta

symbol email ombretta.viapiana@univr.it symbol phone-number +39 045 812 4049
FOTO, 26 ottobre 2017

Zamboni Mauro

symbol email mauro.zamboni@univr.it symbol phone-number +39 045 812 2537
Foto Dott. Elena Zoico, 9 maggio 2018

Zoico Elena

symbol email elena.zoico@univr.it symbol phone-number +39 045 812-2537
foto per il web, 28 marzo 2018

Zoppini Giacomo

symbol email giacomo.zoppini@univr.it symbol phone-number +39 045 8123115

Dottorandi

Dottorandi presenti nel:

Non è presente alcuna persona. 40° Ciclo non iniziato.

Lezioni del Corso
Lezioni della Scuola di Dottorato

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Linee guida percorso formativo

Di seguito i file che contengono le Linee guida per il percorso formativo e il regolamento per l'acquisizione dei crediti formativi (CFU) per l'Anno Accademico 2023/2024.