Training and Research

PhD school courses/classes - 2023/2024

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

1. 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.
More information regarding CFUs is found in the Handbook for PhD Students: https://www.univr.it/phd-vademecum

2. 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. Please do not enquiry: if you entered the requested information, then registration was silently successful.

3. When Zoom links are not explicitly indicated, courses are delivered in presence only.

4. All information we have is published here. Please do not enquiry for missing information or Zoom links: as soon as we get new information, we will promptly publish it on this page.

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

Introduzione alla meta-analisi per la ricerca biomedica (revisione della letteratura, raccolta dei dati, costruzione del database)  (2023/2024)

Teacher

Giuseppe Verlato

Referent

Giuseppe Verlato

Credits

1

Language

English

Class attendance

Free Choice

Seminars 0

Learning objectives

The following topics will be covered: formulation of the review question, searching of literature, quality assessment of studies, data extraction, flow-chart of article selection process, according to PRISMA rules.

Prerequisites and basic notions

Students should have basic knowledge of Mathematics and Statistics.

Program

Confidence interval and precision of the estimate. Methods to compute sample size necessary to achieve an adequate precision in estimating proportions.
Probability of type II error and power of a statistical test. Methods to compute sample size necessary to achieve an adequate statistical power to compare the means of two independent or dependent samples, or the proportions of two independent samples.

Didactic methods

Lessons will take place in the computer room. Statistical power computations will be illustrated by Excel files and Stata software (Stata and R-commander). Participants will be encouraged to bring power calculation problems, to be used as examples in the class.

Learning assessment procedures

A written exam will be administered. Students will have to compute sample size in a given problem.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

The exam will evaluate not only the acquisition of statistical knowledge, but also the ability to adopt it critically to solve health problems.

Criteria for the composition of the final grade

The final mark will be expressed on a scale ranging from 0 to 30. A minimum mark of 18 will be required in order to pass the exam.

Scheduled Lessons

When Classroom Teacher topics
Wednesday 22 May 2024
14:00 - 18:00
Duration: 4:00 AM 		Aula d'Informatica della Piastra Odontoiatrica. https://univr.zoom.us/j/94331181144?pwd=b1hxSVVvKzBsWUlDWkE0bTllV0tzQT09 Giuseppe Verlato Correctly formulating review questions. Selecting appropriate keywords and searching electronic databases. Assessing study quality through the Jadad score for experimental studies and the NOS score for observational studies. Summarizing the article selection process through a flow-chart.