Teaching code

4S009837

Teacher

Simone Accordini

Coordinator

Simone Accordini

Credits

6

Language

English

Scientific Disciplinary Sector (SSD)

MED/01 - MEDICAL STATISTICS

Period

Semester 1 dal Oct 2, 2023 al Jan 26, 2024.

Courses Single

Authorized

Lessons timetable Moodle Seminars 0

Learning objectives

The course aims at providing the students with the theoretical and practical tools needed to evaluate the frequency of diseases in human populations and the associated risk factors, i.e. expertise in epidemiology, biostatistics and information technology applied to the analysis of biomedical data. Knowledge and understanding: Knowledge and skills concerning the main designs of epidemiological studies, the statistical methods for the analysis of biomedical data and the programming syntax of a statistical software (STATA/R). Applied knowledge and understanding: a) To know the statistical techniques used for the analysis of biomedical data; b) to perform data analysis using a statistical software (STATA/R); c) to interpret the results obtained. Making judgements: Ability to choose the appropriate statistical methods in relation to the type of data and the design of the study. Communication skills: Ability to communicate the results of an analysis of biomedical data clearly and concisely. Lifelong learning skills: Ability to apply autonomously the statistical and epidemiological methodologies learned during the course on various biomedical problems.

Prerequisites and basic notions

The course requires basic knowledge of descriptive statistics and probability theory. There are no preparatory courses.

Program

1. Introduction to epidemiology
- Definition and key features
- Traditional classification of epidemiology
2. Measures of occurrence
- Outcomes
- Prevalence
- Cumulative incidence
- Incidence rate
3. Measures of association and public health impact
- Determinants
- Epidemiological associations
- Attributable risk (AR) and AR%
- Relative risk (RR) and odds ratio (OR)
- Effect modification
4. Epidemiological studies
- Ecological studies
- Cross-sectional studies
- Cohort studies
- Case-control studies
- Experimental studies
5. Causal interpretation of an empirical association
- Statistical vs. causal associations
- Causal models in epidemiology
- Validity of a study (random error, bias, confounding)
- Types of bias
- Methods to control confounding
- Hill’s positive criteria for causality
6. Principles of statistical inference
- Point estimate and sampling distribution
- Confidence interval
- Hypothesis test
- Test of statistical significance
7. Stratified analysis
- Effect modification vs. confounding
- Stratum-specific estimates
- Testing homogeneity
- Pooled estimate
- Testing the stratified null hypothesis of no association
8. Basic statistical models in epidemiological research
- Linear regression model
- Logistic regression model
9. Statistical methods for survival analysis
- Kaplan-Meier non-parametric estimator
- Log-rank test
- Cox regression model

Bibliography

Didactic methods

The course is structured in theoretical frontal lessons (24 hours) and practical lessons in the computer lab (24 hours) on the use of a statistical software (STATA) for the quantitative analysis of biomedical data. The teaching material (slides of the theoretical lessons, STATA/R files used for the practical lessons) is made available to the students on the e-learning web page of the course (Moodle platform).

Learning assessment procedures

The final exam is a written test in the computer lab (duration: 2 hours). The test is the same for attending and non-attending students and for Erasmus students. The aim of the test is to verify the knowledge of all the topics discussed and the ability to solve a biomedical problem by analyzing health data using STATA statistical software. Alternatively, students can use R statistical software. The commands, results and interpretation of the analysis are reported in written form. In addition, students have to answer some questions to ascertain the understanding of theory.

Evaluation criteria

The written test consists of linked questions that guide the analysis of a health dataset and of questions to ascertain the understanding of theory. Each question is assigned a score.

Criteria for the composition of the final grade

The final grade (expressed in thirtieths) is given by the sum of the scores obtained in the individual questions of the written test.

Exam language

Inglese - English