Medical Statistics

Code:

OPT13

Acronym:

EM

Keywords
Classification	Keyword
OFICIAL	Medicine

Instance: 2019/2020 - 1S (of 09-09-2019 to 09-02-2020)

Active?	Yes
Responsible unit:	Department of Community Medicine, Information and Health Decision Sciences
Course/CS Responsible:	Integrated Master in Medicine

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIMED	14	Mestrado Integrado em Medicina- Plano oficial 2013 (Reforma Curricular)	2	-	1,5	14	40,5
			3

Teaching language

Suitable for English-speaking students

Objectives

This unit aims to empower the students with theoretical foundations and practical approach to advanced statistical methods used in clinical research, assessment of technologies and health service research. After this course unit the students should be able to: identify the correct statistical multiple regression methodology for data analysis; apply these methods using statistical software; interpret the results and apply the correct statistical methdos for rater agreement

Learning outcomes and competences

Explain the basic concepts of statistics;
Perform statistical modling and interpret the results: multiple linear regression; logistic regression.
Explain the basic concepts associated with survival analysis, analysis of measurement agreement and probabilistic graphical models.

Working method

Presencial

Program

Review of basic statistical concepts;
Multiple regression concepts:  model building, model selection and model diagnosis;
Multiple linear regression;
Logistic regression;
Basic notions of survival analysis, analysis of measurement agreement and probabilistic graphical models.

Mandatory literature

David G. Kleinbaum; Lawrence L. Kupper; Azhar Nizam; Eli S Rosenberg; Applied Regression Analysis and Other Multivariable Methods, Cengage Learning, 2013
avid W. Hosmer, Stanley Lemeshow, and Rodney X. Sturdivant; Applied Logistic Regression Analysis, Willey -Interscience, 2013
David Collett; Modelling Survival Data in Medical Research, Chapman & Hall, 2009
Daphne Koller and Nir Friedman; Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009
Fleiss J, Levin B,Paik M.; Statistical Methods for Rates and Proportions, Jhon Wiley & Sons, 2003
Bland JM; An Introduction to Medical Statistics, Oxford University Press, 2000

Teaching methods and learning activities

The course unit will have a total duration of 15 hours; 9 hours of theoretical classes and 5 hours of theoretical-practical classes. After the presentation of each topic there will be time to solve practical exercises using statistical software. An e-learning platform will be used to deliver class notes and to facilitate the communication between students and teaching staff.

The final grade will be based on the result of a theoretical exam (10 points) and practical exercises throughout the course unit (10 points).

Software

spss

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	50,00
Teste	50,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	26,50
Frequência das aulas	14,00
Total:	40,50

Eligibility for exams

Presence in 75% of the classes.

Calculation formula of final grade

The final grade will be based on the result of a theoretical exam (10 points) and practical exercises throughout the course unit (10 points).