Research Methodologies in Biostatistics II

Code:

MO11

Acronym:

MIBII

Keywords
Classification	Keyword
OFICIAL	Health Sciences

Instance: 2022/2023 - 2S (of 13-02-2023 to 02-06-2023)

Active?	Yes
Responsible unit:	Population Studies
Course/CS Responsible:	Master Degree in Oncology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MO	21	Oficial Plan 2018	1	-	3	25	81

Teaching language

Suitable for English-speaking students

Objectives

Develop critical skills, especially critical reading of literature in basic and clinical research in Oncology

Understanding of statistical methods and their importance to the practice of basic and clinical research in oncology.

Acquire critical skills, especially critical reading of literature in basic and clinical research in Oncology

Learning outcomes and competences

The syllabus of this unit responds to the stated objectives of understanding and being able to build statistical models in basic and clinical research in Oncology

Working method

Presencial

Program

1. Analysis of Variance

• Randomized block design. Fatorial design. Residual analysis. Repeated Measures.

1. Multiple Regression Model

• Inference about the regression parameters. Methods for selection of variables.

1. Logistic Regression Model

• Introduction. Interpretation of the coefficients. Strategies for constructing the model. Effect modification and confouding.

1. Diagnostic tests. T

• est classification by disease status: False Positive, False Negative, Positive Predictive Vale, Negative Predictive Value. The ROC curve. Indexes: Area under the curve, Youden Index. Comparing ROC curves.

1. Survival analysis

• Survival function and hazard function. Comparison of survival curves. Cox model. Relative survival.

Mandatory literature

Armitage P.; Statistical methods in medical research. ISBN: 632-05430-1
D Altman; Statistical Methods in Medical Research
Hosmer DW & Lemeshow S;; Applied Logistic Regression
Kleinbaum, D:G, Klein, M;; Survival Analysis: A Self-Learning Text,

Teaching methods and learning activities

1. Self-directed learning


2. Expository, collaborative and active methodology


3. Applied learning (solving exercises)

 

• Seminars and Lectures

 

• Discussion of problems and of the use of statistical software  SPSS and EXCEL on the application of statistical methods.

Teaching methodologies 1, 2 and 3 cover all the stated objectives

 

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	60,00
Trabalho de campo	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	54,00
Frequência das aulas	27,00
Total:	81,00

Eligibility for exams

Attendance of at least 70% of the prgrammed lectures

Calculation formula of final grade

Normal:

The final classification is given by the following formula

CF = 0.4 (Group work) + 0.6 (Individual examination)

Minimum classification on the individual exam: 7.5

Resiiting

The final classification is given by

CF= (individual examination)

Examinations or Special Assignments

It is compulsory the realization of all works (minimal average classification of 7.5 marks)