Acerca de este Curso
4,773

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

A background in health sciences or/and quantitative methods would be useful, but not essential.

Aprox. 9 horas para completar

Sugerido: 4 weeks of study, 2-4 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Qué aprenderás

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    Identify different types of biases that may occur in epidemiological studies, in order to apply strategies to reduce such biases.

Habilidades que obtendrás

ValidityInteraction (Statistics)Information biasConfoundingSelection Bias

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

A background in health sciences or/and quantitative methods would be useful, but not essential.

Aprox. 9 horas para completar

Sugerido: 4 weeks of study, 2-4 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
2 horas para completar

Module 1: Introduction to Validity and Bias

Every time you conduct a study, the most important questions to ask are whether your results are an accurate reflection of the truth both within your sample and in the broader population of interest. This is called validity of the study and more or less determines if your study is of any value. In this module we will discuss what validity actually means and we will describe the different types of systematic error, or bias that may undermine the validity of a study. You will learn how to identify and prevent selection bias and information bias and their variations....
4 videos (Total 16 minutos), 6 readings, 1 quiz
4 videos
Validity4m
Selection Bias4m
Information Bias4m
6 lecturas
About Imperial College & the team5m
How to be successful in this course10m
Grading policy10m
Glossary & Additional readings10m
Examples of Selection and Information Bias30m
Quiz Instructions2m
1 ejercicio de práctica
Validity and Types of Bias25m
Semana
2
3 horas para completar

MODULE 2: Confounding

Studies often focus on the association between two variables; for instance, between a risk factor and a disease. However, reality is usually complex and there are many other variables that may influence this association. Sometimes, the presence of a third variable can either exaggerate the association between the two variables we study or mask an underlying true association. This is called confounding and is any researcher’s nightmare. In this module, you will learn multiple methods to detect confounding in a study, so that you can prepare to deal with it. By the end of the module, you will be able to apply these methods to actual data and conclude whether there is confounding....
3 videos (Total 13 minutos), 1 reading, 1 quiz
3 videos
Criteria for Confounding5m
Criteria for Confounding: An Example4m
1 lectura
Recap: How to Identify Confounding10m
Semana
3
1 hora para completar

MODULE 3: Dealing with Confounding

This module is dedicated to dealing with confounding. Confounding can be addressed either at the design stage, before data is collected, or at the analysis stage. You will learn the main approaches to dealing with confounding and you will see practical examples on how to do this in your own studies. We will also briefly discuss about the Directed Acyclic Graphs, which is a novel way to detect bias and confounding and control for them....
5 videos (Total 16 minutos), 2 readings, 1 quiz
5 videos
Controlling for Confounding at the Design Stage: Example2m
Controlling for Confounding at the Analysis Stage3m
Controlling for Confounding at the Analysis Stage: Example2m
Directed Acyclic Graphs (DAGs)3m
2 lecturas
Recap: How to Control for Confounding5m
Quiz Instructions4m
1 ejercicio de práctica
Dealing with Confounding20m
Semana
4
2 horas para completar

MODULE 4: Effect Modification

This is the final module of the course. We start by discussing what happens when the effect of an exposure on an outcome differs across levels of another variable. This is called effect modification. We will discuss how to approach effect modification and we will highlight the distinction between confounding and effect modification. We will close the course by revisiting causal inference in epidemiology, discussing how we can go through all potential explanations of an association before deciding whether it is of causal nature....
4 videos (Total 14 minutos), 3 readings, 2 quizzes
4 videos
Confounding vs Effect Modification3m
Causation3m
Course Summary1m
3 lecturas
Confounding or Effect Modification?10m
Quiz Instructions2m
Quiz Instructions2m
2 ejercicios de práctica
Confounding and Effect Modification30m
Bias, Confounding and Effect Modification45m

Instructor

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Filippos Filippidis

Lecturer in Public Health
School of Public Health

Comienza a trabajar para obtener tu maestría

Este curso es parte del Global Master of Public Health completamente en línea de Imperial College London. Si eres aceptado en el programa completo, tus cursos cuentan para tu título.

Acerca de Imperial College London

Imperial College London is a world top ten university with an international reputation for excellence in science, engineering, medicine and business. located in the heart of London. Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges. Imperial students benefit from a world-leading, inclusive educational experience, rooted in the College’s world-leading research. Our online courses are designed to promote interactivity, learning and the development of core skills, through the use of cutting-edge digital technology....

Acerca del programa especializado Epidemiology for Public Health

Thousands of new epidemiological studies are conducted every year and their results can have a profound impact on how we live our lives. Decisions regarding the food you eat, how much you exercise, where you live and what treatment you will follow if you get sick are made based on data from such studies. This specialization aims to equip you with the skills that will allow you to correctly interpret epidemiological research, consider its limitations, and design your own studies. The first course of the specialisation, Measuring Disease in Epidemiology, looks into the main measures used in epidemiology and how these can inform decisions around public health policy, screening and prevention. The second course, Study Designs in Epidemiology, provides an overview of the most common study designs, their strengths and limitations. The third course, Validity and Bias in Epidemiology, builds on the fundamental concepts taught in the previous courses to discuss bias and confounding and how they might affect study results. It also provides the essential skills to prevent and control bias and confounding and critically think about causality. At the end of this specialization you will have gained the essential skills to design and critique epidemiological research and you will be able to pursue more advanced courses in epidemiology. Although this specialization is part of the GMPH programme, it can be taken independently of the GMPH....
Epidemiology for Public Health

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