Informações sobre o curso
23,817 visualizações recentes

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

We advise that you first take the previous courses in the series, particularly Introduction to Statistics, though this is not essential.

Aprox. 11 horas para completar

Sugerido: 3-5 hours/week...

Inglês

Legendas: Inglês

O que você vai aprender

  • Check

    Run Kaplan-Meier plots and Cox regression in R and interpret the output

  • Check

    Describe a data set from scratch, using descriptive statistics and simple graphical methods as a necessary first step for more advanced analysis

  • Check

    Describe and compare some common ways to choose a multiple regression model

Habilidades que você terá

Understand common ways to choose what predictors go into a regression modelRun and interpret Kaplan-Meier curves in RConstruct a Cox regression model in R

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

We advise that you first take the previous courses in the series, particularly Introduction to Statistics, though this is not essential.

Aprox. 11 horas para completar

Sugerido: 3-5 hours/week...

Inglês

Legendas: Inglês

Os alunos que estão fazendo este Course são

  • Biostatisticians
  • Data Scientists
  • Medical Doctors
  • Pharmacists
  • Data Analysts

Programa - O que você aprenderá com este curso

Semana
1
4 horas para concluir

The Kaplan-Meier Plot

4 vídeos (Total 16 mín.), 11 leituras, 3 testes
4 videos
What is Survival Analysis?4min
The KM plot and Log-rank test4min
What is Heart Failure and How to run a KM plot in R4min
11 leituras
About Imperial College & the team10min
How to be successful in this course10min
Grading policy10min
Data set and glossary10min
Additional Readings10min
Life tables20min
Feedback: Life Tables10min
The Course Data Set20min
Feedback: Running a KM plot and log-rank test3min
Practice in R: Run another KM Plot and log-rank test10min
Feedback: Running another KM plot and log-rank test10min
3 exercícios práticos
Survival Analysis Variables30min
Life tables30min
Practice in R: Running a KM plot and log-rank test20min
Semana
2
2 horas para concluir

The Cox Model

3 vídeos (Total 18 mín.), 4 leituras, 2 testes
3 videos
How to run Simple Cox model in R7min
Introduction to Missing Data5min
4 leituras
Hazard Function and Risk Set20min
Practice in R: Simple Cox Model30min
Feedback: Simple Cox Model10min
Further Reading20min
2 exercícios práticos
Hazard function and Ratio5min
Simple Cox Model15min
Semana
3
2 horas para concluir

The Multiple Cox Model

1 vídeo (Total 6 mín.), 7 leituras, 1 teste
7 leituras
Introduction to Running Descriptives10min
Practice in R: Getting to know your data30min
Feedback: Getting to know your data10min
How to run multiple Cox model in R20min
Introduction to Non-convergence10min
Practice: Fixing the problem of non-convergence10min
Feedback on fixing a non-converging model15min
1 exercício prático
Multiple Cox Model10min
Semana
4
3 horas para concluir

The Proportionality Assumption

3 vídeos (Total 11 mín.), 7 leituras, 3 testes
3 videos
Cox proportional hazards assumption4min
Summary of Course2min
7 leituras
Checking the proportionality assumption10min
Feedback on Practice Quiz10min
What to do if the proportionality assumption is not met20min
How to choose predictors for a regression model20min
Practice in R: Running a Multiple Cox Model
Results of the exercise on model selection and backwards elimination10min
Final Code10min
3 exercícios práticos
Assessing the proportionality assumption in practice5min
Testing the proportionality assumption with another variable15min
End-of-Module Assessment20min
4.5
6 avaliaçõesChevron Right

Principais avaliações do Survival Analysis in R for Public Health

por VVAug 27th 2019

Good and practical introduction to survival analysis. I liked the emphasis on how to deal with practical data sets and data problems.

por FAJul 22nd 2019

Very nice introductory course on survival analysis in R. Exercises were well designed.

Instrutores

Avatar

Alex Bottle

Reader in Medical Statistics
School of Public Health

Comece a trabalhar rumo ao seu mestrado

Este curso é parte da graduação 100% on-line Global Master of Public Health da Imperial College London. Caso seja aceito para o programa completo, seus cursos contarão para sua graduação.

Sobre 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....

Sobre Programa de cursos integrados Análise estatística com R para saúde pública

Statistics are everywhere. The probability it will rain today. Trends over time in unemployment rates. The odds that India will win the next cricket world cup. In sports like football, they started out as a bit of fun but have grown into big business. Statistical analysis also has a key role in medicine, not least in the broad and core discipline of public health. In this specialisation, you’ll take a peek at what medical research is and how – and indeed why – you turn a vague notion into a scientifically testable hypothesis. You’ll learn about key statistical concepts like sampling, uncertainty, variation, missing values and distributions. Then you’ll get your hands dirty with analysing data sets covering some big public health challenges – fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalisation – using R, one of the most widely used and versatile free software packages around. This specialisation consists of four courses – statistical thinking, linear regression, logistic regression and survival analysis – and is part of our upcoming Global Master in Public Health degree, which is due to start in September 2019. The specialisation can be taken independently of the GMPH and will assume no knowledge of statistics or R software. You just need an interest in medical matters and quantitative data....
Análise estatística com R para saúde pública

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