このコースについて
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100%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

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

英語

字幕:英語

学習内容

  • 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

習得するスキル

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%オンライン

自分のスケジュールですぐに学習を始めてください。

柔軟性のある期限

スケジュールに従って期限をリセットします。

中級レベル

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

英語

字幕:英語

シラバス - 本コースの学習内容

1
4時間で修了

The Kaplan-Meier Plot

What is survival analysis? You’ll see what it is, when to use it and how to run and interpret the most common descriptive survival analysis method, the Kaplan-Meier plot and its associated log-rank test for comparing the survival of two or more patient groups, e.g. those on different treatments. You’ll learn about the key concept of censoring.

...
4件のビデオ (合計16分), 11 readings, 3 quizzes
4件のビデオ
What is Survival Analysis?4 分
The KM plot and Log-rank test4 分
What is Heart Failure and How to run a KM plot in R4 分
11件の学習用教材
About Imperial College & the team10 分
How to be successful in this course10 分
Grading policy10 分
Data set and glossary10 分
Additional Readings10 分
Life tables20 分
Feedback: Life Tables10 分
The Course Data Set20 分
Feedback: Running a KM plot and log-rank test3 分
Practice in R: Run another KM Plot and log-rank test10 分
Feedback: Running another KM plot and log-rank test10 分
3の練習問題
Survival Analysis Variables30 分
Life tables30 分
Practice in R: Running a KM plot and log-rank test20 分
2
2時間で修了

The Cox Model

This week you’ll get to know the most commonly used survival analysis method for incorporating not just one but multiple predictors of survival: Cox proportional hazards regression modelling. You’ll learn about the key concepts of hazards and the risk set. From now and until the end of this course, there’ll be plenty of chance to run Cox models on data simulated from real patient-level records for people admitted to hospital with heart failure. You’ll see why missing data and categorical variables can cause problems in regression models such as Cox.

...
3件のビデオ (合計18分), 4 readings, 2 quizzes
3件のビデオ
How to run Simple Cox model in R7 分
Introduction to Missing Data5 分
4件の学習用教材
Hazard Function and Risk Set20 分
Practice in R: Simple Cox Model30 分
Feedback: Simple Cox Model10 分
Further Reading20 分
2の練習問題
Hazard function and Ratio5 分
Simple Cox Model15 分
3
2時間で修了

The Multiple Cox Model

You’ll extend the simple Cox model to the multiple Cox model. As preparation, you’ll run the essential descriptive statistics on your main variables. Then you’ll see what can happen with real-life public health data and learn some simple tricks to fix the problem.

...
1件のビデオ (合計6分), 7 readings, 1 quiz
7件の学習用教材
Introduction to Running Descriptives10 分
Practice in R: Getting to know your data30 分
Feedback: Getting to know your data10 分
How to run multiple Cox model in R20 分
Introduction to Non-convergence10 分
Practice: Fixing the problem of non-convergence10 分
Feedback on fixing a non-converging model15 分
1の練習問題
Multiple Cox Model10 分
4
3時間で修了

The Proportionality Assumption

In this final part of the course, you’ll learn how to assess the fit of the model and test the validity of the main assumptions involved in Cox regression such as proportional hazards. This will cover three types of residuals. Lastly, you’ll get to practise fitting a multiple Cox regression model and will have to decide which predictors to include and which to drop, a ubiquitous challenge for people fitting any type of regression model.

...
3件のビデオ (合計11分), 7 readings, 3 quizzes
3件のビデオ
Cox proportional hazards assumption4 分
Summary of Course2 分
7件の学習用教材
Checking the proportionality assumption10 分
Feedback on Practice Quiz10 分
What to do if the proportionality assumption is not met20 分
How to choose predictors for a regression model20 分
Practice in R: Running a Multiple Cox Model
Results of the exercise on model selection and backwards elimination10 分
Final Code10 分
3の練習問題
Assessing the proportionality assumption in practice5 分
Testing the proportionality assumption with another variable15 分
End-of-Module Assessment20 分

講師

Avatar

Alex Bottle

Reader in Medical Statistics
School of Public Health

修士号の取得を目指しましょう

この コース は インペリアル・カレッジ・ロンドン(Imperial College London) の100%オンラインの Global Master of Public Health の一部です。 プログラムのすべてで認定されれば、それらのコースが学位学習に加算されます。

インペリアル・カレッジ・ロンドン(Imperial College London)について

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....

Statistical Analysis with R for Public Healthの専門講座について

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....
Statistical Analysis with R for Public Health

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