About this Course
최근 조회 15,758

다음 전문 분야의 4개 강좌 중 4번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

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

완료하는 데 약 10시간 필요

권장: 3-5 hours/week...

영어

자막: 영어

배울 내용

  • 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

귀하가 습득할 기술

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

다음 전문 분야의 4개 강좌 중 4번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

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

완료하는 데 약 10시간 필요

권장: 3-5 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 4시간 필요

The Kaplan-Meier Plot

4개 동영상 (총 16분), 11 readings, 3 quizzes
4개의 동영상
What is Survival Analysis?4m
The KM plot and Log-rank test4m
What is Heart Failure and How to run a KM plot in R4m
11개의 읽기 자료
About Imperial College & the team10m
How to be successful in this course10m
Grading policy10m
Data set and glossary10m
Additional Readings10m
Life tables20m
Feedback: Life Tables10m
The Course Data Set20m
Feedback: Running a KM plot and log-rank test3m
Practice in R: Run another KM Plot and log-rank test10m
Feedback: Running another KM plot and log-rank test10m
3개 연습문제
Survival Analysis Variables30m
Life tables30m
Practice in R: Running a KM plot and log-rank test20m
2
완료하는 데 2시간 필요

The Cox Model

3개 동영상 (총 18분), 4 readings, 2 quizzes
3개의 동영상
How to run Simple Cox model in R7m
Introduction to Missing Data5m
4개의 읽기 자료
Hazard Function and Risk Set20m
Practice in R: Simple Cox Model30m
Feedback: Simple Cox Model10m
Further Reading20m
2개 연습문제
Hazard function and Ratio5m
Simple Cox Model15m
3
완료하는 데 2시간 필요

The Multiple Cox Model

1개 동영상 (총 6분), 7 readings, 1 quiz
7개의 읽기 자료
Introduction to Running Descriptives10m
Practice in R: Getting to know your data30m
Feedback: Getting to know your data10m
How to run multiple Cox model in R20m
Introduction to Non-convergence10m
Practice: Fixing the problem of non-convergence10m
Feedback on fixing a non-converging model15m
1개 연습문제
Multiple Cox Model10m
4
완료하는 데 3시간 필요

The Proportionality Assumption

3개 동영상 (총 11분), 7 readings, 3 quizzes
3개의 동영상
Cox proportional hazards assumption4m
Summary of Course2m
7개의 읽기 자료
Checking the proportionality assumption10m
Feedback on Practice Quiz10m
What to do if the proportionality assumption is not met20m
How to choose predictors for a regression model20m
Practice in R: Running a Multiple Cox Model
Results of the exercise on model selection and backwards elimination10m
Final Code10m
3개 연습문제
Assessing the proportionality assumption in practice5m
Testing the proportionality assumption with another variable15m
End-of-Module Assessment20m
4.4
6개의 리뷰Chevron Right

Survival Analysis in R for Public Health의 최상위 리뷰

대학: 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.

대학: FAJul 22nd 2019

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

강사

Avatar

Alex Bottle

Reader in Medical Statistics
School of Public Health

석사 학위 취득 시작

이 강좌은(는) 임페리얼 칼리지 런던의 100% 온라인 Global Master of Public Health 중 일부입니다. 전체 프로그램을 수료하면 귀하의 강좌가 학위 취득에 반영됩니다.

임페리얼 칼리지 런던 정보

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....

공중 보건학을 위한 R을 통한 통계 분석 전문 분야 정보

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....
공중 보건학을 위한 R을 통한 통계 분석

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.