課程信息

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完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
中級

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

完成時間大約為11 小時
英語(English)
字幕:英語(English)

您將學到的內容有

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

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

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

您將獲得的技能

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
可分享的證書
完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
中級

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

完成時間大約為11 小時
英語(English)
字幕:英語(English)

提供方

伦敦帝国学院 徽標

伦敦帝国学院

立即開始攻讀碩士學位

此 課程 隸屬於 伦敦帝国学院 提供的 100% 在線 Global Master of Public Health。如果您被錄取參加全部課程,您的課程將計入您的學位學習進程。

教學大綱 - 您將從這門課程中學到什麼

1

1

完成時間為 4 小時

The Kaplan-Meier Plot

完成時間為 4 小時
4 個視頻 (總計 16 分鐘), 11 個閱讀材料, 3 個測驗
4 個視頻
What is Survival Analysis?4分鐘
The KM plot and Log-rank test4分鐘
What is Heart Failure and How to run a KM plot in R4分鐘
11 個閱讀材料
About Imperial College & the team10分鐘
How to be successful in this course10分鐘
Grading policy10分鐘
Data set and glossary10分鐘
Additional Readings10分鐘
Life tables20分鐘
Feedback: Life Tables10分鐘
The Course Data Set20分鐘
Feedback: Running a KM plot and log-rank test3分鐘
Practice in R: Run another KM Plot and log-rank test10分鐘
Feedback: Running another KM plot and log-rank test10分鐘
3 個練習
Survival Analysis Variables30分鐘
Life tables30分鐘
Practice in R: Running a KM plot and log-rank test20分鐘
2

2

完成時間為 2 小時

The Cox Model

完成時間為 2 小時
3 個視頻 (總計 18 分鐘), 4 個閱讀材料, 2 個測驗
3 個視頻
How to run Simple Cox model in R7分鐘
Introduction to Missing Data5分鐘
4 個閱讀材料
Hazard Function and Risk Set20分鐘
Practice in R: Simple Cox Model30分鐘
Feedback: Simple Cox Model10分鐘
Further Reading20分鐘
2 個練習
Hazard function and Ratio5分鐘
Simple Cox Model15分鐘
3

3

完成時間為 2 小時

The Multiple Cox Model

完成時間為 2 小時
1 個視頻 (總計 6 分鐘), 7 個閱讀材料, 1 個測驗
7 個閱讀材料
Introduction to Running Descriptives10分鐘
Practice in R: Getting to know your data30分鐘
Feedback: Getting to know your data10分鐘
How to run multiple Cox model in R20分鐘
Introduction to Non-convergence10分鐘
Practice: Fixing the problem of non-convergence10分鐘
Feedback on fixing a non-converging model15分鐘
1 個練習
Multiple Cox Model10分鐘
4

4

完成時間為 3 小時

The Proportionality Assumption

完成時間為 3 小時
3 個視頻 (總計 11 分鐘), 7 個閱讀材料, 3 個測驗
3 個視頻
Cox proportional hazards assumption4分鐘
Summary of Course2分鐘
7 個閱讀材料
Checking the proportionality assumption10分鐘
Feedback on Practice Quiz10分鐘
What to do if the proportionality assumption is not met20分鐘
How to choose predictors for a regression model20分鐘
Practice in R: Running a Multiple Cox Model
Results of the exercise on model selection and backwards elimination10分鐘
Final Code10分鐘
3 個練習
Assessing the proportionality assumption in practice5分鐘
Testing the proportionality assumption with another variable15分鐘
End-of-Module Assessment20分鐘

審閱

來自SURVIVAL ANALYSIS IN R FOR PUBLIC HEALTH的熱門評論

查看所有評論

關於 使用 R 进行公共健康领域的统计分析 專項課程

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....
使用 R 进行公共健康领域的统计分析

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