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Survival Analysis

Survival Analysis

This course will teach you the various methods used for modeling and evaluating survival data or time-to event data.

This course will teach you the various methods used for modeling and evaluating survival data or time-to event data.

$589 | Enroll Now
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  • Overview
  • Learning Outcomes
  • Instructors
  • Syllabus
  • Dates
  • Prerequisites
  • Student Stories
  • FAQS
  • Requirements
Menu
  • Overview
  • Learning Outcomes
  • Instructors
  • Syllabus
  • Dates
  • Prerequisites
  • Student Stories
  • FAQS
  • Requirements

Overview

This course describes the various methods used for modeling and evaluating survival data, also called time-to-event data. General statistical concepts and methods discussed in this course include survival and hazard functions, Kaplan-Meier graphs, log-rank and related tests, Cox proportional hazards model, and the extended Cox model for time-varying covariates. The course will also require participants to use a convenient statistical package (e.g., SAS, JMP, STATA, R, or S+) to analyze survival analysis data.

ACE + CAP Credit Eligible
ACE + CAP Credit Eligible
Expert Instructors
Teacher Assistant Support

Learning Outcomes

After completing this course you will be able to describe survival data and format it appropriately for analysis and understanding. You will learn to graph data, specify and fit proportional hazard models, check assumptions and compute hazard ratios. You will understand stratified and fully-extended PH models and how they are applied to real-world datasets.

  • Describe survival data, and the roles played by censoring, and survival and hazard functions
  • Format data appropriately for analysis, and understanding
  • Graph survival data, and the Kaplan – Meier curve
  • Specify and fit the Cox Proportional Hazards model
  • Check the PH assumption, and compute the hazard ratio
  • Add stratification to specify a Stratified Cox model (with and without interaction)
  • Describe the fully-extended Cox model
  • Apply models to the “Addicts” data, and the Stanford Heart Transplant Study

Who Should Take This Course

Investigators designing, conducting or analyzing medical studies or clinical trials. Researchers in any field (including engineering) working with data on how long things last.

Instructors

dr-anthony-babinec

Mr. Anthony Babinec

Anthony Babinec is the President of AB Analytics. For over two decades, Tony Babinec has specialized in the application of statistical and data mining methods to the solution of business problems. Before forming AB Analytics, Babinec was Director of Advanced Products Marketing at SPSS; he worked on the marketing of Clementine and introduced CHAID, neural nets and other advanced technologies to SPSS users. He is on the Board of Directors of the Chicago Chapter of the American Statistical Association, where he has held various offices including President.

See Instructor Bio

Course Syllabus

Week 1

Overview

  • An overview of survival analysis methods
  • Censoring
  • Key terms: survival and hazard functions
  • Goals of a survival analysis
  • Data layout for the computer
  • Data layout for understanding
  • Descriptive statistics for survival analysis- the hazard ratio
  • Graphing survival data- Kaplan Meier
  • The Log Rank and related tests.

Week 2

Introduction to Proportional Hazards Models

  • Introduction to the Cox Proportional Hazards (PH) model- computer example
  • Model definition and features
  • Maximum likelihood estimation for the Cox PH model
  • Computing the hazard ratio in the Cox PH model
  • The PH assumption
  • Adjusted survival curves
  • Checking the proportional hazard assumption
  • The likelihood function for the Cox PH model

Week 3

The Stratified Cox Model

  • Introduction to the Stratified Cox procedure
  • The no-interaction Stratified Cox model
  • The Stratified Cox model that allows for interaction

Week 4

Definitions and Examples

  • Definition and examples of time-dependent variables
  • Definition and features of the extended Cox model
  • Stanford Heart Transplant Study Example
  • Addicts Dataset Example
  • The likelihood function for the extended Cox model.

Class Dates

2021

Sep 17, 2021 to Oct 15, 2021

2022

No classes scheduled at this time.

2023

No classes scheduled at this time.

Send me reminder for next class

Prerequisites

Course participants should have some experience with computer procedures for regression modeling.

Introductory Statistics

We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.

    • For Statistics 1 – Probability and Study Design, take this assessment test.
    • For Statistics 2 – Inference and Association, take this assessment test.

Recommended

We recommend, but do not require as eligibility to enroll in this course, an understanding of the material covered in these following courses.

Regression Analysis

Regression Analysis

This course will teach you how multiple linear regression models are derived, assumptions in the models, how to test whether data meets assumptions, and develop strategies for building and understanding useful models.
Topic: Statistics, Statistical Modeling | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: May 7, 2021, Oct 1, 2021

What Our Students Say​

The course has helped me understand how survival curves and hazard ratios are obtained.

Dima Abdallah
University College Dublin

All of the courses I have taken at The Institute have been excellent in providing understanding of statistical concepts by focusing on the logic and theory behind the equations and formulas, which has allowed me to maximize my learning experience

Melissa Brewer
Sage Products

Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.

  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.

Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: https://www.schev.edu/

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

Related Courses

Biostatistics 1 - For Medical Science and Public Health Course

Biostatistics 1 – For Medical Science and Public Health

This course teaches the principal statistical concepts used in medical and health sciences. Basic concepts common to all statistical analysis and of specific importance in medicine and health are covered in detail.
Topic: Statistics, Biostatistics | Skill: Intermediate | Credit Options: ACE, CEU
Class Start Dates: Jul 30, 2021, Jan 7, 2022, Jul 22, 2022, Jan 6, 2023
Mapping in R Course

Biostatistics 2 – For Medical Science and Public Health

This course teaches you clinical trial designs including randomized controlled trials, ROC curves, CI and tests for relative risk and odds ratio, and an introduction to survival analysis.
Topic: Statistics, Biostatistics | Skill: Intermediate | Credit Options: ACE, CEU
Class Start Dates: Aug 27, 2021, Feb 11, 2022, Aug 26, 2022, Feb 10, 2023

Additional Course Information

Organization of Course

This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

Homework in this course consists of short answer questions to test concepts, guided data analysis problems using software, and guided data modeling problems using software.

In addition to assigned readings, this course also has supplemental readings available online.

Course Text

The required text is Survival Analysis- A Self Learning Text, 3rd edition by David G Kleinbaum and Mitchel Klein.  It may be purchased here.

Please order a copy of your course textbook prior to course start date.

Software

You should be familiar with R, SAS, SPSS or Stata.  The instructor can comment on all of them, and can offer limited trouble-shooting with SPSS and R.  The Assistant Teachers can help with Stata and SAS.  Illustrations in the text use SAS, and the text also provides help with the other packages.

 

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

Supplemental Information

There is no supplemental content for this course.

Miscellaneous

There is no additional information for this course.

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Survival Analysis
$589 | Enroll Now
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