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Survival Analysis

What Is a Hazard Function in Survival Analysis?

by Karen Grace-Martin

One of the key concepts in Survival Analysis is the Hazard Function.

But like a lot of concepts in Survival Analysis, the concept of “hazard” is similar, but not exactly the same as, its meaning in everyday English. Since it’s so important, though, let’s take a look. [Read more…] about What Is a Hazard Function in Survival Analysis?

Tagged With: Cox Regression, discrete, Event History Analysis, hazard function, Survival Analysis

Related Posts

  • Six Types of Survival Analysis and Challenges in Learning Them
  • What is Survival Analysis and When Can It Be Used?
  • Member Training: Cox Regression
  • Member Training: Discrete Time Event History Analysis

Six Types of Survival Analysis and Challenges in Learning Them

by Karen Grace-Martin Leave a Comment

Survival analysis isn’t just a single model.

It’s a whole set of tests, graphs, and models that are all used in slightly different data and study design situations. Choosing the most appropriate model can be challenging.

In this article I will describe the most common types of tests and models in survival analysis, how they differ, and some challenges to learning them.

[Read more…] about Six Types of Survival Analysis and Challenges in Learning Them

Tagged With: Censoring, competing risk model, Cox proportional hazards model, discrete time, Event History Analysis, frailty model, Kaplan-Meier curve, log rank test, parametric models, Survival Analysis, survival functions

Related Posts

  • Member Training: Cox Regression
  • What is Survival Analysis and When Can It Be Used?
  • Member Training: Discrete Time Event History Analysis
  • How to Set up Censored Data for Event History Analysis

What is Survival Analysis and When Can It Be Used?

by guest Leave a Comment

by Steve Simon, PhD

There are two features of survival models.

First is the process of measuring the time in a sample of people, animals, or machines until a specific event occurs. In fact, many people use the term “time to event analysis” or “event history analysis” instead of “survival analysis” to emphasize the broad range of areas where you can apply these techniques.

Second is the recognition that not everyone/everything in your sample will experience the event. Those not experiencing the event, either because the study ended before they had the event or because they were lost to follow-up, are classified as censored observations.

[Read more…] about What is Survival Analysis and When Can It Be Used?

Tagged With: Censoring, Event History Analysis, Survival Analysis, Time to Event

Related Posts

  • Censoring in Time-to-Event Analysis
  • Six Types of Survival Analysis and Challenges in Learning Them
  • Member Training: Cox Regression
  • Member Training: Discrete Time Event History Analysis

Member Training: Cox Regression

by guest Leave a Comment

When you have data measuring the time to an event, you can examine the relationship between various predictor variables and the time to the event using a Cox proportional hazards model.

In this webinar, you will see what a hazard function is and describe the interpretations of increasing, decreasing, and constant hazard. Then you will examine the log rank test, a simple test closely tied to the Kaplan-Meier curve, and the Cox proportional hazards model.


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

 

[Read more…] about Member Training: Cox Regression

Tagged With: Censoring, Cox proportional hazards model, discrete time, Event History Analysis, hazard function, Kaplan-Meier curve, logistic regression, Survival Analysis, Time to Event

Related Posts

  • Member Training: Discrete Time Event History Analysis
  • Six Types of Survival Analysis and Challenges in Learning Them
  • What is Survival Analysis and When Can It Be Used?
  • Censoring in Time-to-Event Analysis

Member Training: Discrete Time Event History Analysis

by Karen Grace-Martin Leave a Comment

What is the relationship between predictors and whether and when an event will occur?

This is what event history (a.k.a., survival) analysis tests.

There are many flavors of Event History Analysis, though, depending on how time is measured, whether events can repeat, etc.

In this webinar, we discussed many of the issues involved in measuring time, including censoring, and introduce one specific type of event history model: the logistic model for discrete time events.


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

[Read more…] about Member Training: Discrete Time Event History Analysis

Tagged With: Censoring, discrete time, Event History Analysis, logistic regression, Survival Analysis, Time to Event

Related Posts

  • Member Training: Cox Regression
  • Six Types of Survival Analysis and Challenges in Learning Them
  • What is Survival Analysis and When Can It Be Used?
  • Censoring in Time-to-Event Analysis

How to Combine Complicated Models with Tricky Effects

by Karen Grace-Martin 4 Comments

Need to dummy code in a Cox regression model?

Interpret interactions in a logistic regression?

Add a quadratic term to a multilevel model?

quadratic interaction plotThis is where statistical analysis starts to feel really hard. You’re combining two difficult issues into one.

You’re dealing with both a complicated modeling technique at Stage 3 (survival analysis, logistic regression, multilevel modeling) and tricky effects in the model (dummy coding, interactions, and quadratic terms).

The only way to figure it all out in a situation like that is to break it down into parts.  [Read more…] about How to Combine Complicated Models with Tricky Effects

Tagged With: Cox Regression, dummy coding, interaction, logistic regression, multilevel model, quadratic terms, Survival Analysis

Related Posts

  • Member Training: Types of Regression Models and When to Use Them
  • When NOT to Center a Predictor Variable in Regression
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  • Concepts in Linear Regression you need to know before learning Multilevel Models

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