6 Lec Q Part 1

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Questions and Answers

Who co-authored the reference book for survival analysis and the survival package?

Terry Therneau and Patricia Grambsch (correct)

Patricia Grambsch

Terry Therneau

Terry Grambsch

Which package provides tools used in the workshop to estimate survival analysis models and tests?

broom

ggplotZ

survival (correct)

survminer

What is the function of the survmi ner package used in the workshop?

Fit a Cox proportional hazards model

Create highly customizable plots of survival functions (correct)

Estimate survival functions

Clean up output tables and store them as data frames

Which researcher and expert in survival analysis created the survival package used in the workshop?

Terry Therneau Signup and view all the answers

What is the purpose of the broom package used in the workshop?

Clean up output tables and store them as data frames Signup and view all the answers

Which package is used for creating highly customizable plots of survival functions?

survminer Signup and view all the answers

What does the su rvi val package in R aim to do?

Estimate survival functions and test whether they are different between groups Signup and view all the answers

What did Grambsch and Therneau develop related to the Cox model assumption?

Methods to assess the proportional hazards assumption of the Cox model Signup and view all the answers

What is one reason for using the survmi ner package in the workshop?

To create highly customizable plots of survival functions Signup and view all the answers

Who created some of the methods used to assess the proportional hazards assumption of the Cox model?

Patricia Grambsch Signup and view all the answers

In survival analysis, what is the simplest data structure for a typical survival analysis?

Single row per subject with a status variable and single time variable Signup and view all the answers

What does the Surv() function in R specify for survival outcomes?

Time and event status variables Signup and view all the answers

When might bias occur in survival estimates due to informative censoring?

When oldest subjects drop out of the study of time to death after surgery Signup and view all the answers

What does the jasal dataset represent in terms of survival analysis data structure?

Data with a single time variable indicating time to event or censoring Signup and view all the answers

What does the survival function estimate in survival analysis?

The probability that a subject survives without experiencing the event past a certain time Signup and view all the answers

What is the hazard function, h(t), in survival analysis?

The instantaneous rate of events at time t, given that the subject has survived until time t Signup and view all the answers

What does the cumulative hazard function, H(t), show in survival analysis?

How much hazard a subject has accumulated up to time t Signup and view all the answers

What is censoring in survival analysis?

It can be right-censoring, left-censoring, or interval censoring, and it is crucial to handle it appropriately Signup and view all the answers

What do most survival analysis methods assume about censoring?

Non-informative censoring, where censoring times and survival times are unrelated Signup and view all the answers

What may lead to biased estimates of survival in survival analysis?

Failing to account for informative censoring Signup and view all the answers

What is commonly used to estimate survival functions and compare survival curves in survival analysis?

The Kaplan-Meier estimator Signup and view all the answers

What does the median survival time represent in survival analysis?

The time at which 50% of the population is expected to still be surviving Signup and view all the answers

What is inversely related to the cumulative hazard function in survival analysis?

The cumulative hazard function Signup and view all the answers

Study Notes

Survival Analysis: Key Concepts and Methods

Survival analysis models the time before an event occurs, with the outcome variable referred to as survival time, failure time, or time to event.
The survival function estimates the probability that a subject survives without experiencing the event past a certain time.
The survival curve expresses the probability of a subject surviving beyond specific time points.
The median survival time is the time at which 50% of the population is expected to still be surviving.
The hazard function, h(t), is the instantaneous rate of events at time t, given that the subject has survived until time t.
The cumulative hazard function, H(t), shows how much hazard a subject has accumulated up to time t.
The survival function is inversely related to the cumulative hazard function.
Censoring in survival analysis can be right-censoring, left-censoring, or interval censoring, and it is crucial to handle it appropriately.
Most survival analysis methods assume non-informative censoring, where censoring times and survival times are unrelated.
Failing to account for informative censoring may lead to biased estimates of survival.
The Kaplan-Meier estimator is commonly used to estimate survival functions and compare survival curves.
Survival analysis has broad applications across various fields, as it can be applied to diverse events such as disease contraction, divorce, machine malfunction, and job occurrence.

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Description

Learn the basics of survival analysis and how to use the survival package in R for estimating survival functions, testing differences between groups, and fitting Cox proportional hazards models. This workshop from UCLA Office of Advanced Research Computing Statistical Methods and Data Analytics provides just enough background to get started.