# Survminer Cheatsheet to Create Easily Survival Plots

We recently released the survminer verion 0.3, which includes many new features to help in **visualizing** and **sumarizing** **survival analysis** results.

In this article, we present a cheatsheet for survminer, created by Przemysław Biecek, and provide an overview of main functions.

## survminer cheatsheet

The cheatsheet can be downloaded from STHDA and from Rstudio. It contains selected important functions, such as:

**ggsurvplot**() for plotting survival curves**ggcoxzph**() and**ggcoxdiagnostics**() for assessing the assumtions of the Cox model**ggforest**() and**ggcoxadjustedcurves**() for summarizing a Cox model

Additional functions, that you might find helpful, are briefly described in the next section.

## survminer overview

The main functions, in the package, are organized in different categories as follow.

**Survival Curves**

**ggsurvplot**(): Draws survival curves with the ‘number at risk’ table, the cumulative number of events table and the cumulative number of censored subjects table.**arrange_ggsurvplots**(): Arranges multiple ggsurvplots on the same page.**ggsurvevents**(): Plots the distribution of event’s times.**surv_summary**(): Summary of a survival curve. Compared to the default summary() function, surv_summary() creates a data frame containing a nice summary from survfit results.**surv_cutpoint**(): Determines the optimal cutpoint for one or multiple continuous variables at once. Provides a value of a cutpoint that correspond to the most significant relation with survival.**pairwise_survdiff**(): Multiple comparisons of survival curves. Calculate pairwise comparisons between group levels with corrections for multiple testing.

**Diagnostics of Cox Model**

**ggcoxzph**(): Graphical test of proportional hazards. Displays a graph of the scaled Schoenfeld residuals, along with a smooth curve using ggplot2. Wrapper around plot.cox.zph().**ggcoxdiagnostics**(): Displays diagnostics graphs presenting goodness of Cox Proportional Hazards Model fit.**ggcoxfunctional**(): Displays graphs of continuous explanatory variable against martingale residuals of null cox proportional hazards model. It helps to properly choose the functional form of continuous variable in cox model.

**Summary of Cox Model**

**ggforest**(): Draws forest plot for CoxPH model.**ggcoxadjustedcurves**(): Plots adjusted survival curves for coxph model.

**Competing Risks**

**ggcompetingrisks**(): Plots cumulative incidence curves for competing risks.

Find out more at http://www.sthda.com/english/rpkgs/survminer/, and check out the documentation and usage examples of each of the functions in survminer package.

## Infos

This analysis has been performed using **R software** (ver. 3.3.2).

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