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Survival Analysis in Excel

Survival analysis is a statistical technique used to analyze the time until an event of interest occurs.

While Excel may not have dedicated survival analysis functions, you can perform basic survival analysis by using its features. Below is a guide on how to conduct survival analysis in Excel:

Data Preparation

Organize your data in Excel with columns for event times (time to an event or failure) and event indicators (1 if the event occurred, 0 if it did not). Include any relevant covariates (independent variables).

Calculate Survival Function

Calculate the survival function, denoted as S(t), which represents the probability of surviving beyond time t. You can use Excel’s functions to compute survival probabilities based on your data. For example:


Drag this formula down to calculate survival probabilities for different time points.

Create Kaplan-Meier Survival Curves

Visualize your survival data by creating Kaplan-Meier survival curves. Plot time on the x-axis and S(t) on the y-axis using Excel’s charting tools.

Perform Log-Rank Test

For comparing survival curves between groups, you can approximate the log-rank test process in Excel by manually calculating the observed minus expected events and using this to assess group differences. While Excel doesn’t have a built-in log-rank test function, you can:

This process requires careful data arrangement and manual calculations, highlighting Excel’s limitations for conducting sophisticated statistical tests like the log-rank test directly.

Cox Proportional-Hazards Model (Optional)

Applying the Cox Proportional-Hazards Model in Excel is challenging due to the lack of direct support for regression models that handle time-to-event data. However, for a basic understanding or preliminary analysis:

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