# Survival models in DataSHIELD

**URL:** <https://datashield.discourse.group/t/survival-models-in-datashield/565>\
**Category:** Statistical help\
**Created:** [29 May 2022 05:11 UTC](https://datashield.discourse.group/t/survival-models-in-datashield/565 "2022-05-29T05:11:06Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![neelsoumya](https://avatars.discourse-cdn.com/v4/letter/n/9dc877/32.png) [@neelsoumya](https://datashield.discourse.group/u/neelsoumya)\
**Post date:** [29 May 2022 05:11 UTC](https://datashield.discourse.group/t/survival-models-in-datashield/565/1 "2022-05-29T05:11:06Z")

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Dear All,

Survival functionality is now available in DataSHIELD in the dsSurvival package.

A preprint describing this is also available named:

dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD

Please cite this preprint if you use the package.

Kind regards Soumya

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**Author:** ![neelsoumya](https://avatars.discourse-cdn.com/v4/letter/n/9dc877/32.png) [@neelsoumya](https://datashield.discourse.group/u/neelsoumya)\
**Post date:** [29 May 2022 05:12 UTC](https://datashield.discourse.group/t/survival-models-in-datashield/565/2 "2022-05-29T05:12:08Z")

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> **[GitHub - neelsoumya/dsSurvival: Survival functions for DataSHIELD. Package...](https://github.com/neelsoumya/dsSurvival)**
>
> Survival functions for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD. - GitHub - neelsoumya/dsSurvival: Survival function...

> **[GitHub - neelsoumya/dsSurvivalClient: Survival functions (client side) for...](https://github.com/neelsoumya/dsSurvivalClient)**
>
> Survival functions (client side) for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD. - GitHub - neelsoumya/dsSurvivalClien...

> **[dsSurvival: Privacy preserving survival models in DataSHIELD](https://neelsoumya.github.io/dsSurvival_bookdown/)**
>
> This is a bookdown demonstrating how to build privacy preserving survival models using dsSurvival in DataSHIELD. The output format for this example is bookdown::gitbook.

Banerjee S, Sofack G, Papakonstantinou T, Avraam D, Burton P, et al. (2022), dsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD, bioRxiv: 2022.01.04.471418.

> **[dsSurvival: Privacy preserving survival models for federated individual...](https://www.biorxiv.org/content/10.1101/2022.01.04.471418v2)**
>
> Objective Achieving sufficient statistical power in a survival analysis usually requires large amounts of data from different sites. Sensitivity of individual-level data, ethical and practical considerations regarding data sharing across institutions...

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**Author:** ![neelsoumya](https://avatars.discourse-cdn.com/v4/letter/n/9dc877/32.png) [@neelsoumya](https://datashield.discourse.group/u/neelsoumya)\
**Post date:** [5 June 2022 07:10 UTC](https://datashield.discourse.group/t/survival-models-in-datashield/565/3 "2022-06-05T07:10:04Z")

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the published article for dsSurvival is now available here

> **[dsSurvival: Privacy preserving survival models for federated individual...](https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-022-06085-1)**
>
> Objective Achieving sufficient statistical power in a survival analysis usually requires large amounts of data from different sites. Sensitivity of individual-level data, ethical and practical considerations regarding data sharing across institutions...