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Bilibili-Evolved | 强大的哔哩哔哩增强脚本 - 文档站点由 FoundTheWOUT 开发 , 点此进入 GitHub 仓库 | Privacy library

 by   the1812 TypeScript Version: v2.1.7 License: MIT

 by   the1812 TypeScript Version: v2.1.7 License: MIT

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kandi X-RAY | Bilibili-Evolved Summary

Bilibili-Evolved is a TypeScript library typically used in Security, Privacy, Bilibili applications. Bilibili-Evolved has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.
强大的哔哩哔哩增强脚本
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • Bilibili-Evolved has a medium active ecosystem.
  • It has 12269 star(s) with 1145 fork(s). There are 94 watchers for this library.
  • There were 10 major release(s) in the last 12 months.
  • There are 331 open issues and 1704 have been closed. On average issues are closed in 11 days. There are 2 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of Bilibili-Evolved is v2.1.7
Bilibili-Evolved Support
Best in #Privacy
Average in #Privacy
Bilibili-Evolved Support
Best in #Privacy
Average in #Privacy

quality kandi Quality

  • Bilibili-Evolved has 0 bugs and 0 code smells.
Bilibili-Evolved Quality
Best in #Privacy
Average in #Privacy
Bilibili-Evolved Quality
Best in #Privacy
Average in #Privacy

securitySecurity

  • Bilibili-Evolved has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • Bilibili-Evolved code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
Bilibili-Evolved Security
Best in #Privacy
Average in #Privacy
Bilibili-Evolved Security
Best in #Privacy
Average in #Privacy

license License

  • Bilibili-Evolved is licensed under the MIT License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
Bilibili-Evolved License
Best in #Privacy
Average in #Privacy
Bilibili-Evolved License
Best in #Privacy
Average in #Privacy

buildReuse

  • Bilibili-Evolved releases are available to install and integrate.
  • It has 20710 lines of code, 0 functions and 572 files.
  • It has low code complexity. Code complexity directly impacts maintainability of the code.
Bilibili-Evolved Reuse
Best in #Privacy
Average in #Privacy
Bilibili-Evolved Reuse
Best in #Privacy
Average in #Privacy
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Bilibili-Evolved Key Features

强大的哔哩哔哩增强脚本

Community Discussions

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QUESTION

De-identifying survival or flexsurvreg objects in R

Asked 2022-Mar-29 at 11:01

Please consider the following:

I need to provide some R code syntax to analyse data with the flexsurv package. I am not allowed to receive/analyse directly or on-site. I am however allowed to receive the analysis results.


Problem

When we run the flexsurvreg() function on some data (here ovarian from the flexsurv package), the created object (here fitw) contains enough information to "re-create" or "back-engineer" the actual data. But then I would technically have access to the data I am not allowed to have.

# Load package
library("flexsurv")
#> Loading required package: survival

# Run flexsurvreg with data = ovarian
fitw <- flexsurvreg(formula = Surv(futime, fustat) ~ factor(rx) + age,
                    data = ovarian, dist="weibull")

# Look at first observation in ovarian
ovarian[1, ]
#>   futime fustat     age resid.ds rx ecog.ps
#> 1     59      1 72.3315        2  1       1

# With the following from the survival object, the data could be re-created
fitw$data$Y[1, ]
#>   time status  start   stop  time1  time2 
#>     59      1      0     59     59    Inf
fitw$data$m[1, ]
#>   Surv(futime, fustat) factor(rx)     age (weights)
#> 1                   59          1 72.3315         1


Potential solution

We could write the code so that it also sets all those data that might be used for this back-engineering to NA as follows:

# Setting all survival object observation to NA
fitw$data$Y <- NA
fitw$data$m <- NA
fitw$data$mml$scale <- NA
fitw$data$mml$rate <- NA
fitw$data$mml$mu <- NA

Created on 2021-08-27 by the reprex package (v2.0.0)


Question

If I proceed as the above and set all these parameters to NA, could I then receive the fitw object (e.g. as an .RDS file) without ever being able to "back-engineer" the original data? Or is there any other way to share fitw without the attached data?

Thanks!

ANSWER

Answered 2022-Mar-29 at 11:01

Setting, e.g. fitw$data <- NULL will remove all the individual-level data from the fitted model object. Some of the output functions may not work with objects stripped of data however. In the current development version on github, printing the model object should work. Also summary and predict methods should work, as long as covariate values are supplied in newdata - omitting them won't work, since the default is to take the covariate values from the observed data.

Source https://stackoverflow.com/questions/68955039

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Bilibili-Evolved

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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