confinterpret

confinterpret R package

https://github.com/jimvine/confinterpret

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

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  • Academic publication links
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    1 of 2 committers (50.0%) from academic institutions
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    Low similarity (11.0%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

confinterpret R package

Basic Info
  • Host: GitHub
  • Owner: jimvine
  • Language: R
  • Default Branch: master
  • Size: 185 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 9 years ago · Last pushed 12 months ago
Metadata Files
Readme

README.md

confinterpret

<!-- badges: start --> R-CMD-check CRAN_Status_Badge <!-- badges: end -->

An R package for interpreting confidence intervals.

The goal of confinterpret is to allow users to produce standardised descriptive interpretations from confidence intervals in R. The package supports researchers to focus more on generating estimates with associated ranges of uncertainty, rather than on single point-estimates, such as are common when conclusions are drawn from p-values.

The package includes (extensible) support for various test types, which are specified as sets of interpretations dependent on where the lower and upper confidence limits sit.

A collection of interpretation_set objects are provided in the package, to cover certain common situations where the confidence interval is of an effect size comparing two groups. Convenience / wrapper functions are provided for using each of these:

  • Superiority tests: interpret_superiority()
  • Non-inferiority tests: interpret_noninferiority()
  • Equivalence tests: interpret_equivalence()

Installation

confinterpret is on CRAN, so you can install it in the normal way:

R install.packages("confinterpret")

You can also install the development version of confinterpret from github with:

```R

install.packages("devtools")

devtools::install_github("jimvine/confinterpret") ```

Example

This is a basic example which shows you how to solve a common problem:

```R

Set up a dummy confidence interval

ci_above <- matrix(c(0.15, 0.25), nrow = 1, dimnames = list("estimate", c("2.5 %","97.5 %")))

ciabovesup <- interpretsuperiority(ciabove)

Access the short-form interpretation:

ciabovesup$interpretation_short

Access the full interpretation:

ciabovesup$interpretation

Access the full interpretation, marked up with markdown:

ciabovesup$interpretation_md

Plot a chart of the interpretation (specify a nice colour-scheme first):

grDevices::palette(c("#FF671F99", "#F2A90099", "#0085CA99")) plot(ciabovesup) ```

Owner

  • Name: Jim Vine
  • Login: jimvine
  • Kind: user
  • Location: Essex, UK
  • Company: University of Essex

GitHub Events

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Committers

Last synced: over 2 years ago

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  • Total Commits: 94
  • Total Committers: 2
  • Avg Commits per committer: 47.0
  • Development Distribution Score (DDS): 0.096
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  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Jim Vine c****e@j****k 85
Vine j****1@e****k 9
Committer Domains (Top 20 + Academic)

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Last synced: 10 months ago

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  • Average comments per issue: 0
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 251 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 3
  • Total maintainers: 1
cran.r-project.org: confinterpret

Descriptive Interpretations of Confidence Intervals

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 251 Last month
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 36.7%
Downloads: 54.4%
Maintainers (1)
Last synced: 10 months ago

Dependencies

DESCRIPTION cran
  • RColorBrewer * suggests
  • captioner * suggests
  • grDevices * suggests
  • graphics * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests