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scdtb

Single Case Design Toolbox

https://github.com/mightymetrika/scdtb

Science Score: 13.0%

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

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.3%) to scientific vocabulary

Keywords

data math r science statistics
Last synced: 10 months ago · JSON representation

Repository

Single Case Design Toolbox

Basic Info
  • Host: GitHub
  • Owner: mightymetrika
  • License: other
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 1.87 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 1
Topics
data math r science statistics
Created over 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.Rmd 

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# scdtb




The goal of 'scdtb' is to provide tools for the analysis of single case design data.

## Installation

You can install the released version of 'scdtb' from [CRAN](https://CRAN.R-project.org):

```{r eval=FALSE}
install.packages("scdtb")
```

To install the development version of 'scdtb' from GitHub, use the [devtools](https://devtools.r-lib.org/) package:

```{r, eval=FALSE}
# install.packages("devtools")
devtools::install_github("mightymetrika/scdtb")
```


## Analyze Your Data

Use the scdtb() function to launch a 'shiny' application which implements many of the tools in the 'scdtb' package.

The application has the following functionalities:

* Upload a CSV file to be used as the dataset for modeling.
* View the variables available in the uploaded dataset.
* Enter the roles played by the variables in the dataset.
* Create a raw plot of the data.
* Run a mixed effect model.
* Run a crossed lag correlation analysis.
* Run a non-overlap of all pairs computation.
* Run a randomization test.

```{r, eval=FALSE}
library(scdtb)

# Launch application
scdtb()
```

Owner

  • Login: mightymetrika
  • Kind: user

GitHub Events

Total
Last Year

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 2
  • Total pull requests: 36
  • Average time to close issues: 2 months
  • Average time to close pull requests: 1 minute
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 36
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 36
  • Average time to close issues: 2 months
  • Average time to close pull requests: 1 minute
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 36
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • mightymetrika (2)
  • mncube (1)
Pull Request Authors
  • mncube (60)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 179 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: scdtb

Single Case Design Tools

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 179 Last month
Rankings
Dependent packages count: 27.8%
Dependent repos count: 35.7%
Average: 49.5%
Downloads: 84.9%
Maintainers (1)
macksonncube.stats@gmail.com
Last synced: 10 months ago

Dependencies

DESCRIPTION cran
  • R >= 2.10 depends
  • ggplot2 * imports
  • nlme * imports
  • testthat >= 3.0.0 suggests