Package: KernSmoothIRT 6.6
Brian McGuire
KernSmoothIRT: Nonparametric Item Response Theory
Fits nonparametric item and option characteristic curves using kernel smoothing. It allows for optimal selection of the smoothing bandwidth using cross-validation and a variety of exploratory plotting tools. The kernel smoothing is based on methods described in Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.
Authors:
KernSmoothIRT_6.6.tar.gz
KernSmoothIRT_6.6.zip(r-4.7-x86_64)KernSmoothIRT_6.6.zip(r-4.7-arm64)
KernSmoothIRT_6.6.tar.gz(r-4.7-arm64)KernSmoothIRT_6.6.tar.gz(r-4.7-x86_64)KernSmoothIRT_6.6.tar.gz(r-4.6-arm64)KernSmoothIRT_6.6.tar.gz(r-4.6-x86_64)
KernSmoothIRT_6.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
KernSmoothIRT/json (API)
| # Install 'KernSmoothIRT' in R: |
| install.packages('KernSmoothIRT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- BDIkey - The Beck Depression Inventory Data
- BDIkey - The Beck Depression Inventory Data
- BDIresponses - The Beck Depression Inventory Data
- BDIresponses - The Beck Depression Inventory Data
- HIV - The HIV Data
- HIV - The HIV Data
- HIVkey - The HIV Data
- HIVkey - The HIV Data
- Psychkey - The Introductory Psychology Data
- Psychkey - The Introductory Psychology Data
- Psychresponses - The Introductory Psychology Data
- Psychresponses - The Introductory Psychology Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:b73256d9f0. Checks:8 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 110 | ||
| linux-devel-x86_64 | OK | 141 | ||
| source / vignettes | OK | 203 | ||
| linux-release-arm64 | OK | 108 | ||
| linux-release-x86_64 | OK | 119 | ||
| windows-devel-arm64 | OK | 212 | ||
| windows-devel-x86_64 | OK | 143 | ||
| wasm-release | OK | 145 |
Exports:itemcorksIRTPCAplot.ksIRTprint.ksIRTsubjEISsubjEISDIFsubjETSsubjETSDIFsubjOCCsubjOCCDIFsubjscoresubjscoreMLsubjthetaML
Dependencies:base64encbslibcachemclidigestevaluatefastmapfontawesomefshighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlifecyclemagrittrmemoisemimeplotrixR6rappdirsRcpprglrlangrmarkdownsasstinytexxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| KernSmoothIRT Package | KernSmoothIRT |
| The Beck Depression Inventory Data | BDI BDIkey BDIresponses |
| The HIV Data | HIV HIVkey |
| ksIRT - kernel smoothing in Item Response Theory | itemcor |
| ksIRT - kernel smoothing in Item Response Theory | ksIRT print.ksIRT |
| ksIRT - kernel smoothing in Item Response Theory | PCA |
| Plot Method for ksIRT - kernel smoothing in Item Response Theory | plot plot.ksIRT |
| The Introductory Psychology Data | Psych101 Psychkey Psychresponses |
| ksIRT - kernel smoothing in Item Response Theory | subjEIS |
| ksIRT - kernel smoothing in Item Response Theory | subjEISDIF |
| ksIRT - kernel smoothing in Item Response Theory | subjETS |
| ksIRT - kernel smoothing in Item Response Theory | subjETSDIF |
| ksIRT - kernel smoothing in Item Response Theory | subjOCC |
| ksIRT - kernel smoothing in Item Response Theory | subjOCCDIF |
| ksIRT - kernel smoothing in Item Response Theory | subjscore |
| ksIRT - kernel smoothing in Item Response Theory | subjscoreML |
| ksIRT - kernel smoothing in Item Response Theory | subjthetaML |
