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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# metamisc
<!-- badges: start -->
[](https://cran.r-project.org/package=metamisc)
[](https://cran.r-project.org/package=metamisc)
[](https://github.com/smartdata-analysis-and-statistics/metamisc/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
This is the official repository of the R package **metamisc**, which was developed to facilitate meta-analysis of diagnosis and prognosis research studies. The package includes functions for the following tasks:
* To develop and validate multivariable prediction models from datasets with clustering (de Jong et al., 2021)
* To summarize multiple estimates of prediction model discrimination and calibration performance (Debray et al., 2019)
* To evaluate funnel plot asymmetry (Debray et al., 2018)
## Installation
The `metamisc` package can be installed from CRAN as follows:
``` r
install.packages("metamisc")
```
You can install the development version of metamisc from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("smartdata-analysis-and-statistics/metamisc")
```
## JASP
A visual interface to the software has been implemented by JASP <https://jasp-stats.org/>
## References
de Jong VMT, Moons KGM, Eijkemans MJC, Riley RD, Debray TPA. Developing more generalizable prediction models from pooled studies and large clustered data sets. *Stat Med*. 2021 May 5;40(15):3533–59.
Debray TPA, Moons KGM, Riley RD. Detecting small-study effects and funnel plot asymmetry in meta-analysis of survival data: a comparison of new and existing tests. *Res Syn Meth*. 2018;9(1):41–50.
Debray TPA, Damen JAAG, Riley R, Snell KIE, Reitsma JB, Hooft L, et al. A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes. *Stat Methods Med Res*. 2019 Sep;28(9):2768–86.