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dosresmeta's Introduction

Multivariate Dose-Response Meta-Analysis (dosresmeta)

The package dosresmeta consists of a collection of functions to estimate dose-response relations from summarized dose-response data for both continuous and binary outcomes, and to combine them according to principles of (multivariate) random-effects model. The methodology is illustrated in the referenced article.

Info on the dosresmeta package

The package is available on the Comprehensive R Archive Network (CRAN), with info at the related web page (https://CRAN.R-project.org/package=dosresmeta). A development website is available on GitHub (https://github.com/alecri/dosresmeta).

For a short summary of the package, refer to the main help page by typing:

help("dosresmeta-package")

in R after installation (see below).

Installation

The last version officially released on CRAN can be installed directly within R by typing:

install.packages("dosresmeta")

A version still under developement is avaiable on GitHub and can be installed by typing:

install.packages("devtools")
devtools::install_github("alecri/dosresmeta")

R code in published articles

Several peer-reviewed articles and documents provide R code illustrating methodological developments or replicating substantive results. An updated version of the code can be found at the GitHub (https://github.com/alecri) or personal web page (https://alecri.github.io/software/dosresmeta.html) of the package maintainer.

References:

Crippa A, Orsini N. Multivariate Dose-Response Meta-Analysis: the dosresmeta R Package. Journal of Statistical Software, Code Snippets,. 2016; 72(1), 1-15. doi:10.18637/jss.v072.c01. [freely available here]

Crippa A, Orsini N. Dose-response meta-analysis of differences in means. BMC Medical Research Methodology. 2016 Aug 2;16(1):91. [freely available here] [GitHub repository at this link]

Discacciati A, Crippa A, Orsini N. Goodness of fit tools for dose-response meta-analysis of binary outcomes. Research Synthesis Methods. 2015 Jan 1. doi: 10.1002/jrsm.1194. [freely available here] [GitHub repository at this link]

dosresmeta's People

Contributors

alecri avatar

Stargazers

Valirie N. Agbor avatar Alex Johnson avatar louis_delamarre avatar JiamuXu avatar  avatar Zhenglei avatar MichaelJStein avatar Alex Fowler avatar Felipe Mattioni Maturana, Ph.D. avatar Chaochen Wang avatar Mahmoud Ahmed avatar Andrea Discacciati avatar

Watchers

James Cloos avatar Chaochen Wang avatar  avatar

Forkers

agampol

dosresmeta's Issues

A question about the logrr given in the data cc_ex

I'm trying to do a dose-response meta analysis. When I'm reproducing the code in the paper "Multivariate Dose-Response Meta-Analysis: The dosresmeta R Package" , I found that the logrr given in the data cc_ex didn't equal to the log10(adjrr). So, what's the meaning of logrr? What kind of effect size should I get from the papers to calculate it? This really bothers me and hinders the progress of the research, hope for your answer. Thank you!
截屏2022-06-30 15 34 51

dose-response of difference in means

Dear Dr. Crippa,

Thank you very much for your R package! I am currently trying to modify it to fit in my purposes. I am conducting a dose-response meta analysis in RCTs. Each RCT have two interventions, and I am looking at the change between pre- and post- intervention. Therefore, I have one data point for each intervention in each study. What would be the most appropriate way of using the one-stage approach to fit a dose-response curve of difference in means (pre vs post) for all the studies combined with your dosresmeta package?

Best,

Felipe

"Error in if (delta < tol) break" when meta-analysing multiple studies

Hello,
I'm using dosresmeta to conduct a meta-analysis of multiple studies. Here's some sample data:

example_data.csv

When I run the following code:
dosresmeta(formula = log(or) ~ dose, id = id, type = type, cases = cases, n = n, data = example_data, se = se)
R returns an error:
Warning: NaNs producedWarning: NaNs producedError in if (delta < tol) break : missing value where TRUE/FALSE needed
even though it doesn't look like there are any NAs in the dataset or any other visible issues.

Many thanks in advance for your help! I know how busy things must be.

Best wishes,
Yaning

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