The `estmeansd`

package implements the methods of McGrath et al. (2020) for estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Specifically, these methods can be applied to studies that report one of the following sets of summary statistics:

- S1: median, minimum and maximum values, and sample size
- S2: median, first and third quartiles, and sample size
- S3: median, minimum and maximum values, first and third quartiles, and sample size

Additionally, the Shiny app estmeansd implements these methods.

## Installation

You can install the released version of `estmeansd`

from CRAN with:

`install.packages("estmeansd")`

After installing the `devtools`

package (i.e., calling `install.packages(devtools)`

), the development version of `estmeansd`

can be installed from GitHub with:

`devtools::install_github("stmcg/estmeansd")`

## Usage

Specifically, this package implements the Box-Cox (BC) and Quantile Estimation (QE) methods to estimate the sample mean and standard deviation. The BC and QE methods can be applied using the `bc.mean.sd()`

and `qe.mean.sd()`

functions, respectively:

```
library(estmeansd)
set.seed(1)
bc.mean.sd(min.val = 2, med.val = 4, max.val = 9, n = 100) # BC Method
#> $est.mean
#> [1] 4.210971
#>
#> $est.sd
#> [1] 1.337348
qe.mean.sd(min.val = 2, med.val = 4, max.val = 9, n = 100) # QE Method
#> $est.mean
#> [1] 4.347284
#>
#> $est.sd
#> [1] 1.502171
```