README.Rmd

---
output: github_document
bibliography: vignettes/references.bib
---

<!-- 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%"
)
```

# poset

The **poset** package provides simple and efficient statistical routines for partially ordered data, 
such as multivariate ordinal response under consensus or prioritized order.
The current version focuses on the win ratio/net benefit approach [@mao2024] via generalized 
pairwise comparisons [@buyse2010].

## Installation

Install **poset** from CRAN with:

``` r
install.packages("poset")
```

You can install the development version from GitHub with:

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

## Examples

Here is a basic example for two-sample testing and regression.

```{r example}
library(poset)
## data example
head(liver)
```

### Compare bivariate ratings by fibrosis stage 
```{r}
Y1 <- liver[liver$AF, c("R1NASH", "R2NASH")] # advanced
Y0 <- liver[!liver$AF, c("R1NASH", "R2NASH")] # not advanced
wrtest(Y1, Y0)
```


### Regression analysis

```{r}
Y <- 5 - liver[, c("R1NASH", "R2NASH")] # lower score is better
Z <- cbind("Female" = liver$Sex == "F",
           liver[, c("AF", "Steatosis",   "SSF2",  "LSN")]) # covariates
obj <- wreg(Y, Z) # fit model
obj
summary(obj)

```

## References