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README.Rmd
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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, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
[](https://cran.r-project.org/package=PROscorer)
<!-- [](https://codecov.io/github/raybaser/PROscorer?branch=master) -->
[](https://app.codecov.io/gh/raybaser/PROscorer?branch=master)
# PROscorer README
## Overview
The *PROscorer* package is an extensible repository of functions to score
specific patient-reported outcome (PRO), quality of life (QoL), and other
psychometric measures and questionnaire-based instruments commonly used in
research.
(Note: For simplicity, from here forward I will collectively and somewhat
imprecisely refer to these types of instruments as "PRO measures", "PRO-like
instruments", or just "PROs".)
*PROscorer* is intended to standardize scoring procedures for PRO measures
across studies, to promote best practices for scoring PRO-like instruments, and
to improve the reproducibility of research with PRO-like instruments by
providing accurate, up-to-date, and well-documented PRO scoring functions that
can easily be integrated into scientifically reproducible workflows.
Each function in the *PROscorer* package scores a different PRO measure.
Functions are named using the initials of the PRO measure. For example, the
`fsfi` function scores the Female Sexual Function Index (FSFI).
*PROscorer* also comes with a vignette containing detailed descriptions of each
of the instruments scored by PROscorer (see main
[PROscorer](https://CRAN.R-project.org/package=PROscorer) page on CRAN). The
purpose of including these instrument descriptions, complete with references, is
to help improve the descriptions of PRO measures in protocols, grants, and
published results. In most cases, the descriptions can be used in research
documents with little or no editing.
To minimize the possibility of scoring errors and other bugs, each *PROscorer*
function is composed of simpler, well-tested "helper" functions from the
[PROscorerTools](https://CRAN.R-project.org/package=PROscorerTools) package.
This reliance on a small set of simple functions that have been thoroughly
tested ensures that the underlying code base of *PROscorer* functions is
bug-free, and that the scoring functions produce reliable, consistent, and
accurate results.
*PROscorer*, together with the *PROscorerTools* package, is a system to
facilitate the incorporation of PRO measures into research studies and clinical
settings in a scientifically rigorous and reproducible manner. The overarching
goals of the *PROscorer* and *PROscorerTools* packages are to draw attention to
PRO scoring and reporting best-practices and to help eliminate inaccurate and
inconsistent scoring.
The current version is still somewhat developmental, since the formal unit
testing system is still immature for some functions, and not yet in place for
others. Please use with caution at this time, and feel free to contact me with
questions or suggestions. More scoring functions are currently in development
and will be added in future updates, including more functions for the EORTC
family of PRO measures.
## Installation and Usage
Install the stable version of PROscorer from CRAN:
```{r eval=FALSE}
install.packages("PROscorer")
```
Load PROscorer into your R workspace with the following:
```{r eval=FALSE, message = FALSE}
library(PROscorer)
```
As an example, we will use the `makeFakeData` function from the PROscorerTools
package to make fake item responses to the EORTC QLQ-C30 quality of life
questionnaire. The created data set (named "dat") has an "id" variable, plus
responses to 30 items (named "q1", "q2", etc.) from 20 imaginary respondents.
There are also missing responses ("NA") scattered throughout.
```{r eval=FALSE}
dat <- PROscorerTools::makeFakeData(n = 20, nitems = 30, values = 1:4, id = TRUE)
dat
```
Below we will use the `qlq_c30` function to score the fake responses in "dat".
We will save the scores from the EORTC QLQ-C30 questionnaire in a data frame
named "c30scores".
```{r eval=FALSE}
c30scores <- qlq_c30(dat, 'q')
c30scores
```
The first argument to `qlq_c30` took our data frame, "dat". With the second
argument, we needed to tell the `qlq_c30` function how to find our items in
"dat". Since our items are all named with the prefix "q" plus the item number,
we gave this quoted prefix to the second argument. These arguments actually
have names, but in most cases you don't have to explicitly use the names. Below
gives the same results, but explicitly uses the argument names.
```{r eval=FALSE}
c30scores <- qlq_c30(df = dat, iprefix = 'q')
c30scores
```
Specifically, the first argument is named `df` (for **d**ata **f**rame) and the
second is named `iprefix` (for **i**tem prefix).
If you want to merge your scores back into your main data frame with the item
responses, there are several different ways to do so. For example, assuming you
have not changed the order of `dat` or `dat_scored`, you can do the following:
```{r eval=FALSE} dat_scored <- data.frame(dat, c30scores) dat_scored ```
For more information on the `qlq_c30` function, you can access its "help" page
by typing `?qlq_c30` into R.
## Resources for More Information
* You can access the "help" page for "PROscorer" package by typing `?PROscorer`
into R.
* For more detailed information on 'PROscorer', including future development
plans, please see the Introduction to PROscorer vignette on the main
[PROscorer](https://CRAN.R-project.org/package=PROscorer) page on CRAN.
* You might find the [other PROscorer
vignettes](https://CRAN.R-project.org/package=PROscorer) helpful, too. You can
access them from the main
[PROscorer](https://CRAN.R-project.org/package=PROscorer) webpage on CRAN.
* The underlying code base of the
[PROscorer](https://CRAN.R-project.org/package=PROscorer) package is built from
functions from the [PROscorerTools
package](https://CRAN.R-project.org/package=PROscorerTools).
* If you need to score PRO measures from the the FACT (Functional Assessment of
Cancer Therapy) and FACIT (Functional Assessment of Chronic Illness Therapy)
family of measures, please see the [FACTscorer
package](https://github.com/raybaser/FACTscorer).
* If you have any feature requests, or you want to report bugs or other strange
behavior in *PROscorer*, please submit them to me on the [PROscorer
GitHub page](https://github.com/raybaser/PROscorer/issues).