missTally

This is a handy helper function that can be used in PRO scoring
functions to determine the number (or proportion) of item responses that
are missing (or valid) for each row in a data frame of items. This is used
by <code>scoreScale</code> to help determine if a respondent has answered enough
items to be assigned a prorated scale score.

Provides a reliable and flexible toolbox to score
patient-reported outcome (PRO), Quality of Life (QOL), and other
psychometric measures. The guiding philosophy is that scoring errors can
be eliminated by using a limited number of well-tested, well-behaved
functions to score PRO-like measures. The workhorse of the package is
the 'scoreScale' function, which can be used to score most single-scale
measures. It can reverse code items that need to be reversed before
scoring and pro-rate scores for missing item data. Currently, three
different types of scores can be output: summed item scores, mean item
scores, and scores scaled to range from 0 to 100. The 'PROscorerTools'
functions can be used to write new functions that score more complex
measures. In fact, 'PROscorerTools' functions are the building blocks of
the scoring functions in the 'PROscorer' package (which is a repository
of functions that score specific commonly-used instruments). Users are
encouraged to use 'PROscorerTools' to write scoring functions for their
favorite PRO-like instruments, and to submit these functions for
inclusion in 'PROscorer' (a tutorial vignette will be added soon). The
long-term vision for the 'PROscorerTools' and 'PROscorer' packages is to
provide an easy-to-use system to facilitate the incorporation of PRO
measures into research studies in a scientifically rigorous and
reproducible manner. These packages and their vignettes are intended to
help establish and promote "best practices" for scoring and describing
PRO-like measures in research.

Ray Baser

PROscorerTools

Tools to Score Patient-Reported Outcome (PRO) and Other
Psychometric Measures

missTally function

<dl><dt>dfItems</dt>
<dd>A data frame containing only the items of interest.</dd>
<dt>what</dt>
<dd>One of four quoted names indicating the value you want for each
respondent (row) in <code>dfItems</code>: (1) <code>"pmiss"</code> (the default), for the
proportion of items that are missing; (2) <code>"nmiss"</code>, for the number of items
that are missing; (3) <code>"pvalid"</code>, for the proportion of items that are valid,
non-missing; and (4) <code>"nvalid"</code> for the number of items that are valid,
non-missing.</dd></dl>

Arguments

Determine the number (or proportion) of missing (or non-missing) items
for each respondent — missTally

<dl>

<dt>dfItems</dt>
<dd>A data frame containing only the items of interest.</dd>


<dt>what</dt>
<dd>One of four quoted names indicating the value you want for each
respondent (row) in <code>dfItems</code>: (1) <code>"pmiss"</code> (the default), for the
proportion of items that are missing; (2) <code>"nmiss"</code>, for the number of items
that are missing; (3) <code>"pvalid"</code>, for the proportion of items that are valid,
non-missing; and (4) <code>"nvalid"</code> for the number of items that are valid,
non-missing.</dd>

</dl>

missTally: Determine the number (or proportion) of missing (or non-missing) items for each respondent

Description

Usage

Value

Arguments

Examples