R-package)In biomedical literature, the most widely employed statistical
procedure to analyze and visualize the association between two variables
is linear regression. Data points that exert influence on the fit and
its parameters are routinely, but not as often as required, identified
by established influence measures and their corresponding cut-off
values. In this R package, we specifically address the
presence of influential data points that directly impact the statistical
inference of the models, which none of the established measures detect,
such as
leverage
dffits
dfbeta(s)
covratio
Cook’s distance
studentized residuals
Hadi’s measure
We call these data points “reversers”.
reverseR tests linear regressions for significance reversal
through leave-one(multiple)-out and checking if \(\alpha \in [p_{\beta1}, p_{\beta1(i)}]\),
where \(p_{\beta1}\) is the
p-value of the regression’s slope and \(p_{\beta1(i)}\) is the p-value
with the i-th point deleted. This paradigm is along the lines
of the living-in-oblivion measure dfstat or dfstud
(Belsley, Kuh & Welsch, Regression diagnostics: Identifying
influential data and sources of collinearity, 2004) that checks the
impact of each response value on statistical inference.
The reverseR package requires only a standard computer
with enough RAM to support the operations defined by a user. For minimal
performance, this will be a computer with about 4 GB of RAM. For optimal
performance, we recommend a computer with the following specs: RAM: 16+
GB; CPU: 4+ Cores, 3.3+ GHz/Core.
R version greater than 3.5.0 for Linux Ubuntu 16,
Windows 7, 8, 10 or Mac.
Several CRAN packages may be needed.
Runtimes vary for the different functions:
lmInfl for “reverser” analysis: ~ 1-5 sec.
lmMult for multiple leave-out analysis: ~ 5-30 sec.
simInfl for Monte Carlo simulation: 5-600 sec.
Users should install the following packages prior to installing
reverseR, from an R terminal:
install.packages(c("markdown", "knitr"))From an R session, type:
if (!'devtools' %in% installed.packages()) install.packages(devtools)
devtools::install_github("anspiess/reverseR")
source("https://install-github.me/anspiess/reverseR")