lmPlot: Two diagnostic plots for checking p-value influencers

In reverseR: Linear Regression Stability to Significance Reversal

Two diagnostic plots for checking p-value influencers

Description

Two different plot types that visualize p-value influencers.

1. inflPlot: plots the linear regression, marks the reverser(s) in darkred and displays trend lines for the full and leave-reversers-out data set (black and darkred, respectively).
2. pvalPlot: plots the p-values for each leave-one-out data point and displays the (log) p-values as an index plot with reverser points in darkred, together with the \alpha-border as defined in lmInfl and the original models' p-value.

Usage

inflPlot(infl, measure, ...) 
pvalPlot(infl, ...) 

Arguments

infl	an object obtained from lmInfl.
measure	which influence measure to use, see 'Details'.
...	other plotting parameters.

Details

The influence measure's to use are those listed in lmInfl, with the following syntax:
"dfb.Slope", "dffit", "cov.r", "cook.d", "hat", "sR", "hadi", "cdr", "Si".

Value

The corresponding plot.

Author(s)

Andrej-Nikolai Spiess

References

Regression diagnostics: Identifying influential data and sources of collinearity.
Belsley DA, Kuh E, Welsch RE.
John Wiley, New York (2004).

Applied Regression Analysis: A Research Tool.
Rawlings JO, Pantula SG, Dickey DA.
Springer; 2nd Corrected ed. 1998. Corr. 2nd printing 2001.

Applied Regression Analysis and Generalized Linear Models.
Fox J.
SAGE Publishing, 3rd ed, 2016.

Residuals and Influence in Regression.
Cook RD & Weisberg S.
Chapman & Hall, 1st ed, New York, USA (1982).

Examples

set.seed(123)
a <- 1:20
b <- 5 + 0.08 * a + rnorm(20, 0, 1)
LM1 <- lm(b ~ a)
res1 <- lmInfl(LM1) 
inflPlot(res1)
pvalPlot(res1)

reverseR documentation built on Sept. 12, 2024, 7:32 a.m.