# infIndexPlot

##### Influence Index Plot

Provides index plots of influence and related diagnostics for a regression model.

- Keywords
- regression, hplot

##### Usage

`infIndexPlot(model, ...)`influenceIndexPlot(model, ...)

# S3 method for lm
infIndexPlot(model, vars=c("Cook", "Studentized", "Bonf", "hat"),
id=TRUE, grid=TRUE, main="Diagnostic Plots", ...)

# S3 method for influence.merMod
infIndexPlot(model,
vars = c("dfbeta", "dfbetas", "var.cov.comps",
"cookd"), id = TRUE, grid = TRUE, main = "Diagnostic Plots", ...)
# S3 method for influence.lme
infIndexPlot(model,
vars = c("dfbeta", "dfbetas", "var.cov.comps",
"cookd"), id = TRUE, grid = TRUE, main = "Diagnostic Plots", ...)

##### Arguments

- model
A regression object of class

`lm`

,`glm`

, or`lmerMod`

, or an influence object for a`lmer`

,`glmer`

, or`lme`

object (see`influence.mixed.models`

). The`"lmerMod"`

method calls the`"lm"`

method and can take the same arguments.- vars
All the quantities listed in this argument are plotted. Use

`"Cook"`

for Cook's distances,`"Studentized"`

for Studentized residuals,`"Bonf"`

for Bonferroni p-values for an outlier test, and and`"hat"`

for hat-values (or leverages) for a linear or generalized linear model, or`"dfbeta"`

,`"dfbetas"`

,`"var.cov.comps"`

, and`"cookd"`

for an influence object derived from a mixed model. Capitalization is optional. All but`"dfbeta"`

and`"dfbetas"`

may be abbreviated by the first one or more letters.- main
main title for graph

- id
a list of named values controlling point labelling. The default,

`TRUE`

, is equivalent to`id=list(method="y", n=2, cex=1, col=carPalette()[1], location="lr")`

;`FALSE`

suppresses point labelling. See`showLabels`

for details.- grid
If TRUE, the default, a light-gray background grid is put on the graph.

- …
Arguments passed to

`plot`

##### Value

Used for its side effect of producing a graph. Produces index plots of diagnostic quantities.

##### References

Cook, R. D. and Weisberg, S. (1999)
*Applied Regression, Including Computing and Graphics.* Wiley.

Fox, J. (2016)
*Applied Regression Analysis and Generalized Linear Models*,
Third Edition. Sage.
Fox, J. and Weisberg, S. (2019)
*An R Companion to Applied Regression*, Third Edition, Sage.

Weisberg, S. (2014)
*Applied Linear Regression*, Fourth Edition, Wiley.

##### See Also

`cooks.distance`

, `rstudent`

,
`outlierTest`

, `hatvalues`

, `influence.mixed.models`

.

##### Examples

```
# NOT RUN {
influenceIndexPlot(lm(prestige ~ income + education + type, Duncan))
# }
```

*Documentation reproduced from package car, version 3.0-5, License: GPL (>= 2)*