partial.resid.plot {asbio} R Documentation

## Partial residual plots for interpretation of multiple regression.

### Description

The function creates partial residual plots which help a user graphically determine the effect of a single predictor with respect to all other predictors in a multiple regression model.

### Usage

```partial.resid.plot(x, smooth.span = 0.8, lf.col = 2, sm.col = 4,...)
```

### Arguments

 `x` A output object of class `lm` or class `glm` `smooth.span` Degree of smoothing for smoothing line. `lf.col` Color for linear fit. `sm.col` Color for smoother fit. `...` Additional arguments from `plot`.

### Details

Creates partial residual plots (see Kutner et al. 2002). Smoother lines from `lowess` and linear fits from `lm` are imposed over plots to help an investigator determine the effect of a particular X variable on Y with all other variables in the model. The function automatically inserts explanatory variable names on axes.

### Value

Returns p partial residual plots, where p = the number of explanatory variables.

Ken Aho

### References

Kutner, M. H., Nachtsheim, C. J., Neter, J., and W. Li. (2005) Applied Linear Statistical Models, 5th edition. McGraw-Hill, Boston.

`partial.R2`

### Examples

```Soil.C<-c(13,20,10,11,2,25,30,25,23)
Soil.N<-c(1.2,2,1.5,1,0.3,2,3,2.7,2.5)
Slope<-c(15,14,16,12,10,18,25,24,20)
Aspect<-c(45,120,100,56,5,20,5,15,15)
Y<-c(20,30,10,15,5,45,60,55,45)
x <- lm(Y ~ Soil.N + Soil.C + Slope + Aspect)
op <- par(mfrow=c(2,2),mar=c(5,4,1,1.5))
partial.resid.plot(x)
par(op)
```

[Package asbio version 1.7 Index]