# plot.mpt

From mpt v0.6-2
by Florian Wickelmaier

##### Diagnostic Plot for MPT Models

Plots MPT residuals against fitted values.

- Keywords
- models

##### Usage

```
# S3 method for mpt
plot(x, showNames = TRUE,
xlab = "Predicted response probabilities", ylab = "Deviance residuals",
…)
```# S3 method for mpt
residuals(object, type = c("deviance", "pearson"), …)

##### Arguments

- x, object
an object of class

`mpt`

, typically the result of a call to`mpt`

.- showNames
logical. Should the names of the residuals be plotted? Defaults to

`TRUE`

.- xlab, ylab
graphical parameters passed to plot.

- type
the type of residuals which should be returned; the alternatives are:

`"deviance"`

(default) and`"pearson"`

.- …
further arguments passed to or from other methods.

##### Details

The deviance residuals are plotted against the predicted response
probabilities. If `showNames`

is true, plotting symbols are the
names of the residuals.

##### Value

For `residuals`

, a named vector of residuals having as many elements as
response categories.

##### See Also

##### Examples

```
# NOT RUN {
## Compare two constrained MPT models
data(proact)
spec <- mptspec(
p1*q1*r1,
p1*q1*(1 - r1),
p1*(1 - q1)*r1,
(1 - p1) + p1*(1 - q1)*(1 - r1),
p2*q2*r2,
p2*q2*(1 - r2),
p2*(1 - q2)*r2,
(1 - p2) + p2*(1 - q2)*(1 - r2),
p3*q3*r3,
p3*q3*(1 - r3),
p3*(1 - q3)*r3,
(1 - p3) + p3*(1 - q3)*(1 - r3)
)
m1 <- mpt(update(spec, .restr = list(p2=p1, p3=p1)),
proact[proact$test == 1, ])
m2 <- mpt(update(spec, .restr = list(q2=q1, q3=q1)), m1$y)
par(mfrow = c(1, 2)) # residuals versus fitted values
plot(m1, main = "p constrained", ylim = c(-3, 3.5)) # good fit
plot(m2, main = "q constrained", ylim = c(-3, 3.5)) # bad fit
sum( resid(m1)^2 ) # likelihood ratio G2
sum( resid(m1, "pearson")^2 ) # Pearson X2
# }
```

*Documentation reproduced from package mpt, version 0.6-2, License: GPL (>= 2)*

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