Description Usage Arguments Details Value Author(s) See Also Examples

Try fitting all models that differ from the current model by adding or deleting a single term from those supplied while maintaining marginality.

1 2 3 4 5 6 7 8 | ```
## S3 method for class 'clm2'
addterm(object, scope, scale = 0, test = c("none", "Chisq"),
k = 2, sorted = FALSE, trace = FALSE,
which = c("location", "scale"), ...)
## S3 method for class 'clm2'
dropterm(object, scope, scale = 0, test = c("none", "Chisq"),
k = 2, sorted = FALSE, trace = FALSE,
which = c("location", "scale"), ...)
``` |

`object` |
A |

`scope` |
for |

`scale` |
used in the definition of the AIC statistic for selecting the
models. Specifying |

`test` |
should the results include a test statistic relative to the original model? The Chisq test is a likelihood-ratio test. |

`k` |
the multiple of the number of degrees of freedom used for the penalty.
Only |

`sorted` |
should the results be sorted on the value of AIC? |

`trace` |
if |

`which` |
should additions or deletions occur in location or scale models? |

`...` |
arguments passed to or from other methods. |

The definition of AIC is only up to an additive constant because the likelihood function is only defined up to an additive constant.

A table of class `"anova"`

containing columns for the change
in degrees of freedom, AIC and the likelihood ratio statistic. If
`test = "Chisq"`

a column also contains the
p-value from the Chisq test.

Rune Haubo B Christensen

`clm2`

, `anova`

,
`addterm.default`

and `dropterm.default`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
options(contrasts = c("contr.treatment", "contr.poly"))
if(require(MASS)) { ## dropterm, addterm, housing
mB1 <- clm2(SURENESS ~ PROD + GENDER + SOUPTYPE,
scale = ~ COLD, data = soup, link = "probit",
Hess = FALSE)
dropterm(mB1, test = "Chi") # or
dropterm(mB1, which = "location", test = "Chi")
dropterm(mB1, which = "scale", test = "Chi")
addterm(mB1, scope = ~.^2, test = "Chi", which = "location")
addterm(mB1, scope = ~ . + GENDER + SOUPTYPE,
test = "Chi", which = "scale")
addterm(mB1, scope = ~ . + AGEGROUP + SOUPFREQ,
test = "Chi", which = "location")
## Fit model from polr example:
fm1 <- clm2(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
addterm(fm1, ~ Infl + Type + Cont, test= "Chisq", which = "scale")
dropterm(fm1, test = "Chisq")
}
``` |

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