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

Compute an analysis of deviance table for one or more maximum likelihood conjoint measurement model fits.

1 2 |

`object, ...` |
objects of class |

`dispersion` |
the dispersion parameter for the fitting family. By default, it is obtained from the object(s) |

`test` |
a character string (partially) matching one of "Chisq", "F", or "Cp". See |

See `anova.glm`

for details. In brief, specifying a single object, results in the display of a sequential analysis of deviance table for that model. Specifying several objects, a table indicating the results of the likelihood ratio tests between successive models is displayed. The models must be nested and fit to the same data set. One can mix a `formula`

method model with a `glm`

model, but not more than one comparison between a pair of such models at a time.

An object of class "anova" inheriting from class "data.frame".

see section Warnings in `anova`

for warnings.

Kenneth Knoblauch

Ho, Y. H., Landy. M. S. and Maloney, L. T. (2008). Conjoint measurement of gloss and surface texture. *Psychological Science*, **19**, 196–204.

1 2 3 4 5 | ```
bg.add <- mlcm(BumpyGlossy)
bg.ind <- mlcm(BumpyGlossy, model = "ind", whichdim = 2)
bg.full <- mlcm(BumpyGlossy, model = "full")
anova(bg.ind, bg.add, bg.full, test = "Chisq")
``` |

```
Analysis of Deviance Table
Model 1: Resp ~ (B12 + B13 + B14 + B15) - 1
Model 2: Resp ~ (G12 + G13 + G14 + G15 + B12 + B13 + B14 + B15) - 1
Model 3: Resp ~ (G12.B11 + G13.B11 + G14.B11 + G15.B11 + G11.B12 + G12.B12 +
G13.B12 + G14.B12 + G15.B12 + G11.B13 + G12.B13 + G13.B13 +
G14.B13 + G15.B13 + G11.B14 + G12.B14 + G13.B14 + G14.B14 +
G15.B14 + G11.B15 + G12.B15 + G13.B15 + G14.B15 + G15.B15) -
1
Resid. Df Resid. Dev Df Deviance Pr(>Chi)
1 971 500.12
2 967 476.48 4 23.635 9.452e-05 ***
3 951 461.53 16 14.947 0.5285
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
```

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