vaso

<p>A binary data on the neural constriction of vasculature. Three test persons
inhaled a certain amount of air with different rates. In some cases a
vasoconstriction occurred at their skin. The objective of the study was to
indicate a correlation between breathing and vasoconstriction.
The test persons repeated the test 9, 8, 22 times, making a total of
39 observations.</p>

dataset

A post-estimation method for categorical response models (CRM).
Inputs from objects of class serp(), clm(), polr(), multinom(), mlogit(),
vglm() and glm() are currently supported. Available tests include the
Hosmer-Lemeshow tests for the binary, multinomial and ordinal logistic
regression; the Lipsitz and the Pulkstenis-Robinson tests for the ordinal
models. The proportional odds, adjacent-category, and constrained continuation-ratio
models are particularly supported at ordinal level. Tests for the proportional
odds assumptions in ordinal models are also possible with the Brant and the
Likelihood-Ratio tests. Moreover, several summary measures of predictive strength
(Pseudo R-squared), and some useful error metrics, including, the brier
score, misclassification rate and logloss are also available for the
binary, multinomial and ordinal models. Ugba, E. R. and Gertheiss, J. (2018)
<http://www.statmod.org/workshops_archive_proceedings_2018.html>.

Ejike Ugba

gofcat

Goodness-of-Fit Measures for Categorical Response Models

Ejike R. Ugba

vaso function

<p>A data frame with 39 observations on the following 3 variables:
- vol: amount of air
- rate: rate of breathing
- vaso: condition of vasculature: no vasoconstriction = 1, vasoconstriction = 2</p>

vaso: Vasoconstriction and Breathing

Description

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References

See Also