R: Analysis of variance with a count variable

Analysis of variance with a count variable {Rfast} | R Documentation

## Analysis of variance with a count variable

### Description

Analysis of variance with a count variable.

### Usage

    poisson.anova(y, ina, logged = FALSE)
    geom.anova(y, ina, type = 1, logged = FALSE)
    quasipoisson.anova(y, ina, logged = FALSE)

### Arguments

`y` | A numerical vector with discrete valued data, i.e. counts.
`ina` | A numerical vector with discrete numbers starting from 1, i.e. 1, 2, 3, 4,... or a factor variable. This is suppose to be a categorical predictor. If you supply a continuous valued vector the function will obviously provide wrong results.
`type` | This argument is for the geometric distribution. Type 1 refers to the case where the minimum is zero and type 2 for the case of the minimum being 1.
`logged` | Should the p-values be returned (FALSE) or their logarithm (TRUE)?

### Details

This is the analysis of variance with Poisson or geometric distributed data. What we do is a log-likelihood ratio test. However, this is exactly the same as Poisson regression with a single predictor variable who happens to be categorical. Needless to say that this is faster function than the glm command in R. For the same purpose with a Bernoulli variable use `g2Test`. The quasinpoisson.anova is when in the glm function you specify family = quasipoisson. This is suitable for the case of over or under-dispersed data.

### Value

A vector with two values, the difference in the deviances (or the scale difference in the case of quasi poisson) and the relevant p-value. The quasipoisson.anova also returns the estimate of the φ parameter.

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr> and Manos Papadakis <papadakm95@gmail.com>.

### See Also

`logistic.cat1, g2Test, poisson.anovas, anova, poisson_only, poisson.mle`

### Examples

    y <- rpois(300, 10)
    ina <- rbinom(300, 3, 0.5) + 1
    a1 <- poisson.anova(y, ina)
    a2 <- glm(y ~ ina, poisson)

    ## Not run:
    res<-anova(a2, test = "Chisq")

    ## End(Not run)
    y <- rgeom(300, 0.7)
    res<-geom.anova(y, ina)

[Package Rfast version 2.0.4 Index]