aod: Interfaces for aod package for data science pipelines.

In rbertolusso/intubate: Interface to Popular R Functions for Data Science Pipelines

Description

Interfaces to aod functions that can be used in a pipeline implemented by magrittr.

Usage

ntbt_betabin(data, ...)
ntbt_donner(data, ...)
ntbt_negbin(data, ...)
ntbt_quasibin(data, ...)
ntbt_quasipois(data, ...)
ntbt_raoscott(data, ...)
ntbt_splitbin(data, ...)

Arguments

data	data frame, tibble, list, ...
...	Other arguments passed to the corresponding interfaced function.

Details

Interfaces call their corresponding interfaced function.

Value

Object returned by interfaced function.

Author(s)

Roberto Bertolusso

Examples

## Not run: 
library(intubate)
library(magrittr)
library(aod)


## ntbt_betabin: beta-binomial generalized linear model accounting
##               for overdispersion in clustered binomial data (n, y)
data(orob2)
## Original function to interface
betabin(cbind(y, n - y) ~ seed, ~ 1, data = orob2)

## The interface puts data as first parameter
ntbt_betabin(orob2, cbind(y, n - y) ~ seed, ~ 1)

## so it can be used easily in a pipeline.
orob2 %>%
  ntbt_betabin(cbind(y, n - y) ~ seed, ~ 1)


## ntbt_donner: Test of Proportion Homogeneity using Donner's Adjustment
data(rats)

## Original function to interface
donner(formula = cbind(y, n - y) ~ group, data = rats)

## The interface puts data as first parameter
ntbt_donner(rats, formula = cbind(y, n - y) ~ group)

## so it can be used easily in a pipeline.
rats %>%
  ntbt_donner(formula = cbind(y, n - y) ~ group)


## ntbt_negbin: negative-binomial log linear model accounting
##              for overdispersion in counts y
data(salmonella)
## Original function to interface
negbin(y ~ log(dose + 10) + dose, ~ 1, salmonella)

## The interface puts data as first parameter
ntbt_negbin(salmonella, y ~ log(dose + 10) + dose, ~ 1)

## so it can be used easily in a pipeline.
salmonella %>%
  ntbt_negbin(y ~ log(dose + 10) + dose, ~ 1)


## ntbt_quasibin: Quasi-Likelihood Model for Proportions
data(orob2) 
## Original function to interface
quasibin(cbind(y, n - y) ~ seed * root, data = orob2, phi = 0) 

## The interface puts data as first parameter
ntbt_quasibin(orob2, cbind(y, n - y) ~ seed * root, phi = 0)

## so it can be used easily in a pipeline.
orob2 %>%
  ntbt_quasibin(cbind(y, n - y) ~ seed * root, phi = 0)


## ntbt_quasipois: Quasi-Likelihood Model for Counts
data(salmonella)

## Original function to interface
quasipois(y ~ log(dose + 10) + dose, data = salmonella)

## The interface puts data as first parameter
ntbt_quasipois(salmonella, y ~ log(dose + 10) + dose)

## so it can be used easily in a pipeline.
salmonella %>%
  ntbt_quasipois(y ~ log(dose + 10) + dose)


## ntbt_raoscott: Test of Proportion Homogeneity using Rao and Scott's Adjustment
data(rats)

## Original function to interface
raoscott(cbind(y, n - y) ~ group, data = rats)

## The interface puts data as first parameter
ntbt_raoscott(rats, cbind(y, n - y) ~ group)

## so it can be used easily in a pipeline.
rats %>%
  ntbt_raoscott(cbind(y, n - y) ~ group)


## ntbt_splitbin: Split Grouped Data Into Individual Data
mydata <- data.frame(
    success = c(0, 1, 0, 1),
    f1 = c("A", "A", "B", "B"),
    f2 = c("C", "D", "C", "D"),
    n = c(4, 2, 1, 3)
    )
## Original function to interface
splitbin(formula = n ~ f1 + f2 + success, data = mydata)

## The interface puts data as first parameter
ntbt_splitbin(mydata, formula = n ~ f1 + f2 + success)

## so it can be used easily in a pipeline.
mydata %>%
  ntbt_splitbin(formula = n ~ f1 + f2 + success)

## End(Not run)

rbertolusso/intubate documentation built on May 27, 2019, 3 a.m.