BANOVA.model {BANOVA}

Extract BANOVA models

Description

BANOVA.model extracts BANOVA models from the package.

Usage

BANOVA.model(model_name, single_level = F)

Arguments

model_name

a character string in c('Normal', 'T', 'Bernoulli', 'Binomial', 'Poisson', 'ordMultinomial', 'Multinomial', 'multiNormal', 'truncNormal')

single_level

if the model is a single level model, default False

Details

The function loads a pre-specified 'Stan' model for the analysis in BANOVA.

'Normal' model: A model suitable for a continuous dependent variable, which follows a Normal distribution.

'T' model: A model suitable for a continuous dependent variable, which might be prone to 'outliers' or fatter tails than the Normal.

'Bernoulli' model: A model suitable for a binary dependent variable, which can take values 0 and 1.

'Binomial' model: A model suitable for a dependent variable, which represents a number of successes in a sequence of B independent Bernoulli experiments.

'Poisson' model: A model suitable for a dependent variable, which represents count data. A Poisson distributed dependent variable can take values 0, 1, 2 ....

'ordMultinomial' model: A model suitable for an ordered categorical (ordinal) dependent variable, which follows an ordered Multinomial distribution. This dependent variable can take values from 1 to K, where possible alternatives are ordered according to some principal.

'Multinomial' model: A model suitable for a categorical (nominal) dependent variable, which follows a Multinomial distribution. This dependent variable can take values from 1 to K, where possible alternatives are unordered.

'multiNormal' model: A model suitable for a Multivariate Normal dependent variable, which represents L possibly correlated Normal dependent variables with shared predictors. The analysis corresponds to the seemingly unrelated regressions (SUR) technique.

'truncNormal' model: A model suitable a dependent variable, which values can only be observed if they lie within a certain range. The variable can be bounded from below, above, or from two sides.

Value

BANOVA.model returns an object of class "BANOVA.model". The returned object is a list containing:

model_code

the model code of the extracted model

model_name

the model name

single_level

if the model is a single level model

Examples

model <- BANOVA.model('Poisson', single_level = FALSE) 
cat(model$model_code)