summary.substitution: Create a Summary of a Substitution Model represented by a...

In florale/multilevelcoda: Estimate Bayesian Multilevel Models for Compositional Data

Create a Summary of a Substitution Model represented by a substitution object

Description

Create a Summary of a Substitution Model represented by a substitution object

Usage

## S3 method for class 'substitution'
summary(object, delta, to, from, ref, level, digits = 2, ...)

Arguments

object	A substitution class object.
delta	A integer, numeric value or vector indicating the desired delta at which substitution results should be summarised. Default to all delta available in the substitution object.
to	A character value or vector specifying the names of the compositional parts that were reallocated to in the model.
from	A character value or vector specifying the names of the compositional parts that were reallocated from in the model.
ref	Either a character value or vector (("grandmean" and/or "clustermean" or "users"), Default to all ref available in the substitution object.
level	A character string or vector ("between" and/or "within"). Default to all level available in the substitution object.
digits	A integer value used for number formatting. Default is 2.
...	generic argument, not in use.

Value

A summary of substitution object.

Mean	Posterior means.
CI_low and CI_high	95% credible intervals.
Delta	Amount substituted across compositional parts.
From	Compositional part that is substituted from.
To	Compositional parts that is substituted to.
Level	Level where changes in composition takes place. Either between or within.
Reference	Either grandmean, clustermean, or users.

Examples

if(requireNamespace("cmdstanr")){
  ## fit a model with compositional predictor at between and between-person levels
  m <- brmcoda(complr = complr(data = mcompd, sbp = sbp,
                               parts = c("TST", "WAKE", "MVPA", "LPA", "SB"),
                               idvar = "ID", total = 1440),
  formula = Stress ~ bilr1 + bilr2 + bilr3 + bilr4 +
    wilr1 + wilr2 + wilr3 + wilr4 + (1 | ID),
  chain = 1, iter = 500,
  backend = "cmdstanr")
  
  subm <- substitution(object = m, delta = 5)
  summary(subm)
}

florale/multilevelcoda documentation built on April 21, 2024, 9:44 a.m.