plot_delta_comp: Get predictions from compositional ilr multiple linear...

In tystan/deltacomp: Functions to Analyse Compositional Data and Produce Confidence Intervals for Relative Increases and Decreases in the Compositional Components

Get predictions from compositional ilr multiple linear regression model

Description

Provided the data (containing outcome, composiitional compoents and covariates), fit a ilr multiple linear regression model and provide predictions from reallocating compositional values pairwise amunsnst the components model.

Usage

plot_delta_comp(dc_obj, comp_total = NULL, units_lab = NULL)

Arguments

dc_obj	A deltacomp_obj object returned from the function predict_delta_comps
comp_total	A numeric scalar that is the original units of the composition to make the x-axis the original scale instead of in the range [min(delta), max(delta)] in (-1, 1).
units_lab	Character string of the units of the compositions relating to comp_total to add to the x-axis label

Author(s)

Ty Stanford <[e-mail]>

Examples

data(fairclough)

deltacomp_df <-
  predict_delta_comps(
    dataf = fairclough,
    y = "z_bmi",
    comps = c("sleep","sed","lpa","mvpa"),
    covars = c("decimal_age","sex"),
    deltas =  seq(-20, 20, by = 5) / (24 * 60), 
    comparisons = "prop-realloc",
    alpha = 0.05
  )
class(deltacomp_df)

plot_delta_comp(
  dc_obj = deltacomp_df,
  comp_total = 24 * 60,
  units_lab = "min"
)

deltacomp_df <-
  predict_delta_comps(
    dataf = fairclough,
    y = "z_bmi",
    comps = c("sleep","sed","lpa","mvpa"),
    covars = c("decimal_age","sex"),
    deltas =  seq(-20, 20, by = 5) / (24 * 60), 
    comparisons = "one-v-one",
    alpha = 0.05
  )

plot_delta_comp(
  dc_obj = deltacomp_df,
  comp_total = 24 * 60,
  units_lab = "min"
)

tystan/deltacomp documentation built on Oct. 26, 2022, 7:24 a.m.