prompt_scale: Prompt scale of axes depending on model type

In OxWearables/epicoda: Supports epidemiological analyses using compositional exposure variables

Prompt scale of axes depending on model type

Description

Prompt scale of axes depending on model type

Usage

prompt_scale(model, terms, plot_log)

Arguments

model	Model to use in estimates/predictions.
terms	Are estimates for differences in outcome associated with differences in compositional variables? If terms = TRUE all estimates and plots will be for difference in outcome associated with differences in the compositional variables. If terms = FALSE, fixed_values is used to set the values of the non-compositional covariates, and outputs are predictions for the outcome based on these values of the non-compositional covariates and the given value of the compositional variables (and confidence intervals include uncertainty due to all variables in the model, not just the compositional variables). Note that for logistic regression models with terms = TRUE estimates are odds ratios; for logistic regression models with terms = FALSE estimates are probabilities (i.e. predictions on the response scale).
plot_log	If this is TRUE, the y-axis will be log-transformed.

OxWearables/epicoda documentation built on Dec. 7, 2022, 9:07 p.m.