get_demand_comparisons: Get Pairwise Comparisons for Demand Parameters

In beezdemand: Behavioral Economic Easy Demand

Get Pairwise Comparisons for Demand Parameters

Description

Conducts pairwise comparisons for Q0 and/or alpha parameters from a beezdemand_nlme model across levels of specified factors. Comparisons are performed on the log10 scale of the parameters. Results include estimates of differences (on log10 scale) and optionally, ratios (on the natural scale by applying 10^difference).

Usage

get_demand_comparisons(
  fit_obj,
  params_to_compare = c("Q0", "alpha"),
  compare_specs = NULL,
  contrast_type = "pairwise",
  contrast_by = NULL,
  adjust = "tukey",
  at = NULL,
  ci_level = 0.95,
  report_ratios = TRUE,
  ...
)

Arguments

fit_obj	A beezdemand_nlme object.
params_to_compare	Character vector: "Q0", "alpha", or c("Q0", "alpha"). Default c("Q0", "alpha").
compare_specs	A formula specifying the factors whose levels are to be included in the EMM calculation prior to contrasting. This defines the "cells" of your design for EMMs. E.g., ~ factor1 (EMMs for levels of factor1, averaging over others), ~ factor1 * factor2 (EMMs for all cells of factor1 x factor2). If NULL, it defaults to an interaction of all factors in fit_obj$param_info$factors.
contrast_type	Character string specifying the type of contrast (passed to method in emmeans::contrast). Commonly "pairwise", "revpairwise", "eff", "consec", "poly". Default "pairwise".
contrast_by	Optional character vector of factor names to condition the contrasts by (passed to by in emmeans::contrast). If NULL (default), contrasts are performed over the primary terms implied by compare_specs and contrast_type. Example: If compare_specs = ~ dose * drug, contrast_type = "pairwise", and contrast_by = "dose", this will perform pairwise comparisons of drug levels within each level of dose. Note: If the original fit_obj model is additive for the factors involved (i.e., no interaction term was fitted), specifying contrast_by will result in identical contrast estimates across the levels of the contrast_by variable(s). In such cases, consider analyzing main effects directly (e.g., compare_specs = ~drug, contrast_by = NULL).
adjust	P-value adjustment method. Default "tukey".
at	Optional named list for emmeans::ref_grid().
ci_level	Confidence level. Default 0.95.
report_ratios	Logical. If TRUE, reports contrasts as ratios. Default TRUE.
...	Additional arguments passed to emmeans::emmeans() or emmeans::contrast().

Value

A list named by parameter. Each element contains:

emmeans	Tibble of EMMs (log10 scale) with CIs.
contrasts_log10	Tibble of comparisons (log10 differences) with CIs and p-values.
contrasts_ratio	(If report_ratios=TRUE and successful) Tibble of comparisons as ratios (natural scale), with CIs for ratios.

S3 class beezdemand_comparison is assigned.

Examples

data(ko, package = "beezdemand")
ko$y_ll4 <- ll4(ko$y, lambda = 4)
fit <- fit_demand_mixed(ko, y_var = "y_ll4", x_var = "x",
  id_var = "monkey", factors = "dose", equation_form = "zben")
get_demand_comparisons(fit)

beezdemand documentation built on March 3, 2026, 9:07 a.m.