beezdemand (version 0.2.0)

get_demand_param_emms: Get Estimated Marginal Means for Demand Parameters

Description

Calculates Estimated Marginal Means (EMMs) for Q0 and alpha parameters from a beezdemand_nlme model for all combinations of specified factor levels. Reports parameters on both their estimation scale (log10) and their natural, back-transformed scale. Optionally includes Essential Value (EV).

Usage

get_demand_param_emms(
  fit_obj,
  factors_in_emm = NULL,
  at = NULL,
  ci_level = 0.95,
  include_ev = FALSE,
  ...
)

Value

A tibble containing:

Factor levels

Columns for each factor in factors_in_emm.

Q0_param_log10, alpha_param_log10

EMMs for the model parameters (log10 scale) with their respective confidence intervals (LCL_Q0_param, UCL_Q0_param, etc.).

Q0_natural, alpha_natural

EMMs back-transformed to the natural scale (10^param) with their respective confidence intervals (LCL_Q0_natural, UCL_Q0_natural, etc.).

EV, LCL_EV, UCL_EV

(If include_ev=TRUE) Essential Value and its CI.

Arguments

fit_obj

A beezdemand_nlme object.

factors_in_emm

Character vector of factor names to compute EMMs over. Defaults to all factors present in the fit_obj.

at

Optional named list specifying levels of conditioning variables for emmeans::ref_grid().

ci_level

Confidence level for the EMMs (default 0.95).

include_ev

Logical. If TRUE, calculates and includes Essential Value (EV) derived from alpha, along with its confidence interval (calculated by back-transforming the CI of alpha_param_log10). Default FALSE.

...

Additional arguments passed to emmeans::emmeans().

Examples

# \donttest{
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_param_emms(fit)
# }