beezdemand (version 0.2.0)

get_demand_param_trends: Get Trends (Slopes) of Demand Parameters with respect to Continuous Covariates

Description

Computes the trend (slope) of Q0 and/or alpha with respect to one or more continuous covariates using emmeans::emtrends() on a fitted beezdemand_nlme model. Trends are computed on the parameter estimation scale (log10), consistent with how parameters are modeled.

Usage

get_demand_param_trends(
  fit_obj,
  params = c("Q0", "alpha"),
  covariates,
  specs = ~1,
  at = NULL,
  ci_level = 0.95,
  ...
)

Value

A tibble combining trends for each requested parameter and covariate, including columns for grouping factors (from specs), parameter, covariate, trend (slope on log10 scale), and its CI (lower.CL, upper.CL).

Arguments

fit_obj

A beezdemand_nlme object from fit_demand_mixed().

params

Character vector of parameters to analyze: any of "Q0", "alpha". Default c("Q0", "alpha").

covariates

Character vector of continuous covariate names for which to compute trends.

specs

A formula specifying the factors over which to produce trends (e.g., ~ drug for trends by drug; ~ 1 for overall). Default ~ 1.

at

Optional named list to condition variables (factors or continuous) when computing trends (passed through to emmeans::ref_grid).

ci_level

Confidence level for intervals. Default 0.95.

...

Additional args passed to emmeans::emtrends().

Examples

# \donttest{
data(ko)
ko$dose_num <- as.numeric(as.character(ko$dose))
fit <- fit_demand_mixed(ko, y_var = "y_ll4", x_var = "x",
                        id_var = "monkey", factors = "drug",
                        equation_form = "zben")
trends <- get_demand_param_trends(fit, covariates = "dose_num",
                                  specs = ~ drug)
# }