
Get Trends (Slopes) of Demand Parameters with respect to Continuous Covariates
Source:R/mixed-methods.R
get_demand_param_trends.RdComputes 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,
...
)Arguments
- fit_obj
A
beezdemand_nlmeobject fromfit_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.,
~ drugfor trends by drug;~ 1for 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().
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).
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")
#> Generating starting values using method: 'heuristic'
#> Using heuristic method for starting values.
#> --- Fitting NLME Model ---
#> Equation Form: zben
#> Param Space: log10
#> NLME Formula: y_ll4 ~ Q0 * exp(-(10^alpha/Q0) * (10^Q0) * x)
#> Start values (first few): Q0_int=2.27, alpha_int=-3
#> Number of fixed parameters: 6 (Q0: 3, alpha: 3)
trends <- get_demand_param_trends(fit, covariates = "dose_num",
specs = ~ drug)
#> Warning: No trends could be calculated. Check 'covariates', 'specs', and 'at'.
# }