beezdemand (version 0.2.0)

fit_cp_linear: Fit a Linear Cross-Price Demand Model

Description

Fit a Linear Cross-Price Demand Model

Usage

fit_cp_linear(
  data,
  type = c("fixed", "mixed"),
  x_var = "x",
  y_var = "y",
  id_var = "id",
  group_var = "group",
  target_var = "target",
  filter_target = TRUE,
  target_level = "alt",
  formula = NULL,
  log10x = FALSE,
  group_effects = FALSE,
  random_slope = FALSE,
  return_all = TRUE,
  ...
)
fit_cp_linear.default(
  data,
  formula = NULL,
  log10x = FALSE,
  return_all = FALSE,
  ...
)
fit_cp_linear.mixed(
  data,
  formula = NULL,
  log10x = FALSE,
  return_all = FALSE,
  ...
)

Value

Fitted linear model.

Arguments

data

A data frame containing columns for price, consumption, and optionally target indicator, subject identifier, and group.

type

The type of model: "fixed" for standard linear or "mixed" for mixed effects.

x_var

Character string; name of the price column. Default is "x". Renamed to "x" internally.

y_var

Character string; name of the consumption column. Default is "y". Renamed to "y" internally.

id_var

Character string; name of the subject identifier column. Default is "id". Required for mixed models; renamed to "id" internally.

group_var

Character string; name of the group column. Default is "group". Renamed to "group" internally when present.

target_var

Character string; name of the target indicator column. Default is "target". Renamed to "target" internally when present.

filter_target

Logical; if TRUE (default), filters to rows where the target column equals target_level.

target_level

Character string; value of the target column to retain when filter_target = TRUE. Default is "alt".

formula

Optional formula override. If NULL, a formula will be constructed based on other parameters. If non-NULL and any *_var argument differs from its default, an error is thrown because the formula references canonical column names that no longer exist before renaming; rename columns before calling, or omit the formula argument.

log10x

Logical; if TRUE and formula is NULL, uses log10(x) instead of x in the formula. Default is FALSE.

group_effects

Logical or character; if TRUE, includes group as a factor with interactions. Can also be "intercept" for group intercepts only or "interaction" for full interactions. Default is FALSE.

random_slope

Logical; for mixed models, if TRUE, includes random slopes for x. Default is FALSE.

return_all

Logical; if TRUE, returns additional model metadata.

...

Additional arguments passed to underlying modeling functions.

Examples

# \donttest{
data(etm)
## Fixed-effects linear cross-price model
fit_fixed <- fit_cp_linear(etm, type = "fixed", group_effects = TRUE)
summary(fit_fixed)

## Mixed-effects linear cross-price model
fit_mixed <- fit_cp_linear(etm, type = "mixed", group_effects = TRUE)
summary(fit_mixed)
# }