First differences for the matched count families

The discrete-change effect on the expected count E(Y) as variable moves from from to to, holding the other covariates at their sample means (or at the values at gives them). The interval follows the package's one rule (see first_difference()): percentile intervals from the fit's stored bootstrap draws for the GEC, fixed-effects CPB and zero-inflated GEC fits, the delta method over the full covariance, the dispersion parameter included, for the matched count families and the hurdles' margins. For count_reg this is a single number; for the two-part models it is reported on each margin: the binary stage's probability (participation, or the structural-zero probability), the count stage's mean, and the marginal mean, their product, each at from and to. The first two are different quantities and their changes do not add up to the marginal change, which is \(\Delta(pm) = \Delta p\, m_0 + p_0 \Delta m + \Delta p\, \Delta m\).

Usage

# S3 method for class 'gec'
first_difference(object, variable, from, to, level = 0.95, at = NULL, ...)

# S3 method for class 'gec_fe'
first_difference(object, variable, from, to, level = 0.95, at = NULL, ...)

# S3 method for class 'cpb_fe'
first_difference(object, variable, from, to, level = 0.95, at = NULL, ...)

# S3 method for class 'hurdle_gec'
first_difference(
  object,
  variable,
  from,
  to,
  level = 0.95,
  stage = c("both", "participation", "intensity", "zero", "count"),
  at = NULL,
  ...
)

# S3 method for class 'zi_gec'
first_difference(
  object,
  variable,
  from,
  to,
  level = 0.95,
  stage = c("both", "participation", "intensity", "zero", "count"),
  at = NULL,
  ...
)

# S3 method for class 'count_reg'
first_difference(object, variable, from, to, level = 0.95, at = NULL, ...)

# S3 method for class 'hurdle_count'
first_difference(
  object,
  variable,
  from,
  to,
  level = 0.95,
  stage = c("both", "participation", "intensity", "zero", "count"),
  at = NULL,
  ...
)

# S3 method for class 'zi_count'
first_difference(
  object,
  variable,
  from,
  to,
  level = 0.95,
  stage = c("both", "participation", "intensity", "zero", "count"),
  at = NULL,
  ...
)

Arguments

object

A fitted count_reg, gec, gec_fe, cpb_fe, hurdle_count, zi_count, hurdle_gec, or zi_gec model.

variable

Name of the covariate to change (must be in the model).

from, to

The two values of variable.

level

Confidence level of the intervals.

at

Optional named numeric vector fixing other model-matrix columns at given values instead of their means (see first_difference()); in a two-part model a column of both equations is fixed in both.

...

Unused; unknown arguments error.

stage

For the two-part models, which equation(s) the change is applied to. "both" (default) moves the variable wherever it appears; "intensity"/"count" or "participation"/"zero" moves it in only that equation, holding it at the reference in the other. For a variable in only one equation all options coincide; for a variable in both, "both" gives the total effect and the single-stage options the partial effect through that margin. All component rows are always returned.

Value

A "ud_fd" data frame – the package-wide first-difference contract shared by every first_difference() method: columns component, from, to, diff, lower, upper, method. Single-equation fits return one row (component = "mean"); two-part fits return one row per margin level (binary-stage probability, count-stage mean, marginal mean). method records the uncertainty source per row ("delta", a bootstrap label, or "none" with NA bounds).