Poisson regression and loglinear models — morie_poisson_loglinear • rmorie

Equations 4.1 to 4.7, 4.12, 4.15 of Bilder & Loughin (2025).

Usage

morie_poisson_loglinear(
  mu_hat = NA,
  n = NA,
  z = 1.96,
  b0 = NA,
  bs = NULL,
  xs = NULL,
  exposure = NA,
  beta_x_i = NA,
  beta_z_j = NA,
  beta_xz_ij = NA,
  bxz = NULL,
  beta_z_jp = NA,
  beta_xz_i = NA,
  s_j = NA,
  s_jp = NA
)

Arguments

mu_hat, n, z: Score interval pieces.
b0, bs, xs: Log link.
exposure: Rate-model exposure t.
beta_x_i, beta_z_j,: beta_xz_ij Loglinear cell parameters.
beta_xz_ij: See Usage.
bxz: Four interaction parameters c(ij, i'j', i'j, ij') for the odds ratio of eq 4.7.
beta_z_jp, beta_xz_i, s_j, s_jp: Ordinal-score ratio pieces.

Value

List with score_ci, mu, mu_rate, mu_cell, or_loglinear, mean_ratio (as supplied).

Examples

morie_poisson_loglinear()
#> list()