lsmeans: Extract Least Square Means from a GEE Model

In tern.gee: Tables and Graphs for Generalized Estimating Equations (GEE) Model Fits

Extract Least Square Means from a GEE Model

Description

Extract Least Square Means from a GEE Model

Usage

lsmeans(
  object,
  conf_level = 0.95,
  weights = "proportional",
  specs = object$vars$arm,
  ...
)

## S3 method for class 'tern_gee_logistic'
lsmeans(
  object,
  conf_level = 0.95,
  weights = "proportional",
  specs = object$vars$arm,
  ...
)

Arguments

object	(tern_gee) result of fit_gee().
conf_level	(proportion) confidence level
weights	(string) type of weights to be used for the least square means, see emmeans::emmeans() for details.
specs	(string or formula) specifications passed to emmeans::emmeans()
...	additional arguments for methods

Value

A data.frame with least-square means and contrasts. Additional classes allow to dispatch downstream methods correctly, too.

Examples

df <- fev_data
df$AVAL <- rbinom(n = nrow(df), size = 1, prob = 0.5)
fit <- fit_gee(vars = vars_gee(arm = "ARMCD"), data = df)

lsmeans(fit)

lsmeans(fit, conf_level = 0.90, weights = "equal")

tern.gee documentation built on Sept. 11, 2024, 8:11 p.m.