geessbin_all: Function for analysis using all combinations of GEE methods and covariance estimators

Description

geessbin_all provides analysis results using all combinations of three GEE methods and 12 covariance estimators.

Usage

geessbin_all(
  formula,
  data = parent.frame(),
  id = NULL,
  corstr = "independence",
  repeated = NULL,
  b = NULL,
  maxitr = 50,
  tol = 1e-05,
  scale.fix = FALSE,
  conf.level = 0.95
)

Value

The list containing two data frames. The first is a table of estimates of regression coefficients, standard errors, z-values, and p-values. The second is a table of odds ratios and confidence intervals.

Arguments

formula: Object of class formula: symbolic description of model to be fitted (see documentation of lm and formula for details).
data: Data frame.
id: Vector that identifies the subjects or clusters (NULL by default).
corstr: Working correlation structure. The following are permitted: "independence", "exchangeable", "ar1", and "unstructured" ("independence" by default).
repeated: Vector that identifies repeatedly measured variable within each subject or cluster. If repeated = NULL, as is the case in function gee, data are assumed to be sorted so that observations on a cluster are contiguous rows for all entities in the formula.
b: Numeric vector specifying initial values of regression coefficients. If b = NULL (default value), the initial values are calculated using the ordinary or Firth logistic regression assuming that all the observations are independent.
maxitr: Maximum number of iterations (50 by default).
tol: Tolerance used in fitting algorithm (1e-5 by default).
scale.fix: Logical variable; if TRUE, the scale parameter is fixed at 1 (FALSE by default).
conf.level: Numeric value of confidence level for confidence intervals (0.95 by default).