statsmodels.genmod.generalized_estimating_equations.GEE.fit¶
- GEE.fit(maxiter=60, ctol=1e-06, start_params=None, params_niter=1, first_dep_update=0, cov_type='robust', ddof_scale=None, scaling_factor=1.0, scale=None)[source]¶
Fits a marginal regression model using generalized estimating equations (GEE).
- Parameters:
- maxiter
int
The maximum number of iterations
- ctol
float
The convergence criterion for stopping the Gauss-Seidel iterations
- start_paramsarray_like
A vector of starting values for the regression coefficients. If None, a default is chosen.
- params_niter
int
The number of Gauss-Seidel updates of the mean structure parameters that take place prior to each update of the dependence structure.
- first_dep_update
int
No dependence structure updates occur before this iteration number.
- cov_type
str
One of “robust”, “naive”, or “bias_reduced”.
- ddof_scalescalar or
None
The scale parameter is estimated as the sum of squared Pearson residuals divided by N - ddof_scale, where N is the total sample size. If ddof_scale is None, the number of covariates (including an intercept if present) is used.
- scaling_factorscalar
The estimated covariance of the parameter estimates is scaled by this value. Default is 1, Stata uses N / (N - g), where N is the total sample size and g is the average group size.
- scale
str
orfloat
,optional
scale can be None, ‘X2’, or a float If a float, its value is used as the scale parameter. The default value is None, which uses X2 (Pearson’s chi-square) for Gamma, Gaussian, and Inverse Gaussian. The default is 1 for the Binomial and Poisson families.
- maxiter
- Returns:
An
instance
of
the
GEEResults
class
orsubclass
Notes
If convergence difficulties occur, increase the values of first_dep_update and/or params_niter. Setting first_dep_update to a greater value (e.g. ~10-20) causes the algorithm to move close to the GLM solution before attempting to identify the dependence structure.
For the Gaussian family, there is no benefit to setting params_niter to a value greater than 1, since the mean structure parameters converge in one step.