Estimate the global odds ratio for a GEE with ordinal or nominal data.
The following data structures are calculated in the class:
‘ibd’ is a list whose i^th element ibd[i] is a sequence of integer pairs (a,b), where endog_li[i][a:b] is the subvector of binary indicators derived from the same ordinal value.
cpp is a dictionary where cpp[group] is a map from cut-point pairs (c,c’) to the indices of all between-subject pairs derived from the given cut points.
PJ Heagerty and S Zeger. “Marginal Regression Models for Clustered Ordinal Measurements”. Journal of the American Statistical Association Vol. 91, Issue 435 (1996).
Thomas Lumley. Generalized Estimating Equations for Ordinal Data: A Note on Working Correlation Structures. Biometrics Vol. 52, No. 1 (Mar., 1996), pp. 354-361 http://www.jstor.org/stable/2533173
|covariance_matrix(expected_value, index)||Returns the working covariance or correlation matrix for a given cluster of data.|
|covariance_matrix_solve(expval, index, ...)||Solves matrix equations of the form covmat * soln = rhs and returns the values of soln, where covmat is the covariance matrix represented by this class.|
|get_eyy(endog_expval, index)||Returns a matrix V such that V[i,j] is the joint probability that endog[i] = 1 and endog[j] = 1, based on the marginal probabilities of endog and the global odds ratio current_or.|
|observed_crude_oddsratio()||To obtain the crude (global) odds ratio, first pool all binary indicators corresponding to a given pair of cut points (c,c’), then calculate the odds ratio for this 2x2 table.|
|pooled_odds_ratio(tables)||Returns the pooled odds ratio for a list of 2x2 tables.|
|update(params)||Updates the association parameter values based on the current regression coefficients.|