statsmodels.stats.contingency_tables.StratifiedTable

class statsmodels.stats.contingency_tables.StratifiedTable(tables, shift_zeros=False)

Analyses for a collection of 2x2 contingency tables.

Such a collection may arise by stratifying a single 2x2 table with respect to another factor. This class implements the ‘Cochran-Mantel-Haenszel’ and ‘Breslow-Day’ procedures for analyzing collections of 2x2 contingency tables.

Parameters:tables (list or ndarray) – Either a list containing several 2x2 contingency tables, or a 2x2xk ndarray in which each slice along the third axis is a 2x2 contingency table.

logodds_pooled

float – An estimate of the pooled log odds ratio. This is the Mantel-Haenszel estimate of an odds ratio that is common to all the tables.

log_oddsratio_se

float – The estimated standard error of the pooled log odds ratio, following Robins, Breslow and Greenland (Biometrics 42:311-323).

oddsratio_pooled

float – An estimate of the pooled odds ratio. This is the Mantel-Haenszel estimate of an odds ratio that is common to all tables.

risk_pooled

float – An estimate of the pooled risk ratio. This is an estimate of a risk ratio that is common to all the tables.

Notes

This results are based on a sampling model in which the units are independent both within and between strata.

Methods

from_data(var1, var2, strata, data)	Construct a StratifiedTable object from data.
logodds_pooled()
logodds_pooled_confint([alpha, method])	A confidence interval for the pooled log odds ratio.
logodds_pooled_se()
oddsratio_pooled()
oddsratio_pooled_confint([alpha, method])	A confidence interval for the pooled odds ratio.
risk_pooled()
summary([alpha, float_format, method])	A summary of all the main results.
test_equal_odds([adjust])	Test that all odds ratios are identical.
test_null_odds([correction])	Test that all tables have odds ratio equal to 1.