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.

Notes

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

Attributes

logodds_pooled()
oddsratio_pooled()
risk_pooled()

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.

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.