statsmodels.stats.contingency_tables.Table

class statsmodels.stats.contingency_tables.Table(table, shift_zeros=True)

A two-way contingency table.

Parameters:

• table (array-like) – A contingency table.
• shift_zeros (boolean) – If True and any cell count is zero, add 0.5 to all values in the table.

table_orig

array-like – The original table is cached as table_orig.

marginal_probabilities

tuple of two ndarrays – The estimated row and column marginal distributions.

independence_probabilities

ndarray – Estimated cell probabilities under row/column independence.

fittedvalues

ndarray – Fitted values under independence.

resid_pearson

ndarray – The Pearson residuals under row/column independence.

standardized_resids

ndarray – Residuals for the independent row/column model with approximate unit variance.

chi2_contribs

ndarray – The contribution of each cell to the chi^2 statistic.

local_logodds_ratios

ndarray – The local log odds ratios are calculated for each 2x2 subtable formed from adjacent rows and columns.

local_oddsratios

ndarray – The local odds ratios are calculated from each 2x2 subtable formed from adjacent rows and columns.

cumulative_log_oddsratios

ndarray – The cumulative log odds ratio at a given pair of thresholds is calculated by reducing the table to a 2x2 table based on dichotomizing the rows and columns at the given thresholds. The table of cumulative log odds ratios presents all possible cumulative log odds ratios that can be formed from a given table.

cumulative_oddsratios

ndarray – The cumulative odds ratios are calculated by reducing the table to a 2x2 table based on cutting the rows and columns at a given point. The table of cumulative odds ratios presents all possible cumulative odds ratios that can be formed from a given table.

See also

statsmodels.graphics.mosaicplot.mosaic, scipy.stats.chi2_contingency

Notes

The inference procedures used here are all based on a sampling model in which the units are independent and identically distributed, with each unit being classified with respect to two categorical variables.

References

Definitions of residuals:

https://onlinecourses.science.psu.edu/stat504/node/86

Methods

chi2_contribs()
cumulative_log_oddsratios()
cumulative_oddsratios()
fittedvalues()
from_data(data[, shift_zeros])	Construct a Table object from data.
independence_probabilities()
local_log_oddsratios()
local_oddsratios()
marginal_probabilities()
resid_pearson()
standardized_resids()
test_nominal_association()	Assess independence for nominal factors.
test_ordinal_association([row_scores, …])	Assess independence between two ordinal variables.