statsmodels.stats.contingency_tables.Table¶

class
statsmodels.stats.contingency_tables.
Table
(table, shift_zeros=True)[source]¶ A twoway contingency table.
Parameters:  table (arraylike) – 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
¶ arraylike – The original table is cached as table_orig.

marginal_probabilities
[source]¶ tuple of two ndarrays – The estimated row and column marginal distributions.

independence_probabilities
[source]¶ ndarray – Estimated cell probabilities under row/column independence.

standardized_resids
[source]¶ ndarray – Residuals for the independent row/column model with approximate unit variance.

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

local_oddsratios
[source]¶ ndarray – The local odds ratios are calculated from each 2x2 subtable formed from adjacent rows and columns.

cumulative_log_oddsratios
[source]¶ 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
[source]¶ 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.