# statsmodels.stats.contingency_tables.SquareTable¶

class statsmodels.stats.contingency_tables.SquareTable(table, shift_zeros=True)[source]

Methods for analyzing a square contingency table.

Parameters
tablearray_like

A square contingency table, or DataFrame that is converted to a square form.

shift_zerosbool

If True and any cell count is zero, add 0.5 to all values in the table.

These methods should only be used when the rows and columns of the
table have the same categories. If table is provided as a
Pandas DataFrame, the row and column indices will be extended to
create a square table, inserting zeros where a row or column is
missing. Otherwise the table should be provided in a square form,
with the (implicit) row and column categories appearing in the
same order.
Attributes
chi2_contribs

Returns the contributions to the chi^2 statistic for independence.

The returned table contains the contribution of each cell to the chi^2 test statistic for the null hypothesis that the rows and columns are independent.

cumulative_log_oddsratios

Returns cumulative log odds ratios.

The cumulative log odds ratios for a contingency table with ordered rows and columns are calculated by collapsing all cells to the left/right and above/below a given point, to obtain a 2x2 table from which a log odds ratio can be calculated.

cumulative_oddsratios

Returns the cumulative odds ratios for a contingency table.

See documentation for cumulative_log_oddsratio.

fittedvalues

Returns fitted cell counts under independence.

The returned cell counts are estimates under a model where the rows and columns of the table are independent.

independence_probabilities

Returns fitted joint probabilities under independence.

The returned table is outer(row, column), where row and column are the estimated marginal distributions of the rows and columns.

local_log_oddsratios

Returns local log odds ratios.

The local log odds ratios are the log odds ratios calculated for contiguous 2x2 sub-tables.

local_oddsratios

Returns local odds ratios.

See documentation for local_log_oddsratios.

marginal_probabilities

Estimate marginal probability distributions for the rows and columns.

rowndarray

Marginal row probabilities

colndarray

Marginal column probabilities

resid_pearson

Returns Pearson residuals.

The Pearson residuals are calculated under a model where the rows and columns of the table are independent.

standardized_resids

Returns standardized residuals under independence.

Methods

 from_data(data[, shift_zeros]) Construct a Table object from data. homogeneity([method]) Compare row and column marginal distributions. summary([alpha, float_format]) Produce a summary of the analysis. symmetry([method]) Test for symmetry of a joint distribution. Assess independence for nominal factors. test_ordinal_association([row_scores, …]) Assess independence between two ordinal variables.

Methods

 from_data(data[, shift_zeros]) Construct a Table object from data. homogeneity([method]) Compare row and column marginal distributions. summary([alpha, float_format]) Produce a summary of the analysis. symmetry([method]) Test for symmetry of a joint distribution. Assess independence for nominal factors. test_ordinal_association([row_scores, …]) Assess independence between two ordinal variables.

Properties

 chi2_contribs Returns the contributions to the chi^2 statistic for independence. cumulative_log_oddsratios Returns cumulative log odds ratios. cumulative_oddsratios Returns the cumulative odds ratios for a contingency table. fittedvalues Returns fitted cell counts under independence. independence_probabilities Returns fitted joint probabilities under independence. local_log_oddsratios Returns local log odds ratios. local_oddsratios Returns local odds ratios. marginal_probabilities Estimate marginal probability distributions for the rows and columns. resid_pearson Returns Pearson residuals. standardized_resids Returns standardized residuals under independence.