statsmodels.stats.contingency_tables.Table2x2

class statsmodels.stats.contingency_tables.Table2x2(table, shift_zeros=True)

Analyses that can be performed on a 2x2 contingency table

Parameters:

tablearray_like

A 2x2 contingency table

shift_zerosbool

If true, 0.5 is added to all cells of the table if any cell is equal to zero.

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_oddsratios.

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.

log_oddsratio

Returns the log odds ratio for a 2x2 table

log_oddsratio_se

Returns the standard error for the log odds ratio

log_riskratio

Returns the log of the risk ratio

log_riskratio_se

Returns the standard error of the log of the risk ratio

marginal_probabilities

Estimate marginal probability distributions for the rows and columns

rowndarray

Marginal row probabilities

colndarray

Marginal column probabilities

oddsratio

Returns the odds ratio for a 2x2 table

resid_pearson

Returns Pearson residuals

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

riskratio

Returns the risk ratio for a 2x2 table

The risk ratio is calculated with respect to the rows.

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
log_oddsratio_confint([alpha, method])	A confidence level for the log odds ratio
log_oddsratio_pvalue([null])	P-value for a hypothesis test about the log odds ratio
log_riskratio_confint([alpha, method])	A confidence interval for the log risk ratio
log_riskratio_pvalue([null])	p-value for a hypothesis test about the log risk ratio
oddsratio_confint([alpha, method])	A confidence interval for the odds ratio
oddsratio_pvalue([null])	P-value for a hypothesis test about the odds ratio
riskratio_confint([alpha, method])	A confidence interval for the risk ratio
riskratio_pvalue([null])	p-value for a hypothesis test about the risk ratio
summary([alpha, float_format, method])	Summarizes results for a 2x2 table analysis
symmetry([method])	Test for symmetry of a joint distribution
test_nominal_association()	Assess independence for nominal factors
test_ordinal_association([row_scores, ...])	Assess independence between two ordinal variables

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.

Note that for the risk ratio, the analysis is not symmetric with respect to the rows and columns of the contingency table. The two rows define population subgroups, column 0 is the number of ‘events’, and column 1 is the number of ‘non-events’.

Methods

from_data(data[, shift_zeros])	Construct a Table object from data
homogeneity([method])	Compare row and column marginal distributions
log_oddsratio_confint([alpha, method])	A confidence level for the log odds ratio
log_oddsratio_pvalue([null])	P-value for a hypothesis test about the log odds ratio
log_riskratio_confint([alpha, method])	A confidence interval for the log risk ratio
log_riskratio_pvalue([null])	p-value for a hypothesis test about the log risk ratio
oddsratio_confint([alpha, method])	A confidence interval for the odds ratio
oddsratio_pvalue([null])	P-value for a hypothesis test about the odds ratio
riskratio_confint([alpha, method])	A confidence interval for the risk ratio
riskratio_pvalue([null])	p-value for a hypothesis test about the risk ratio
summary([alpha, float_format, method])	Summarizes results for a 2x2 table analysis
symmetry([method])	Test for symmetry of a joint distribution
test_nominal_association()	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
log_oddsratio	Returns the log odds ratio for a 2x2 table
log_oddsratio_se	Returns the standard error for the log odds ratio
log_riskratio	Returns the log of the risk ratio
log_riskratio_se	Returns the standard error of the log of the risk ratio
marginal_probabilities	Estimate marginal probability distributions for the rows and columns
oddsratio	Returns the odds ratio for a 2x2 table
resid_pearson	Returns Pearson residuals
riskratio	Returns the risk ratio for a 2x2 table
standardized_resids	Returns standardized residuals under independence