3.11.10.5.1. statsmodels.stats.inter_rater.KappaResults¶
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class
statsmodels.stats.inter_rater.
KappaResults
(**kwds)[source]¶ Results for Cohen’s kappa
Attributes
kappa (cohen’s kappa) var_kappa (variance of kappa) std_kappa (standard deviation of kappa) alpha (one-sided probability for confidence interval) kappa_low (lower (1-alpha) confidence limit) kappa_upp (upper (1-alpha) confidence limit) var_kappa0 (variance of kappa under H0: kappa=0) std_kappa0 (standard deviation of kappa under H0: kappa=0) z_value (test statistic for H0: kappa=0, is standard normal distributed) pvalue_one_sided (one sided p-value for H0: kappa=0 and H1: kappa>0) pvalue_two_sided (two sided p-value for H0: kappa=0 and H1: kappa!=0) distribution_kappa (asymptotic normal distribution of kappa) distribution_zero_null (asymptotic normal distribution of kappa under) H0: kappa=0 The confidence interval for kappa and the statistics for the test of H0: kappa=0 are based on the asymptotic normal distribution of kappa. -
__init__
(**kwds)¶
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3.11.10.5.1.1. Methods¶
__init__ (**kwds) |
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clear (() -> None. Remove all items from D.) |
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copy (() -> a shallow copy of D) |
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fromkeys (...) |
v defaults to None. |
get ((k[,d]) -> D[k] if k in D, ...) |
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has_key ((k) -> True if D has a key k, else False) |
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items (() -> list of D’s (key, value) pairs, ...) |
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iteritems (() -> an iterator over the (key, ...) |
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iterkeys (() -> an iterator over the keys of D) |
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itervalues (...) |
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keys (() -> list of D’s keys) |
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pop ((k[,d]) -> v, ...) |
If key is not found, d is returned if given, otherwise KeyError is raised |
popitem (() -> (k, v), ...) |
2-tuple; but raise KeyError if D is empty. |
setdefault ((k[,d]) -> D.get(k,d), ...) |
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update (([E, ...) |
If E present and has a .keys() method, does: for k in E: D[k] = E[k] |
values (() -> list of D’s values) |
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viewitems (...) |
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viewkeys (...) |
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viewvalues (...) |