Metadata-Version: 2.1
Name: diff-binom-confint
Version: 0.0.1
Summary: Computation of confidence intervals for binomial proportions and for difference of binomial proportions.
Home-page: https://github.com/DeepPSP/DBCI
Author: DeepPSP
Author-email: wenh06@gmail.com
License: MIT
Description: # Confidence Intervals for Difference of Binomial Proportions
        
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        Computation of confidence intervals for binomial proportions and for difference of binomial proportions.
        
        ## References
        
        1. <a name="ref1"></a> [SAS](https://www.lexjansen.com/wuss/2016/127_Final_Paper_PDF.pdf)
        2. <a name="ref2"></a> [PASS](https://ncss-wpengine.netdna-ssl.com/wp-content/themes/ncss/pdf/Procedures/PASS/Confidence_Intervals_for_the_Difference_Between_Two_Proportions.pdf)
        3. <a name="ref3"></a> [statsmodels.stats.proportion](https://www.statsmodels.org/devel/_modules/statsmodels/stats/proportion.html)
        4. <a name="ref4"></a> [scipy.stats._binomtest](https://github.com/scipy/scipy/blob/main/scipy/stats/_binomtest.py)
        5. <a name="ref5"></a> [corplingstats](https://corplingstats.wordpress.com/2019/04/27/correcting-for-continuity/)
        6. <a name="ref6"></a> [DescTools.StatsAndCIs](https://github.com/AndriSignorell/DescTools/blob/master/R/StatsAndCIs.r)
        
        ## NOTE
        
        [Reference 1](#ref1) has errors in the description of the methods `Wilson CC`, `Mee`, `Miettinen-Nurminen`.
        The correct computation of `Wilson CC` is given in [Reference 5](#ref5).
        The correct computation of `Mee`, `Miettinen-Nurminen` are given in the **code blocks** in [Reference 1](#ref1)
        
        ## Test data
        
        [Test data](test/test-data/) are
        
        1. taken from [Reference 1](#ref1) for automatic test of the correctness of the implementation of the algorithms.
        2. generated using [DescTools.StatsAndCIs](#ref6) via
        
            ```R
            library("DescTools")
            library("data.table")
        
            results = data.table()
            for (m in c("wilson", "wald", "waldcc", "agresti-coull", "jeffreys",
                            "modified wilson", "wilsoncc","modified jeffreys",
                            "clopper-pearson", "arcsine", "logit", "witting", "pratt", 
                            "midp", "lik", "blaker")){
                ci = BinomCI(84,101,method = m)
                new_row = data.table("method" = m, "ratio"=ci[1], "lower_bound" = ci[2], "upper_bound" = ci[3])
                results = rbindlist(list(results, new_row))
            }
            fwrite(results, "./test/test-data/example-84-101.csv")  # with manual slight adjustment of method names
            ```
        
        The filenames has the following pattern:
        
        ```python
        # for computing confidence interval for difference of binomial proportions
        "example-(?P<n_positive>[\\d]+)-(?P<n_total>[\\d]+)-vs-(?P<ref_positive>[\\d]+)-(?P<ref_total>[\\d]+)\\.csv"
        
        # for computing confidence interval for binomial proportions
        "example-(?P<n_positive>[\\d]+)-(?P<n_total>[\\d]+)\\.csv"
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: dev
