Two formulas are presented for judging the significance of the difference between correlated proportions. The chi square equivalent of one of the developed formulas is pointed out.
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%0 Journal Article
%1 mcnemar1947sampling
%A McNemar, Quinn
%D 1947
%J Psychometrika
%K significance
%N 2
%P 153--157
%R 10.1007/BF02295996
%T Note on the sampling error of the difference between correlated proportions or percentages
%U https://doi.org/10.1007/BF02295996
%V 12
%X Two formulas are presented for judging the significance of the difference between correlated proportions. The chi square equivalent of one of the developed formulas is pointed out.
@article{mcnemar1947sampling,
abstract = {Two formulas are presented for judging the significance of the difference between correlated proportions. The chi square equivalent of one of the developed formulas is pointed out.},
added-at = {2024-02-16T10:11:54.000+0100},
author = {McNemar, Quinn},
biburl = {https://www.bibsonomy.org/bibtex/249521066f0a43c5f81640e13a3181af1/albinzehe},
day = 01,
doi = {10.1007/BF02295996},
interhash = {24159e1d5ddf6be61005d7c652efa478},
intrahash = {49521066f0a43c5f81640e13a3181af1},
issn = {1860-0980},
journal = {Psychometrika},
keywords = {significance},
month = jun,
number = 2,
pages = {153--157},
timestamp = {2024-02-16T10:11:54.000+0100},
title = {Note on the sampling error of the difference between correlated proportions or percentages},
url = {https://doi.org/10.1007/BF02295996},
volume = 12,
year = 1947
}