This article presents a model for multiple pair-wise comparisons of selected categories (cells) of a contingency table after the chi-square test has rejected the null hypothesis of equality of population proportions. The model will determine which, if any, pair-wise proportions among the multiple cross-classifications have led to the rejection. The model is developed by considering the relationship between the chi-square distribution and a particular standardized normal.
Get full access to this article
View all access options for this article.
References
1.
Allison, H. E. (1964). Computational forms for chi-square. The American Statistician, 18, 17-18.
2.
Andrews, D. W. K. (1988). Chi-square diagnostic tests for econometric models. The Journal of Econometrics, 37, 135-156.
3.
Berry, K. J. and Mielke, P. W. Jr. (1988). Monte Carlo comparison of the asymptotic chi-square and likelihood-ratio tests with the nonasymptotic chi-square test for sparse rxr tables. Psychological Bulletin, 103(2), 256-264.
4.
Boyton, K. M. and Poe, N. M. (1979). Alternate formulas for chi-square. Perceptual and Motor Skills, 48, 556-558.
5.
Campos, L. (1967). On the computations of the chi-square from derived tables of contingencies. Philippine Sociological Review, 15(3-4), 162-166.
6.
Chapman, Judith-Anne. (1976). A comparison of the x2, -2 log R, and multinomial probability criteria for significance tests when expected frequencies are small. Journal of the American Statistical Association, 71(356), 854-863.
7.
Cohen, J. E. (1976). The distribution of the chi-square statistic under clustered sampling from contingency tables. Journal of the American Statistical Association, 71(355), 665-669.
8.
Hamdan, M. A. (1968). Optimum choice of classes for contingency tables. American Statistical Association Journal, 63(321), 291-297.
9.
Israels, A. Z. and Van Driel, J. (1983). Use of the chi-square statistic for selecting explanatory variables in multiway tables. Quality and Quantity, 17, 103-116.
10.
Iverson, G. R. (1979). Decomposing chi-square: A forgotten technique. Sociological Methods and Research, 8(2), 143-157. COX AND KEY
11.
Jemrich, R. I. (1970). Asymptotic X2 test for the equality of two correlation matrices. Journal of the American Statistical Association, 65, 904-912.
12.
Kimucan, M. T. and Wolfsam, D. (1990). Direct comparison of bibliometric models."Information Processing and Management, 26(6), 777-790.
13.
Kroll, N. E. A. (1989). Testing independence in 2x2 contingency tables. Journal of Education Statistics, 14(1), 47-79.
14.
Lancaster, H. 0. (1969). The chi-squared distribution. New York: Wiley.
15.
Loosen, Franz (1979). Note on the chi-square statistic of association in 2x2 contingency tables and the correction for continuity. Quality and Quantity, 13, 351-356.
16.
Marascuilo, L. A. and Dagenais, F. (1982). Planned and post hoc comparisons for tests of homogeneity where the fependent variable is vategorical and ordered, Educational and Psychological Measurement, 42(3), 777-781.
17.
Ringuest, J. L. (1986). A chi-square statistic for validating simulation-generated responses. Computer and Operations Research, 13(4), 379-385.
18.
Spratt, D. A. (1964). Use of chi-square. Journal of Abnormal and Social Psychology, 69(1), 101-104.