1976
DOI: 10.1080/00031305.1976.10479127
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Actual Type 1 Error Probabilities for Various Tests in the Homogeneity Case of the 2 × 2 Contingency Table

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Cited by 21 publications
(6 citation statements)
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“…Against these criteria a number of clear conclusions can be drawn with regard to the usefulness of the four variants of X 2 in analysing 2 x 2 contingency tables. Although the data presented here have been confined to the conventional criterion level of significance (a=0.05), similar conclusions can be reached with other a levels (see also Camilli & Hopkins, 1978, 1979Garside & Mack, 1976;Overall et al, 1987;Rhoades & Overall, 1982;Roscoe & Byars, 1971).…”
Section: Discussionsupporting
confidence: 82%
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“…Against these criteria a number of clear conclusions can be drawn with regard to the usefulness of the four variants of X 2 in analysing 2 x 2 contingency tables. Although the data presented here have been confined to the conventional criterion level of significance (a=0.05), similar conclusions can be reached with other a levels (see also Camilli & Hopkins, 1978, 1979Garside & Mack, 1976;Overall et al, 1987;Rhoades & Overall, 1982;Roscoe & Byars, 1971).…”
Section: Discussionsupporting
confidence: 82%
“…Some researchers have followed Yates (1934) in claiming that the use of Pearson's X 2 in the case of 2 x 2 contingency tables tends to generate too many Type I errors, especially with small samples (e.g. Garside & Mack 1976;Haber, 1980). Nevertheless, the correction for continuity appropriate to any particular statistic will depend upon the range of possible values that the statistic may take, and in the case of 2 x 2 contingency tables this depends in turn upon the underlying statistical model.…”
Section: Corrections For Continuitymentioning
confidence: 99%
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“…When considering sample size determination for 2 X 2 contingency tables, one should be aware of the problem of discrepancies between the nominal and actual levels of significance. Garside and Mack (1976) give some numerical results which indicate that for 0.1 < P < 0.5 (P P1 P2) and n reasonably large, only minor differences are found. For example, with n = 100 and a = 0.05, the actual significance levels ranged from 0.0310 to 0.0384 for 0.1 < P < 0.5.…”
Section: Resultsmentioning
confidence: 89%
“…A brief description is given in Section 3 of the algorithm used to generate the critical regions (the algorithm is applicable to any combination of sample sizes but for larger values, i.e., N, > 100; i = 1, 2, excessive amounts of computer time are required). The latter two papers have recently been reviewed by Garside and Mack [5]. An alternate approach for small sample sizes has been proposed by Boschoo [2].…”
Section: Introductionmentioning
confidence: 99%