Fisher exact test

(redirected from Fisher's exact test)
Also found in: Wikipedia.

Fish·er ex·act test

(fish'ĕr),
the test for association in a two-by-two table that is based on the exact distribution of the frequencies within the table.

Fish·er ex·act test

(fish'ĕr eg-zakt' test)
Statistical significance assessment that uses a two-by-two table that is based on the exact distribution of the frequencies within the table.

Fisher exact test

[R. A. Fisher, Brit. mathematician, 1890–1962]
A test used to determine the statistical significance of findings generated from small sets of data.

Fisher,

Ronald A., English statistician, 1890-1962.
Fisher exact test - a statistical hypothesis test.
References in periodicals archive ?
Fisher's exact test was used to determine the comparison of TGF-[alpha] expression between SMG and SLG.
P-value = 0.384 * Fisher's exact test (low expected value) was higher than 0.05, which implies that the difference between the knowledge of men and women in this area was not statistically significant.
In a post hoc analysis, the mutations were significantly more prevalent among CCCA patients, compared with 2,702 control women of African ancestry (P = .03 by the chi-square test and P = 0.04 by Fisher's exact test after adjusting for relatedness of study participants).
In the analysis of the dependence between categorical variables, chi-square test and Fisher's exact test were performed.
At baseline, comparing indices of sodium, phosphorus, calcium, BUN, and IWG using the chi-square test, and potassium and albumin with Fisher's exact test showed that the differences in these indices were not statistically significant [Tables 2 and 3] in either group.
The goal of the study was to identify relationships between variables; a Fisher's Exact test was deemed the most appropriate test to run for this particular study given the relatively small sample size.
The Fisher's exact test, was used to compare between the 2 groups; for descriptive sample data, 95% confidence interval (CI) were calculated.
The Fisher's exact test and Mann-Whitney test were used for comparative studies.
Categorical variables were compared using a Chi-square test or Fisher's exact test. Midterm survival was demonstrated by Kaplan-Meier survival curves.
Results: Using analysis of variance (ANOVA) for continuous variables and Fisher's Exact Test for categorical variables, there were no statistically significant differences in demographics between the groups.
No statistical assumptions are needed for a Fisher's Exact Test except for computational ability and time.
Comparisons were tested at 5% level of significance using independent sample /-test, test, Fisher's exact test, and one-way analysis of variance (ANOVA) with LSD post hoc test where appropriate.