This file, as the Fisher's exact test, performs the exact probability test for a table of frequency data cross-classified according to two categorical variables, each of which has two levels or subcategories (2x2). It is a non-parametric statistical test used to determine if there are nonrandom associations between the two categorical variables. Barnard's exact test is used to calculate an exact P-value with small number of expected frequencies, for which the Chi-square test is not appropriate (in case the total number of observations is less than 20 or the number of frequency cells are less than 5). The test was proposed by G. A. Barnard in two papers (1945 and 1947). While Barnard's test seems like a natural test to consider, it's not at all commonly used. This probably due that it is a little unknown.
Perhaps due to its computational difficulty it is not widely used until recently, where the computers make it feasible. It is considering that the Barnard's exact test is more powerful than the Fisher's one.
It needs to inputs the a,b,c,d -observed frequency cells.
The output is a table with the Wald statistic, nuisance parameter and P-value. Also a plot of the nuisance parameter PI against the corresponding P-value for all the PI in (0, 1). It shows the maximized PI where it attains the P-value.For a least conflict with figure, press the left mouse button on the legend and drag to the desired location. |
