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Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).
SPSS 6.1 Exact test for Windows. Prentice Hall. Mehta CR and Patel NR. 1983. A network algorithm for performing Fisher's exact test in rxc contingency tables. Journal of the American Statistical Association, 78(382): 427–434. Mehta CR and Patel NR. 1995. Exact logistic regression: theory and examples. Statistics in Medicine, 14: 2143–2160.
Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).
An alternative exact test, Barnard's exact test, has been developed and proponents [22] of it suggest that this method is more powerful, particularly in 2×2 tables. [23] Furthermore, Boschloo's test is an exact test that is uniformly more powerful than Fisher's exact test by construction. [24]
SPSS: A dialog box for Propensity Score Matching is available from the IBM SPSS Statistics menu (Data/Propensity Score Matching), and allows the user to set the match tolerance, randomize case order when drawing samples, prioritize exact matches, sample with or without replacement, set a random seed, and maximize performance by increasing ...
Fisher's exact test, based on the work of Ronald Fisher and E. J. G. Pitman in the 1930s, is exact because the sampling distribution (conditional on the marginals) is known exactly. This should be compared with Pearson's chi-squared test , which (although it tests the same null) is not exact because the distribution of the test statistic is ...
[citation needed] An exact binomial test can then be used, where b is compared to a binomial distribution with size parameter n = b + c and p = 0.5. Effectively, the exact binomial test evaluates the imbalance in the discordants b and c. To achieve a two-sided P-value, the P-value of the extreme tail should be multiplied by 2. For b ≥ c:
In fact, it can be shown that the unconditional analysis of matched pair data results in an estimate of the odds ratio which is the square of the correct, conditional one. [2] In addition to tests based on logistic regression, several other tests existed before conditional logistic regression for matched data as shown in related tests. However ...