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The logrank test, or log-rank test, is a hypothesis test to compare the survival distributions of two samples. It is a nonparametric test and appropriate to use when the data are right skewed and censored (technically, the censoring must be non-informative).
Let () denote the deterministic communication complexity of a function, and let denote the rank of its input matrix (over the reals). Since every protocol using up to c {\displaystyle c} bits partitions M f {\displaystyle M_{f}} into at most 2 c {\displaystyle 2^{c}} monochromatic rectangles, and each of these has rank at most 1,
[1] [2] Choosing the right statistical test is not a trivial task. [1] The choice of the test depends on many properties of the research question. The vast majority of studies can be addressed by 30 of the 100 or so statistical tests in use .
The researcher indicates the probability of this sample difference being due to chance by reporting the probability associated with some test statistic. [8] For instance, the from the Cox-model or the log-rank test might then be used to assess the significance of any differences observed in these survival curves. [9]
The Wilcoxon signed-rank test is a non-parametric rank test for statistical hypothesis testing used either to test the location of a population based on a sample of data, or to compare the locations of two populations using two matched samples. [1] The one-sample version serves a purpose similar to that of the one-sample Student's t-test. [2]
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