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The logrank test statistic compares estimates of the hazard functions of the two groups at each observed event time. It is constructed by computing the observed and expected number of events in one of the groups at each observed event time and then adding these to obtain an overall summary across all-time points where there is an event.
Bowker's test of symmetry; Categorical distribution, general model; Chi-squared test; Cochran–Armitage test for trend; Cochran–Mantel–Haenszel statistics; Correspondence analysis; Cronbach's alpha; Diagnostic odds ratio; G-test; Generalized estimating equations; Generalized linear models; Krichevsky–Trofimov estimator; Kuder ...
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]
Survival models can be viewed as consisting of two parts: the underlying baseline hazard function, often denoted (), describing how the risk of event per time unit changes over time at baseline levels of covariates; and the effect parameters, describing how the hazard varies in response to explanatory covariates.
The one-sample Wilcoxon signed-rank test can be used to test whether data comes from a symmetric population with a specified center (which corresponds to median, mean and pseudomedian). [11] If the population center is known, then it can be used to test whether data is symmetric about its center. [12]
In some cases, one may wish to compare different Kaplan–Meier curves. This can be done by the log rank test, and the Cox proportional hazards test. Other statistics that may be of use with this estimator are pointwise confidence intervals, [13] the Hall-Wellner band [14] and the equal-precision band. [15]
The Wilcoxon signed-rank test is a nonparametric test of nonindependent data from only two groups. The Skillings–Mack test is a general Friedman-type statistic that can be used in almost any block design with an arbitrary missing-data structure. The Wittkowski test is a general Friedman-Type statistics similar to Skillings-Mack test. When the ...
The data for this test consists of two groups; and for each member of the groups, the outcome is ranked for the study as a whole. Kerby showed that this rank correlation can be expressed in terms of two concepts: the percent of data that support a stated hypothesis, and the percent of data that do not support it.