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Biometrics 58, 48 57] used mean survival time and pointwise survival probability to compare treatment strategies.
The data were analyzed using the analysis of probability to compare the groups (arthritic and non-arthritic women).
Wilcoxon rank-sum tests to compare medians, and Fisher's exact test of probability to compare proportions were used, as appropriate, to identify associations.
Analysis of variance was conducted by Gabriel's t-test at 5% level of probability to compare mean values.
Then, the Mann–Whitney U test was evaluated by the Monte Carlo method to compute two-sided probability to compare the results of Group 2, Group 3 and Group 4 with Group 1.
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This study included hospital-level data (survival probabilities) to compare different properties of hospital performance.
We implemented and evaluated two methods to generate boundary curves from the boundary probabilities to compare the necessary complexity required to compute the final boundaries.
First, in aggregate analyses, we calculated a series of conditional probabilities to compare the likelihood of a subject pulling the prosocial option on a trial given that her partner pulled the prosocial option or the selfish option on previous trials.
Furthermore, we can use these probability limits to compare the relative bias in the OLS and CE estimators.
Statistical analyses were performed by using a χ distribution with 1 df and the Fisher exact probability test to compare proportions between the 2 groups.
Steady-state and transition probabilities used to compare stochastic models of Simple Positive-ACK, PLO, and SRVF are derived from these traces.
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