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Exact(6)
We assumed a uniform prior distribution for the surviving proportion for the new treatment and this distribution was updated as the study accrued patients.
Using this rule, we would have stopped the study if the surviving proportion was not greater than 0/10, 1/17, 2/23, 4/33 or 5/38.
The probability of early stopping was 99% for a true surviving proportion of 0.05, 88% for a proportion of 0.1, 31% for a proportion of 0.2 and 6% for a proportion of 0.3.
The study would have been stopped at any time if we had determined there was a less than 1% chance that the surviving proportion in the experimental arm of the study was less than that from the historical control group.
To ascertain that there were no systematic departures of our lifetime data from the Weibull distribution, we plotted the logarithm of the negative log of the surviving proportion (i.e. flies alive after a given time point) in each infected group against the log of time, and found the plots to be linear (data not shown).
The objective of the Markov model is to estimate the long-term health and cost consequences for the model cohort over the next 30 years (i.e. the surviving proportion of cohort would be 41 years old at the end of the last Markov cycle).
Similar(54)
The surviving proportions of cells as compared to the untreated controls were determined using EZ4U according to the instructions of the manufacturer.
Our findings are consistent with this study: compared with the septic AKI patients who survived, proportion of receiving RRT was significantly higher in who died (43.13% versus 29.35%, P = 0.007).
Several (proxy) measures of reproductive success are available, including number of children ever born, number of surviving children, proportion of married offspring and potential proxies of mate value, such as number of marriages and age at first marriage.
* Outcome = proportion surviving; † Outcome = proportion not dead or dependent (defined as mRS<4).
Plotting the cumulative proportion surviving against the survival times gives the stepped survival curve shown in Fig. 1.
Related(20)
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