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The survey data can demonstrate the probability distribution of farm-level yields in the region.
Figures 5 and 6 demonstrate the probability of full coverage versus number of sensors deployed in the region.
(A) Schematic diagram of the experiment process; (B) TH-immunoreactive cell bodies in SN of different groups of rats; (C) Quantification of DA neurons loss among different groups of rats, *P < 0.05 (n = 10 in each group); (D) The Kaplan-Meier curves demonstrate the probability of disease onset, *P < 0.05.
These curves demonstrate the probability for a treatment to be cost-effective, depending on the willingness to pay by the healthcare institution.
The cost-effectiveness acceptability curve [ 57] was then constructed to demonstrate the probability of being cost-effective for each strategy in the 10,000 iterations at each level of the ceiling ratio.
Results of probabilistic analysis are also presented in the form of cost-effectiveness acceptability curves (CEACs), which demonstrate the probability of supported employment being cost-effective relative to standard care at different levels of willingness to pay per extra unit of benefit, that is, at different cost-effectiveness thresholds (Fenwick et al., 2001).
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Figure 6 demonstrates the probability of repetition of keys.
The CEAC (Fig. 2) demonstrates the probability of the intervention being cost-effective at varying willingness-to-pay thresholds per improvement in QALYs.
1 4 demonstrates the probability density function of the log-logistic, lognormal, Pearson 5 and Pearson 6 distributions and investigations were accordingly made with these functions.
Kaplan-Meier survivorship analysis graphically demonstrates the probability of any technique or procedure not failing at a particular time [ 1, 10].
CEACs are shown in Fig. 5 demonstrating the probability that a strategy is cost-effective, given different values of willingness to pay for a QALY.
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CEO of Professional Science Editing for Scientists @ prosciediting.com