The phrase "a plausible value for" is correct and usable in written English.
It can be used when discussing a reasonable or believable estimate or figure in a specific context, such as statistics or research.
Example: "After analyzing the data, we determined a plausible value for the average temperature increase over the next decade."
Alternatives: "a reasonable estimate for" or "a credible figure for".
The vectors provide a plausible value for each of the PISA 2006 reporting scales.
To obtain a plausible value for ψ max, we estimated ψ s in (19) pretending either sex or age was the unobserved covariate x.
Thus to obtain a plausible value for ψ max, we suggest estimating ψ s, as defined in (19), based on observed covariates.
As our multi-unit recordings were mostly from two or three neurons, we divided the medians of the SRs by 2.5 (on average) to have a plausible value for comparisons of our data with single-unit recordings in other mammals.
To bound the overall bias Σ s ψ s ε s pr (S = s), we specify an upper bound for ε s based only on the fraction missing and a plausible value for the maximum of ψ s based on the estimates of ψ s if an observed covariate were missing.
We assumed a unique (and plausible) value for the overall residual variance in order to allow for a direct comparison and interpretations of the results.
Essentially, MI is a means for representing uncertainty in missing data, by producing a distribution of plausible values for a missing variable in a record, given the values of that record's non-missing covariates.
The guidelines, for example, called for agencies to present a range of "plausible values" for the risk posed by a particular chemical, and then to calculate a "central" or "expected" estimate of risk.
The nomogram proposed in this paper is such a tool and is particularly useful to study sensitivity to the prior probability of the null hypothesis, as illustrated in Figure 2. Combined with a precise P value we obtain a range of plausible values for the posterior probability of the null hypothesis, which is far easier to interpret than the P value itself.
A 95% confidence interval was used to provide a range of plausible values for these parameters, and to investigate the likelihood of specific exposure groups overlapping with the larger exposure group of interest.
Making the "right" choice is not easy, and we suggest using a range of "plausible" values for sensitivity checks.
