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The phrase "accurate sample size for" is correct and usable in written English.
It can be used in contexts related to research, statistics, or data analysis when discussing the appropriateness of the number of observations or participants in a study.
Example: "To ensure the validity of our findings, we need to determine the accurate sample size for our survey."
Alternatives: "appropriate sample size for" or "correct sample size for".
Exact(1)
First, there might have been sampling bias since all participants were recruited from a single hospital and accurate sample size for this study was not calculated.
Similar(59)
The sample size was determined a priori because no studies were available to calculate an accurate sample size.
It will provide data on recruitment to enable an accurate estimation of sample size for a planned randomised controlled trial.
One of the main objectives of this feasibility study is to provide data on recruitment and to enable an accurate estimation of sample size for a planned RCT.
While this recommendation works at most reasonable orangutan densities, at very low orangutan densities, surveying a somewhat larger area may be necessary to obtain a large enough sample size for accurate estimation.
A sample size estimate was not conducted on the pilot study data, given the advice of Kraemer and colleagues that this is not an accurate means of estimating the required sample size for a large randomised controlled trial [ 55].
The thumb rule for a good sample size for SEM is more than 200, a more accurate estimation being 20 subjects for every variable in the model.
Sample size for each species, n = 1.
Absence of such information hinders accurate determination of sample sizes for study design, grant applications, and meta-analyses of research and whether studies were adequately powered to detect effects of interest.
The common nonparametric procedures such as the Wald- or ANOVA-type tests, however, have drawbacks since they usually require large sample sizes for accurate test decisions.
Our results show that i) model selection and parameter estimation improve with larger sample sizes and ii) consistent with previous work [ 19, 20], recent demographic events are more challenging and require substantially larger sample sizes for accurate inference.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com