nQuery Sample Size Software

nQuery is a clinical trial design platform used for the design and monitoring of adaptive, group sequential and fixed sample size trials. It is most commonly used by Biostatisticians to calculate Sample size and Statistical power for adaptive clinical trial design. nQuery is proprietary software developed and distributed by Statsols. nQuery includes calculations for 1000+ sample size and power scenarios.

nQuery Sample Size Software
Developer(s)Statsols
Stable release
nQuery Advanced 8.5.2
TypeSample Size Statistical Power Calculation Statistical Hypothesis Testing Adaptive Clinical Trial Design
LicenseProprietary
Websitewww.statsols.com

nQuery History

Janet Dixon Elashoff is a now-retired American statistician and daughter of the mathematician and statistician Wilfrid Joseph Dixon, creator of BMDP. J. Elashoff is also the retired Director of the Division of Biostatistics, Cedars-Sinai Medical Center. While at UCLA and Cedars-Sinai during the 1990s, she wrote the program nQuery Sample Size Software (then known as nQuery Advisor). This quickly became widely used to estimate the sample size requirements for pharmaceutical testing and she joined the company Statistical Solutions LLC to commercialize it.[1]

There are over 6,000 scientific studies that feature nQuery. These are available to the public for educational and research purposes.[2] The US National Institutes of Health Library lists over 895 published studies that used nQuery for sample size calculation for clinical trial design. These are freely available to the public to review.[3]

Frequentist and Bayesian statistics

nQuery allows researchers to apply both frequentist and Bayesian statistics to calculate the appropriate sample size for their study.[4]

Adaptive Clinical Trial Design

nQuery is used for Adaptive clinical trial design. Trials with an adaptive design are reported to be often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. [5]

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gollark: There's already APRS and such so maybe APIONET could interop with that.
gollark: PSK31 or something.

References

  1. Chernick, Michael R.; Friis, Robert H. (2003), Introductory Biostatistics for the Health Sciences: Modern Applications Including Bootstrap, Wiley series in probability and statistics, John Wiley & Sons, p. 360, ISBN 9780471458654
  2. https://scholar.google.com/scholar?start=0&q=%22nquery%22
  3. https://www.ncbi.nlm.nih.gov/pmc/?term=nquery
  4. "What sample size and power analysis procedures you get in nQuery | Sample Size Software | Power Analysis Software".
  5. Pallmann, Philip; Bedding, Alun W.; Choodari-Oskooei, Babak; Dimairo, Munyaradzi; Flight, Laura; Hampson, Lisa V.; Holmes, Jane; Mander, Adrian P.; Odondi, Lang'o; Sydes, Matthew R.; Villar, SofĂ­a S.; Wason, James M. S.; Weir, Christopher J.; Wheeler, Graham M.; Yap, Christina; Jaki, Thomas (2018). "Adaptive designs in clinical trials: Why use them, and how to run and report them". BMC Medicine. 16 (1): 29. doi:10.1186/s12916-018-1017-7. PMC 5830330. PMID 29490655.
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