NQuery Sample Size Software: Difference between revisions

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{{Short description|Clinical trial design platform}}

{{advert|date=May 2018}}

{{Lowercase title}}

{{Infobox Softwaresoftware

| name = nQuery Sample Size Software

| logo = NQuery_Powering_Sample_Size.jpg

| logo alt = nQuery Sample Size Software logo

| genre = [[Sample size determination|Sample Size]]

[[Statistical power|Statistical Power Calculation]] [[Statistical hypothesis testing|Statistical Hypothesis Testing]] [[Adaptive clinical trial|Adaptive Clinical Trial Design]]

| developer = [[Statsols]]

| latest release version = nQuery Advanced 8.5.27

| license = [[Proprietary software|Proprietary]]

| website = {{URL|www.statsols.com}}

}}

'''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 Biostatisticiansbiostatisticians to calculate [[Sample size determination|Samplesample size]] and [[Statisticalstatistical power]] for [[Adaptive clinical trial|adaptive clinical trial design.]] nQuery is proprietary software developed and distributed by [[Statsols]]. nQueryThe software includes calculations for 1000+over 1,000 sample sizesizes and power scenarios.

==nQuery historyHistory==

[[Janet D. Elashoff|Janet Dixon Elashoff]], creator of nQuery, is a now-retired American statistician and daughter of the mathematician and statistician [[Wilfrid Dixon|Wilfrid Joseph Dixon]], creator of BMDP. J. Elashoff is also the retired Director of the Division of Biostatistics, [[Cedars-Sinai Medical Center]]. While at [[University of California, Los Angeles|UCLA]] and Cedars-Sinai during the 1990s, she wrote the program nQuery Sample Size Software (then known asnamed nQuery Advisor). This software quickly became widely used to estimate the sample size requirements for pharmaceutical testingtrials. and sheShe joined the company Statistical Solutions LLC in order to commercialize it.<ref name=cherfriis>{{citation|title=Introductory Biostatistics for the Health Sciences: Modern Applications Including Bootstrap|series=Wiley series in probability and statistics|first1=Michael R.|last1=Chernick|first2=Robert H.|last2=Friis|publisher=John Wiley & Sons|year=2003|isbn=9780471458654|page=360|url=https://books.google.com/books?id=QRwuz6yA97oC&pg=PA360}}</ref>

In June 2020, nQuery was acquired by Insightful Science.<ref>{{cite press release |title=Insightful Science Acquires nQuery, Builds on Portfolio of Category-Leading Scientific Software Solutions |url=https://www.prnewswire.com/news-releases/insightful-science-acquires-nquery-builds-on-portfolio-of-category-leading-scientific-software-solutions-301068141.html}}</ref>

==nQuery featured in scientific journals ==

{{Puffery}}<!-- All this is showing that this word is popular in searches. It doesn't show that anything significant is actually discussed in these articles or how many articles are in peer review journals or how many conclusions have been invalidated by other articles. -->

There are over 6,000 scientific studies that feature nQuery. These are available to the public for educational and research purposes.<ref>https://scholar.google.com/scholar?start=0&q=%22nquery%22</ref> 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.<ref>https://www.ncbi.nlm.nih.gov/pmc/?term=nquery</ref>

==Uses ==

== Frequentist and Bayesian statistics ==

nQuery is used for [[Adaptive clinical trial|Adaptiveadaptive clinical trial design.]] Trials with an adaptive design arehave been reported to be often more efficient, informative, and ethical than trials with a traditional fixed design sincebecause they often make better use ofconserve resources such as time and money, and mightoften require fewer participants. <ref>{{Cite journal | doi=10.1186/s12916-018-1017-7| pmid=29490655| pmc=5830330| title=Adaptive designs in clinical trials: Why use them, and how to run and report them| year=2018| last1=Pallmann | first1=Philip| |last2=Bedding| |first2=Alun W.| |last3=Choodari-Oskooei| |first3=Babak| |last4=Dimairo| |first4=Munyaradzi| |last5=Flight | first5=Laura| |last6=Hampson| |first6=Lisa V. | last7=Holmes| |first7=Jane| |last8=Mander| |first8=Adrian P.| |last9=Odondi | first9=Lang'o| |last10=Sydes| |first10=Matthew R.| |last11=Villar| |first11=Sofía S. |year=2018 |title=Adaptive designs in clinical trials: Why use them, and how to run and report them |journal=BMC Medicine |volume=16 |issue=1 |pages=29 |doi=10.1186/s12916-018-1017-7 |pmc=5830330 |pmid=29490655 |last12=Wason| |first12=James M. S.| |last13=Weir | first13=Christopher J.| |last14=Wheeler | first14=Graham M.| |last15=Yap| |first15=Christina| |last16=Jaki | first16=Thomas| journal=BMC Medicine| volumedoi-access=16|free issue=1| pages=29}}</ref>

nQuery allows researchers to apply both [[Frequentist inference|frequentist]] and [[Bayesian inference|Bayesian]] statistics to calculate the appropriate sample size for their study.<ref>{{Cite web | url=https://www.statsols.com/nquery/sample-size-procedures | title=What sample size and power analysis procedures you get in nQuery &#124; Sample Size Software &#124; Power Analysis Software}}</ref>

nQuery allows researchers to apply both [[Frequentist inference|frequentist]] and [[Bayesian inference|Bayesian]] statistics to calculate the appropriate sample size for their study.<ref>{{Cite web | url=https://www.statsols.com/nquery/sample-size-procedures | title=What sample size and power analysis procedures you get in nQuery &#124; Sample Size Software &#124; Power Analysis Software}}</ref>

== Adaptive clinical trial design ==

nQuery is used for [[Adaptive clinical trial|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. <ref>{{Cite journal | doi=10.1186/s12916-018-1017-7| pmid=29490655| pmc=5830330| title=Adaptive designs in clinical trials: Why use them, and how to run and report them| year=2018| last1=Pallmann| first1=Philip| last2=Bedding| first2=Alun W.| last3=Choodari-Oskooei| first3=Babak| last4=Dimairo| first4=Munyaradzi| last5=Flight| first5=Laura| last6=Hampson| first6=Lisa V.| last7=Holmes| first7=Jane| last8=Mander| first8=Adrian P.| last9=Odondi| first9=Lang'o| last10=Sydes| first10=Matthew R.| last11=Villar| first11=Sofía S.| last12=Wason| first12=James M. S.| last13=Weir| first13=Christopher J.| last14=Wheeler| first14=Graham M.| last15=Yap| first15=Christina| last16=Jaki| first16=Thomas| journal=BMC Medicine| volume=16| issue=1| pages=29}}</ref>

==References==

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==External links==

*[https://www.statsols.com/ Official Statsols Page for nQuery Sample Size Software]

[[Category:Sampling (statistics)]]