NQuery Sample Size Software

Last updated
nQuery
Developer(s) Statsols
Stable release
nQuery Advanced 8.7
Type Sample Size Statistical Power Calculation Statistical Hypothesis Testing Adaptive Clinical Trial Design
License Proprietary
Website 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 biostatisticians to calculate sample size and statistical power for adaptive clinical trial design. nQuery is proprietary software developed and distributed by Statsols. The software includes calculations for over 1,000 sample sizes and power scenarios.

Contents

History

Janet Dixon Elashoff, creator of nQuery, is a retired American statistician and daughter of the mathematician and statistician Wilfrid Joseph Dixon, creator of BMDP. 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 named nQuery Advisor). This software quickly became widely used to estimate the sample size requirements for pharmaceutical trials. She joined the company Statistical Solutions LLC in order to commercialize it. [1]

In June 2020, nQuery was acquired by Insightful Science. [2]

Uses

nQuery is used for adaptive clinical trial design. Trials with an adaptive design have been reported to be more efficient, informative, and ethical than trials with a traditional fixed design because they conserve resources such as time and money and often require fewer participants. [3]

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

Related Research Articles

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means.

Biostatistics is a branch of statistics that applies statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments, the collection and analysis of data from those experiments and the interpretation of the results.

<span class="mw-page-title-main">Meta-analysis</span> Statistical method that summarizes data from multiple sources

A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. It is thus a basic methodology of metascience. Meta-analytic results are considered the most trustworthy source of evidence by the evidence-based medicine literature.

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<span class="mw-page-title-main">Mathematical statistics</span> Branch of statistics

Mathematical statistics is the application of probability theory, a branch of mathematics, to statistics, as opposed to techniques for collecting statistical data. Specific mathematical techniques which are used for this include mathematical analysis, linear algebra, stochastic analysis, differential equations, and measure theory.

<span class="mw-page-title-main">David Spiegelhalter</span> English statistician (born 1953)

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In statistics, sequential analysis or sequential hypothesis testing is statistical analysis where the sample size is not fixed in advance. Instead data are evaluated as they are collected, and further sampling is stopped in accordance with a pre-defined stopping rule as soon as significant results are observed. Thus a conclusion may sometimes be reached at a much earlier stage than would be possible with more classical hypothesis testing or estimation, at consequently lower financial and/or human cost.

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BMDP was a statistical package developed in 1965 by Wilfrid Dixon at the University of California, Los Angeles. The acronym stands for Bio-Medical Data Package, the word package was added by Dixon as the software consisted of a series of programs (subroutines) which performed different parametric and nonparametric statistical analyses.

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Paul Meier was a statistician who promoted the use of randomized trials in medicine.

<span class="mw-page-title-main">PS Power and Sample Size</span>

PS is an interactive computer program for performing statistical power and sample size calculations.

Janet Dixon Elashoff is a retired American statistician, formerly the director of biostatistics for Cedars-Sinai Medical Center and professor of biomathematics at the University of California, Los Angeles.

<span class="mw-page-title-main">Nancy Flournoy</span> American statistician

Nancy Flournoy is an American statistician. Her research in statistics concerns the design of experiments, and particularly the design of adaptive clinical trials; she is also known for her work on applications of statistics to bone marrow transplantation, and in particular on the graft-versus-tumor effect. She is Curators' Distinguished Professor Emeritus of Statistics at the University of Missouri.

<span class="mw-page-title-main">Statsols</span>

Statsols is the producer and distributor of the proprietary nQuery sample size software.

<span class="mw-page-title-main">Adaptive design (medicine)</span> Concept in medicine referring to design of clinical trials

In an adaptive design of a clinical trial, the parameters and conduct of the trial for a candidate drug or vaccine may be changed based on an interim analysis. Adaptive design typically involves advanced statistics to interpret a clinical trial endpoint. This is in contrast to traditional single-arm clinical trials or randomized clinical trials (RCTs) that are static in their protocol and do not modify any parameters until the trial is completed. The adaptation process takes place at certain points in the trial, prescribed in the trial protocol. Importantly, this trial protocol is set before the trial begins with the adaptation schedule and processes specified. Adaptions may include modifications to: dosage, sample size, drug undergoing trial, patient selection criteria and/or "cocktail" mix. The PANDA provides not only a summary of different adaptive designs, but also comprehensive information on adaptive design planning, conduct, analysis and reporting.

Guosheng Yin is a statistician, data scientist, educator and researcher in Biostatistics, Statistics, machine learning, and AI. Presently, Guosheng Yin is Chair in Statistics in Department of Mathematics at Imperial College London. Previously, he served as the Head of Department and the Patrick S C Poon Endowed Chair in Statistics and Actuarial Science, at the University of Hong Kong. Before he joined the University of Hong Kong, Yin worked at the University of Texas M.D. Anderson Cancer Center till 2009 as a tenured Associate Professor of Biostatistics.

Tim Hesterberg is an American statistician. He is a Fellow of the American Statistical Association and currently works as a staff data scientist at Instacart.

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. "Insightful Science Acquires nQuery, Builds on Portfolio of Category-Leading Scientific Software Solutions" (Press release).
  3. 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, Sofía 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.
  4. "What sample size and power analysis procedures you get in nQuery | Sample Size Software | Power Analysis Software".