Article
Multidisciplinary Sciences
Scott D. Foster, Pierre Feutry, Peter Grewe, Campbell Davies
Summary: The amount of information needed for analytical tasks in population genetics depends on the number of individuals sampled and the genetic markers measured, with different tasks requiring varying numbers of individuals and genetic markers. Real data from sampling locations across the tropical Pacific Ocean were used to assess genetic differences and sample sizes for tasks such as profile testing, stock delineation, and assignment of individuals to stocks in yellowfin tuna populations. Task-specific sample size requirements were determined to help guide the design of molecular ecological surveys for yellowfin tuna.
Review
Public, Environmental & Occupational Health
Katie M. O'Brien, Kaitlyn G. Lawrence, Alexander P. Keil
Summary: Nested case-control or case-cohort sampling methods in cohort studies can reduce costs and provide flexibility and efficiency. However, these methods are underutilized in epidemiologic literature. Recent advances in statistical methods and software have made analysis of case-cohort data easier and applicable to a variety of research questions and populations.
Review
Medicine, General & Internal
Xinlian Zhang, Phillipp Hartmann
Summary: The calculation of required sample size is crucial in designing both animal and human studies. This review defines key terms related to sample size determination, such as mean, standard deviation, statistical hypothesis testing, type I/II error, power, direction of effect, effect size, expected attrition, corrected sample size, and allocation ratio. It also provides practical examples of sample size calculations based on pilot studies, similar larger studies, or estimated effect sizes per Cohen and Sawilowsky if no previous studies are available.
FRONTIERS IN MEDICINE
(2023)
Article
Health Care Sciences & Services
Lin Naing, Rusli Bin Nordin, Hanif Abdul Rahman, Yuwadi Thein Naing
Summary: This article introduces the methods and important parameters for sample size calculation in prevalence studies using calculators. It discusses the correct selection of parameters and reporting issues. By demonstrating the use of a purposely-designed calculator, it helps researchers make informed decisions and prepare appropriate reports.
BMC MEDICAL RESEARCH METHODOLOGY
(2022)
Article
Multidisciplinary Sciences
Amrit Sudershan, Kanak Mahajan, Rakesh K. Panjaliya, Manoj K. Dhar, Parvinder Kumar
Summary: Sampling methods for studying population behavior are uncertain and require representative samples for generalization. Sample size greatly affects the detection of research effects, with smaller samples having lower statistical power and higher risk of missing underlying differences. This study provides a calculation method for determining sample availability during research.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Katharina T. Schmid, Barbara Hoellbacher, Cristiana Cruceanu, Anika Boettcher, Heiko Lickert, Elisabeth B. Binder, Fabian J. Theis, Matthias Heinig
Summary: The authors present a statistical framework for informed multi-sample experimental design in scRNASeq data to reduce unnecessary costs and maximize data utility. The study shows that shallow sequencing of high numbers of cells leads to higher overall power than deep sequencing of fewer cells. The model is implemented as an R package and accessible as a web tool.
NATURE COMMUNICATIONS
(2021)
Article
Social Sciences, Mathematical Methods
Nathaniel Josephs, Dennis M. Feehan, Forrest W. Crawford
Summary: The network scale-up method is a survey-based approach used to estimate the size of hidden subgroups in a general population. It is widely used in estimating the size of important risk groups, but there are currently no guidelines for calculating the minimum sample size. This study provides a sample size formula that is applicable to any network scale-up survey and demonstrates its effectiveness through analytical and simulation methods.
SOCIOLOGICAL METHODS & RESEARCH
(2022)
Article
Biology
Armando Turchetta, Erica E. M. Moodie, David A. Stephens, Sylvie D. Lambert
Summary: This study provides a Bayesian approach for calculating sample size, allowing for more accurate and robust estimates that account for uncertainty in inputs through the "two priors" method. Compared to standard frequentist formulae, this methodology relies on fewer assumptions, incorporates pre-trial knowledge, and shifts the focus to the MDD.
Article
Biochemical Research Methods
Tao Wang, Yongzhuang Liu, Quanwei Yin, Jiaquan Geng, Jin Chen, Xipeng Yin, Yongtian Wang, Xuequn Shang, Chunwei Tian, Yadong Wang, Jiajie Peng
Summary: QTL analyses of multiomic molecular traits play a significant role in inferring the functional effects of genome variants. However, limited study sample size restricts QTL discovery and leads to missing molecular trait-variant associations. This study presents xQTLImp, a computational framework, to efficiently impute missing molecular QTL associations. Experimental results demonstrate high imputation accuracy and novel QTL discovery ability of xQTLImp.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Quantum Science & Technology
Mark Bun, Robin Kothari, Justin Thaler
Summary: New quantum algorithms have been proposed for evaluating composed functions, and tight composition theorems for linear-size depth-d AC(0) circuits have been proven. Additionally, it has been shown that AC(0) circuits of depth d+1 require a larger size to compute the Inner Product function, even on average.
Article
Psychology
Marton Kovacs, Don van Ravenzwaaij, Rink Hoekstra, Balazs Aczel
Summary: In this tutorial, a web app and R package are introduced, providing nine different procedures to determine and justify the sample size for independent two-group study designs. Each procedure's most important decision points are highlighted, and example justifications are suggested.
ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE
(2022)
Review
Biology
Cristina Politi, Stefanos Roumeliotis, Giovanni Tripepi, Belinda Spoto
Summary: Genetic association studies are useful for identifying genes that contribute to complex disorders. However, inadequate sample size calculation can lead to unreliable results. This article discusses the importance of considering statistical and genetic parameters in sample size calculation and provides a practical approach using genetic software to determine the appropriate sample size for a hypothetical gene-disease association study.
Article
Public, Environmental & Occupational Health
Jie K. Hu, Kwun C. G. Chan, David J. Couper, Norman E. Breslow
Summary: The case-cohort design reduces the cost of epidemiological studies by selecting more informative participants in the full cohort for expensive variable measurements. Additive hazards models are rarely used in case-cohort studies due to software and application limitations, but a newly developed method and R package now allow for their application. The method enhances precision by incorporating auxiliary information from the full cohort and can identify synergistic effects between biomarkers in predicting coronary heart disease risk, which traditional risk factors may overlook.
EUROPEAN JOURNAL OF EPIDEMIOLOGY
(2021)
Article
Biology
Bonnie E. Shook-Sa, Michael G. Hudgens
Summary: This paper investigates the impact of inverse probability of treatment weights (IPTWs) on sample size calculations when estimating causal effects. It presents a simplified design effect approximation method and discusses practical considerations.
Article
Health Care Sciences & Services
T. J. Cole
Summary: The study fitted growth reference curves for 6878 boys aged 0-21 years using GAMLSS method, exploring the impact of sample size and sample composition on precision. It concluded that optimally designed studies need 7000-25000 subjects per sex to achieve constant precision across the age range.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2021)
