Relevant bibliographies by topics / Optimal Sample Size

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Optimal Sample Size'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Optimal Sample Size"

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Cressie, Noel, Jonathan Biele, and Peter B. Morgan. "Sample-size-optimal sequential testing." Journal of Statistical Planning and Inference 39, no. 2 (1994): 305–27. http://dx.doi.org/10.1016/0378-3758(94)90211-9.

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Müller, Peter, Giovanni Parmigiani, Christian Robert, and Judith Rousseau. "Optimal Sample Size for Multiple Testing." Journal of the American Statistical Association 99, no. 468 (2004): 990–1001. http://dx.doi.org/10.1198/016214504000001646.

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Stec, Daniel, Piotr Gąsiorek, Witold Morek, et al. "Estimating optimal sample size for tardigrade morphometry." Zoological Journal of the Linnean Society 178, no. 4 (2016): 776–84. http://dx.doi.org/10.1111/zoj.12404.

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Ito, H., W. W. Wallender, and N. S. Raghuwanshi. "Optimal Sample Size for Furrow Irrigation Design." Biosystems Engineering 91, no. 2 (2005): 229–37. http://dx.doi.org/10.1016/j.biosystemseng.2005.02.009.

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Schwertman, Neil C., and David K. Smith. "Optimal Sample Size for Detection of an Infestation." Journal of Agricultural, Biological, and Environmental Statistics 3, no. 4 (1998): 359. http://dx.doi.org/10.2307/1400570.

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Annis, Charles, Luca Gandossi, and Oliver Martin. "Optimal sample size for probability of detection curves." Nuclear Engineering and Design 262 (September 2013): 98–105. http://dx.doi.org/10.1016/j.nucengdes.2013.03.059.

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Barenghi, Carlo F., Amir D. Aczel, and Roger J. Best. "Determining the optimal sample size for decision making." Journal of Statistical Computation and Simulation 24, no. 2 (1986): 135–45. http://dx.doi.org/10.1080/00949658608810896.

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Kadane, Joseph B. "Optimal sample size for risk-compensated survey assessment." Law, Probability and Risk 16, no. 4 (2017): 151–62. http://dx.doi.org/10.1093/lpr/mgx013.

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Katsis, Athanassios. "CALCULATING THE OPTIMAL SAMPLE SIZE FOR BINOMIAL POPULATIONS." Communications in Statistics - Theory and Methods 30, no. 4 (2001): 665–78. http://dx.doi.org/10.1081/sta-100002143.

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Walter, S. D., M. Eliasziw, and A. Donner. "Sample size and optimal designs for reliability studies." Statistics in Medicine 17, no. 1 (1998): 101–10. http://dx.doi.org/10.1002/(sici)1097-0258(19980115)17:1<101::aid-sim727>3.0.co;2-e.

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Dissertations / Theses on the topic "Optimal Sample Size"

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Medeiros, José António Amaro Correia. "Optimal sample size for assessing bacterioneuston structural diversity." Master's thesis, Universidade de Aveiro, 2011. http://hdl.handle.net/10773/10901.

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Mestrado em Biologia Aplicada - Microbiologia Clínica e Ambiental<br>The surface microlayer (SML) is located at the interface atmospherehydrosphere and is theoretically defined as the top millimeter of the water column. However, the SML is operationally defined according to the sampling method used and the thickness varies with weather conditions and organic matter content, among other factors. The SML is a very dynamic compartment of the water column involved in the process of transport of materials between the hydrosphere and the atmosphere. Bacterial communities inhabiting the SML (bacterioneuston) are expected to be adapted to the particular SML environment which is characterized by physical and chemical stress associated to surface tension, high exposure to solar radiation and accumulation of hydrophobic compounds, some of which pollutants. However, the small volumes of SML water obtained with the different sampling methods reported in the literature, make the sampling procedure laborious and time-consuming. Sample size becomes even more critical when microcosm experiments are designed. The objective of this work was to determine the smallest sample size that could be used to assess bacterioneuston diversity by culture independent methods without compromising representativeness and therefore ecological significance. For that, two extraction methods were tested on samples of 0,5 mL, 5 mL and 10 mL of natural SML obtained at the estuarine system Ria de Aveiro. After DNA extraction, community structure was assessed by DGGE profiling of rRNA gene sequences. The CTAB-extraction procedure was selected as the most efficient extraction method and was later used with larger samples (1 mL, 20 mL and 50 mL). The DNA obtained was once more analyzed by DGGE and the results showed that the estimated diversity of the communities does not increase proportionally with increasing sample size and that a good estimate of the structural diversity of bacterioneuston communities can be obtained with very small samples.<br>A microcamada superficial marinha (SML) situa-se na interface atmosferahidrosfera e teoricamente é definida como o milímetro mais superficial da coluna de água. Operacionalmente, a espessura da SML depende do método de amostragem utilizado e é também variável com outros fatores, nomeadamente, as condições meteorológicas e teor de matéria orgânica, entre outros. A SML é um compartimento muito dinâmico da coluna de água que está envolvida no processo de transporte de materiais entre a hidrosfera e a atmosfera. As comunidades bacterianas que habitam na SML são designadas de bacterioneuston e existem indícios de que estão adaptadas ao ambiente particular da SML, caracterizado por stresse físico e químico associado à tensão superficial, alta exposição à radiação solar e acumulação de compostos hidrofóbicos, alguns dos quais poluentes de elevada toxicidade. No entanto, o reduzido volume de água da SML obtidos em cada colheita individual com os diferentes dispositivos de amostragem reportados na literatura, fazem com que o procedimento de amostragem seja laborioso e demorado. O tamanho da amostra torna-se ainda mais crítico em experiências de microcosmos. O objectivo deste trabalho foi avaliar se amostras de pequeno volume podem ser usadas para avaliar a diversidade do bacterioneuston, através de métodos de cultura independente, sem comprometer a representatividade, e o significado ecológico dos resultados. Para isso, foram testados dois métodos de extracção em amostras de 0,5 mL, 5 mL e 10 mL de SML obtida no sistema estuarino da Ria de Aveiro. Após a extracção do DNA total, a estrutura da comunidade bacteriana foi avaliada através do perfil de DGGE das sequências de genes que codificam para a sub unidade 16S do rRNA. O procedimento de extracção com brometo de cetil trimetil de amônia (CTAB) foi selecionado como sendo o método de extração com melhor rendimento em termos de diversidade do DNA e mais tarde foi aplicado a amostras de maior dimensão (1 mL, 20 mL e 50 mL). O DNA obtido foi mais uma vez usado para análise dos perfis de DGGE de 16S rDNA da comunidade e os resultados mostraram que a estimativa da diversidade de microorganismos não aumentou proporcionalmente com o aumento do tamanho da amostra e que com amostras de pequeno volume podem ser obtidas boas estimativas da diversidade estrutural das comunidades de bacterioneuston.
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Thach, Chau Thuy. "Self-designing optimal group sequential clinical trials /." Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/9585.

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Takazawa, Akira. "Optimal decision criteria for the study design and sample size of a biomarker-driven phase III trial." Kyoto University, 2020. http://hdl.handle.net/2433/253492.

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Brungard, Colby W. "Alternative Sampling and Analysis Methods for Digital Soil Mapping in Southwestern Utah." DigitalCommons@USU, 2009. http://digitalcommons.usu.edu/etd/472.

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Digital soil mapping (DSM) relies on quantitative relationships between easily measured environmental covariates and field and laboratory data. We applied innovative sampling and inference techniques to predict the distribution of soil attributes, taxonomic classes, and dominant vegetation across a 30,000-ha complex Great Basin landscape in southwestern Utah. This arid rangeland was characterized by rugged topography, diverse vegetation, and intricate geology. Environmental covariates calculated from digital elevation models (DEM) and spectral satellite data were used to represent factors controlling soil development and distribution. We investigated optimal sample size and sampled the environmental covariates using conditioned Latin Hypercube Sampling (cLHS). We demonstrated that cLHS, a type of stratified random sampling, closely approximated the full range of variability of environmental covariates in feature and geographic space with small sample sizes. Site and soil data were collected at 300 locations identified by cLHS. Random forests was used to generate spatial predictions and associated probabilities of site and soil characteristics. Balanced random forests and balanced and weighted random forests were investigated for their use in producing an overall soil map. Overall and class errors (referred to as out-of-bag [OOB] error) were within acceptable levels. Quantitative covariate importance was useful in determining what factors were important for soil distribution. Random forest spatial predictions were evaluated based on the conceptual framework developed during field sampling.
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Kothawade, Manish. "A Bayesian Method for Planning Reliability Demonstration Tests for Multi-Component Systems." Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1416154538.

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Hathaway, John Ellis. "Determining the Optimum Number of Increments in Composite Sampling." BYU ScholarsArchive, 2005. https://scholarsarchive.byu.edu/etd/425.

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Composite sampling can be more cost effective than simple random sampling. This paper considers how to determine the optimum number of increments to use in composite sampling. Composite sampling terminology and theory are outlined and a model is developed which accounts for different sources of variation in compositing and data analysis. This model is used to define and understand the process of determining the optimum number of increments that should be used in forming a composite. The blending variance is shown to have a smaller range of possible values than previously reported when estimating the number of increments in a composite sample. Accounting for differing levels of the blending variance significantly affects the estimated number of increments.
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Vong, Camille. "Model-Based Optimization of Clinical Trial Designs." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-233445.

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General attrition rates in drug development pipeline have been recognized as a necessity to shift gears towards new methodologies that allow earlier and correct decisions, and the optimal use of all information accrued throughout the process. The quantitative science of pharmacometrics using pharmacokinetic-pharmacodynamic models was identified as one of the strategies core to this renaissance. Coupled with Optimal Design (OD), they constitute together an attractive toolkit to usher more rapidly and successfully new agents to marketing approval. The general aim of this thesis was to investigate how the use of novel pharmacometric methodologies can improve the design and analysis of clinical trials within drug development. The implementation of a Monte-Carlo Mapped power method permitted to rapidly generate multiple hypotheses and to adequately compute the corresponding sample size within 1% of the time usually necessary in more traditional model-based power assessment. Allowing statistical inference across all data available and the integration of mechanistic interpretation of the models, the performance of this new methodology in proof-of-concept and dose-finding trials highlighted the possibility to reduce drastically the number of healthy volunteers and patients exposed to experimental drugs. This thesis furthermore addressed the benefits of OD in planning trials with bio analytical limits and toxicity constraints, through the development of novel optimality criteria that foremost pinpoint information and safety aspects. The use of these methodologies showed better estimation properties and robustness for the ensuing data analysis and reduced the number of patients exposed to severe toxicity by 7-fold.  Finally, predictive tools for maximum tolerated dose selection in Phase I oncology trials were explored for a combination therapy characterized by main dose-limiting hematological toxicity. In this example, Bayesian and model-based approaches provided the incentive to a paradigm change away from the traditional rule-based “3+3” design algorithm. Throughout this thesis several examples have shown the possibility of streamlining clinical trials with more model-based design and analysis supports. Ultimately, efficient use of the data can elevate the probability of a successful trial and increase paramount ethical conduct.
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Fitton, N. V. "Why and How to Report Distributions of Optima in Experiments on Heuristic Algorithms." University of Cincinnati / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1006054556.

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Feijó, Sandra. "Técnicas para execução de experimentos sob ambiente protegido para a cultura da abobrinha italiana." Universidade Federal de Santa Maria, 2005. http://repositorio.ufsm.br/handle/1/3178.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico<br>In order to determinate technicals to execution trials in protected environments for italian pumpkin was accomplished an experiment, from 18/08/2003 to 07/12/2003, in the area of the Department of Fitotecnia UFSM, in plastic greenhouse, with four rows and each row consisted of twenty-four plants. A total of twenty-seven harvests were made, evaluating fruit weight with length ≥15cm. The sample soil was sampled before accomplishment the experiment; one sample point is equal to four sub sample. The Smith heterogeneity index was estimated using SMITH s method (1938) and optimum plot size using method modified maximum curvature (MEIER & LESSMAN, 1971). Estimate, for how long productive period of italian pumpkin, in plastic greenhouse, must be evaluated aiming to estimate the experimental error and the difference among four intervals of harvest, was the aim in order to first paper. The harvest and evaluation of the initial half of the productive period of Italian pumpkin in plastic greenhouse was sufficient to estimate the experimental error, using six plants by plot, to evaluate different intervals of harvest. Because of high experimental error, the evaluation of the Italian pumpkin production during all the productive period is not sufficient to differentiate four treatments of intervals of harvest. The aim the second paper, was evaluate the chemicals characteristics of the soil heterogeneity index under environmental protect and determinate sample size. The values the Smith heterogeneity index were considerate small. The optimum plot size was equal to one basic unit, in other words, one sample point. The sample size estimated was ten sample points for the half width of the confidence interval of 20%, to 5% of error probability. The third paper, aimed evaluate the Smith heterogeneity index in order to different intervals of the harvest of fruits in different levels of the accumulate harvests of italian pumpkin in greenhouse, estimate the optimum plot size and determinate the least significant differences within treatments with variation in the size plot and number of replications. The Smith heterogeneity index is smaller and the use of smaller plots with larger number of replications benefit the experimental precision. The optimum plot size in order to yield italian pumpkin varying between one and seven plants, promoted appropriate evaluation of the yield italian pumpkin in the different studied treatments. Plots with three plants and six replications is better in order conduction the experiments, with least significant differences within treatments (average percentage) in 75,94%.<br>Para se determinar técnicas para execução de experimentos, sob ambiente protegido, para a cultura da abobrinha italiana, foi realizado um experimento em estufa plástica no período de 18/08/2003 a 07/12/2003, em área pertencente ao Departamento de Fitotecnia, na UFSM, Santa Maria, RS. As mudas foram transplantadas para a estufa plástica com espaçamento de 0,80 m entre plantas e 1,0 m entre filas, totalizando 24 plantas por fila. Foram realizadas 27 colheitas de frutos,com comprimento ≥ 15 cm. As amostras de solo foram coletadas antes da implantação do experimento, cada ponto amostral era composto por quatro subamostras. O índice de heterogeneidade de Smith (b) foi estimado pelo método de SMITH (1938) e o tamanho ótimo de parcela através do método da máxima curvatura modificado (MEIER & LESSMAN, 1971). A estimativa do erro experimental e a diferença entre quatro intervalos de colheita foram avaliados no primeiro trabalho. A colheita e avaliação da metade inicial do período produtivo da abobrinha italiana em estufa de plástica foi suficiente para estimar o erro experimental, usando seis plantas por parcela, para avaliar diferentes intervalos de colheita. O objetivo do segundo trabalho, foi avaliar o índice de heterogeneidade de Smith das principais características químicas do solo, em estufa plástica, e determinar o tamanho de amostra. Para todas variáveis analisadas, o índice de heterogeneidade de Smith, foi próximo a zero e o tamanho ótimo de parcela, foi igual à uma unidade básica, ou seja, um ponto amostral. O tamanho de amostra estimado, foi de dez pontos amostrais, como representativo para todas as variáveis analisadas, com semiamplitude do intervalo de confiança da média em porcentagem, de 20% em nível 5% de probabilidade de erro. O terceiro trabalho teve por objetivos avaliar o índice de heterogeneidade de Smith da produção de abobrinha italiana, para os diferentes intervalos de colheita dos frutos, em diferentes níveis de colheitas acumuladas, em ambiente protegido; estimar o tamanho ótimo de parcela e determinar a diferença mínima significativa entre tratamentos, variando o tamanho da parcela e o número de repetições. Como conclusão, o índice de heterogeneidade de Smith, foi baixo e o tamanho ótimo de parcela para a produção total de abobrinha italiana varia entre uma e sete plantas, conforme a freqüência de colheitas. O uso de parcelas com três plantas, seis repetições é mais adequado e apresenta uma diferença mínima significativa entre tratamentos, em porcentagem da média, de 75,94%.
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Her, Chi-Way, and 何淇瑋. "The Optimal Sample Size For Interval Estimation Of Correlation Coefficient." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/20731985747790441131.

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碩士<br>國立交通大學<br>管理科學系所<br>99<br>As the degree of correlation between two variables is one of concern to many social science issues, thus using the sample correlation coefficient to infer population correlation coefficient is a common method. However, the decision of the optimum sample size for the entire study will save a lot of time and cost. Traditionally, the sample size determination in addition to hypothesis testing method, this research will introduce the expected interval length method and the expected interval coverage probability method. Expected interval coverage probability method is based on interval estimation, but it can adjust sample size strict and loose according to the different set coverage probability. In this dissertation, the SAS software is used to construct model, after finding the optimal sample size, we will select the sample size randomly from the two designed population, and observe the interval width and interval coverage probability composed of sample size whether consistent with our original set. The results shows: the expected interval length method will have a better simulation results only when the samples are large enough, and the expected interval coverage probability method will shows unstable when the population parameters very close to 0.
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Books on the topic "Optimal Sample Size"

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Baxter-Jones, Adam DG. Growth and maturation. Edited by Neil Armstrong and Willem van Mechelen. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198757672.003.0002.

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As children grow they increase in size and maturity. While growth refers to changes in size and complexity of tissue composition, maturation is the progressive achievement of adult status. A child’s growth status is an important determinant of current and lifelong health. Regular physical activity is required to obtain optimal growth. Normal healthy children show the same patterns of growth in terms of attainment of size and changes in proportionality. However, growth is not a linear process; the speed of statural growth decreases during infancy, is relatively constant during childhood, and accelerates during adolescence before slowing down in emerging adulthood. Although the patterns of growth are similar in all individuals, the timing and tempo of growth shows vast variability both within and between sexes. Thus it is important to remember that the effects of growth and maturation may mask or be greater than the effects of exercise.
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Najavits, Lisa M., and Melissa L. Anderson. Psychosocial Treatments for Posttraumatic Stress Disorder. Oxford University Press, 2015. http://dx.doi.org/10.1093/med:psych/9780199342211.003.0018.

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Treatments for posttraumatic stress disorder (PTSD) work better than treatment as usual; average effect sizes are in the moderate to high range. A variety of treatments have been established as effective, with no one treatment having superiority. Both present-focused and past-focused treatment models work (neither consistently outperforms the other). Areas of future development include training, dissemination, client access to care, optimal delivery modes, and mechanisms of action. Methodological issues include improving research reporting, broadening study samples, and greater use of active comparison conditions.
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Furst, Eric M., and Todd M. Squires. Active microrheology. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199655205.003.0007.

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Active microrheology uses external forces (most typically magnetic or optical) to force microrheological probes into motion. These techniques short-circuit the Einstein component of passive microrheology. Active microrheology provides an additional handle to probe material properties, and has been used both to extend the range of materials amenable to microrheological analysis, and to examine material properties that are inaccessible to passive microrheology. Three main topics are presented: the use of active microrheology to extend the range of passive microrheology, while maintaining many of the advantages (small sample size, wide frequency range, etc.); its use to complement passive microrheology in active systems, which convert chemical fuel to mechanical work, in order to elucidate the power provided by molecular motors, for instance; and its application (and potential limitations) to investigate the non-linear response properties of materials, including shear thinning and yielding.
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Ramdass, Ranjit. Neurophysiology in the assessment of inflammatory myopathies. Edited by Hector Chinoy and Robert Cooper. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198754121.003.0015.

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Clinical neurophysiology (electrodiagnosis) includes the assessment of peripheral nerves by electrical stimulation (nerve conduction studies, NCS) and needle examination of muscles (electromyography, EMG). Electrodiagnostic assessment is a functional extension of clinical examination into the laboratory. It plays an important role in the investigation of a patient suspected of having myositis, providing valuable information regarding peripheral nerve, neuromuscular junction and muscle functions, to better characterize clinical syndromes. NCS can establish the presence and quantify the severity of a primary or co-existing peripheral neuropathy, while EMG examination can help discriminate between primary myogenic and primary neurogenic disorders. EMG is potentially more sensitive than clinical examination, as abnormalities can be detected in muscles apparently unaffected on clinical examination. Additionally, a number of muscles can be sampled to help target an optimal muscle biopsy site. Neurophysiology can also assist in monitoring treatment responses and detecting emerging problems, such steroid myopathy or drug-induced neuropathy.
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Littlefield, Amy, Deirdre Orceyre, and Stephanie Cheng. Integrative Oncology. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190466268.003.0021.

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Cancer risk increases with age, but a patient’s tolerance to conventional treatments may be reduced with aging and associated morbidities. The development and expansion of age-appropriate therapies and approaches will be crucial as the population of elderly patients with cancer grows in the upcoming years. Taking into account the unique needs of this population will be of great importance. This chapter introduces the field of integrative oncology, the practice of supporting the whole person before, during, and after conventional treatments for cancer. Current evidence recognizes the safe use of many integrative interventions, such as lifestyle and diet changes and supplement and botanical use, to prevent cancer; to reduce side effects and optimize wellness during treatments such as surgery, chemotherapy, and radiation; and to promote full recovery after treatment. Many of these same interventions act directly to optimally regulate pathways in the unique metabolism of the malignant cell process.
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Book chapters on the topic "Optimal Sample Size"

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Kuß, Uwe. "C-Optimal Decisions with Optimality Properties for Finite Sample Size." In Contributions to Econometrics and Statistics Today. Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-70189-4_15.

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Zhang, Lanju, Lu Cui, and Yaoyao Xu. "Optimal Adaptive Phase III Design with Interim Sample Size and Dose Determination." In Contemporary Biostatistics with Biopharmaceutical Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15310-6_10.

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Zaman, Md Faisal, and Hideo Hirose. "Estimation of Optimal Sample Size of Decision Forest with SVM Using Embedded Cross-Validation Method." In Intelligent Information and Database Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20042-7_28.

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Gnecco, Giorgio, and Federico Nutarelli. "Optimal Trade-Off Between Sample Size and Precision of Supervision for the Fixed Effects Panel Data Model." In Machine Learning, Optimization, and Data Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-37599-7_44.

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Brungard, C. W., and J. L. Boettinger. "Conditioned Latin Hypercube Sampling: Optimal Sample Size for Digital Soil Mapping of Arid Rangelands in Utah, USA." In Digital Soil Mapping. Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8863-5_6.

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Viaene, Nicole, Johannes Hallmann, and Leendert P. G. Molendijk. "Methods for nematode extraction." In Techniques for work with plant and soil nematodes. CABI, 2021. http://dx.doi.org/10.1079/9781786391759.0012.

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Abstract Nematodes can be present in different matrices. This chapter describes several methods to extract nematodes from soil and plant parts. It is crucial that an appropriate method is chosen for the purpose of the research as different types of nematodes, and even different nematode stages, are extracted depending on the method. Factors to consider for choosing the optimal extraction method are the extraction efficiency of the method, the maximum sample size that can be analysed and costs of the extraction equipment. In addition, water consumption, labour and the time needed before nematodes can be examined can be important factors.
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Viaene, Nicole, Johannes Hallmann, and Leendert P. G. Molendijk. "Methods for nematode extraction." In Techniques for work with plant and soil nematodes. CABI, 2021. http://dx.doi.org/10.1079/9781786391759.0002.

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Abstract Nematodes can be present in different matrices. This chapter describes several methods to extract nematodes from soil and plant parts. It is crucial that an appropriate method is chosen for the purpose of the research as different types of nematodes, and even different nematode stages, are extracted depending on the method. Factors to consider for choosing the optimal extraction method are the extraction efficiency of the method, the maximum sample size that can be analysed and costs of the extraction equipment. In addition, water consumption, labour and the time needed before nematodes can be examined can be important factors.
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Al-Dousari, Noor, Modi Ahmed, Ali Al-Dousari, Musaad Al-Daihani, and Murahib Al-Elaj. "Dust Particle Size and Statistical Parameters." In Atlas of Fallen Dust in Kuwait. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66977-5_3.

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AbstractGrain ‘size’ can be specified and measured in several different ways. All methods of grain size determination have blemishes, and the choice of the most appropriate method is governed by the nature of the sample and the use to which the data are placed. Four main methods are currently used for size analysis of sands: (a) sieving; (b) settling tube analysis; (c) electro-optical methods, including Coulter Counter analysis and laser granulometry; and (d) computerized image analysis. The classification of the particle size distribution of Kuwait dust was mapped according to the parameters proposed by Folk And Ward (1957) which were widely used for quantitative comparisons between natural grain size distribution and the lognormal distribution that shows better sorted sediments have lower values of σ1. Maps of the distribution of dust in Kuwait were obtained that included: fine sand (F.S.), Coarse sand (C.S), Medium Sand (M.S), Very Fine Sane (V.F.S), Very Coarse Silt (V.C.Silt), Coarse Silt (C.Silt), Medium Silt (M.Silt), Fine Silt (F.Silt), Very Fine Silt (V.F.Silt), in addition to that, the deposition percentage of Clay, Sand, mud (silt plus clay) and silt were provided.
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Metwally, Ibrahim M., Abd El Rahman H. Elbardawiny, Fathy M. Ahmed, and Hazem Z. Fahim. "A Universal Formula for Side-Lobes Removal Optimum Filter in Multi-samples Phase Coded Pulse Compression Radars." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31129-2_52.

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Smith, Richard D., and Joanna Coast. "The Economics of Resistance Through an Ethical Lens." In Ethics and Drug Resistance: Collective Responsibility for Global Public Health. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-27874-8_17.

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Abstract Economics is concerned with the analysis of choice and the efficient use of resources. Markets for antibiotics are heavily affected by their ‘public good’ nature and the externality that results from their consumption in terms of resistance. The non-excludability and non-rivalry associated with knowledge production in antibiotic development also has implications for the supply of antibiotics. On the demand side there are ethical issues associated with free-riding by consumers, free-riding across nations and free-riding across time. On the supply side, the lack of a pipeline for new antibiotics for the future causes both ethical and economic issues – and from both perspectives, efforts should perhaps focus more on alternatives to antibiotics and adjustments to heath care systems to reduce reliance on antibiotics. Indeed, unlike many areas of health care, where economics and ethical perspectives may differ, antimicrobial resistance is a case where the two perspectives align in terms of ensuring efficient and sustainable development and use of this precious resources. All strategies for dealing with resistance should share the same goals of achieving an optimal balance in the use of antimicrobial agents and explicit consideration of the distributional implications.
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Conference papers on the topic "Optimal Sample Size"

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Dong, Guangling, Chi He, and Zhengguo Dai. "Optimal sample size allocation for integrated test scheme." In 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). IEEE, 2015. http://dx.doi.org/10.1109/civemsa.2015.7158624.

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Yang, Su-Fen, and Chih-Ching Yang. "Optimal variable sample size and sampling interval MSE chart." In 2011 8th International Conference on Service Systems and Service Management (ICSSSM 2011). IEEE, 2011. http://dx.doi.org/10.1109/icsssm.2011.5959315.

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Javanmard, Adel, and Andrea Montanari. "Nearly optimal sample size in hypothesis testing for high-dimensional regression." In 2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2013. http://dx.doi.org/10.1109/allerton.2013.6736695.

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Klygach, Denis, Maksim Vakhitov, Amur Khashimov, Vladimir Zhivulin, Denis Vinnik, and Darya Sherstyuk. "Determination of the Optimal Sample Size for Measurement in a Coaxial Transmission Line." In 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). IEEE, 2020. http://dx.doi.org/10.1109/usbereit48449.2020.9117619.

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Sudarsanam, Nandan, Ramya Chandran, and Daniel D. Frey. "Conducting Non-Adaptive Experiments in a Live Setting: A Bayesian Approach to Determining Optimal Sample Size." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98335.

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Abstract This research studies the use of predetermined experimental plans in a live setting with a finite implementation horizon. In this context, we seek to determine the optimal experimental budget in different environments using a Bayesian framework. We derive theoretical results on the optimal allocation of resources to treatments with the objective of minimizing cumulative regret, a metric commonly used in online statistical learning. Our base case studies a setting with two treatments assuming Gaussian priors for the treatment means and noise distributions. We extend our study through analytical and semi-analytical techniques which explore worst-case bounds and the generalization to k treatments. We determine theoretical limits for the experimental budget across all possible scenarios. The optimal level of experimentation that is recommended by this study varies extensively and depends on the experimental environment as well as the number of available units. This highlights the importance of such an approach which incorporates these factors to determine the budget.
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Yu-Hui Yeh, Flora, and Marcus Gallagher. "An empirical study of the sample size variability of optimal active learning using Gaussian process regression." In 2008 IEEE International Joint Conference on Neural Networks (IJCNN 2008 - Hong Kong). IEEE, 2008. http://dx.doi.org/10.1109/ijcnn.2008.4634342.

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Higo, Eishiro, and Mahesh D. Pandey. "Value of Information and Hypothesis Testing Approaches for Sample Size Determination in Engineering Component Inspection: A Comparison." In ASME 2016 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/pvp2016-63932.

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A sample size determination method is developed for a two-action problem that represents a component maintenance scenario requiring current state estimation. For safety and generation efficiency, each component of a nuclear power plant must be regularly inspected. In terms of safety, the larger the sample size inspected, the less the uncertainty about current and future states of the components; however, such inspections are expensive. Thus, sample size determination becomes an important problem. A key idea for solving this problem is the Value of Information (VoI) and its derivation: the Expected Net Gain of Sampling (ENGS). The ENGS is a function of sample size and represents by how much a decision maker benefits from the observed data. By maximizing the ENGS, the optimal sample size is determined in terms of cost-benefit analysis.
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Zhao, Chunhui, Wei Wang, and Chengxia Yu. "Predicting glucose concentration for hyper/hypoglycemia alert: Multiple order model migration and optimal model selection via analysis of sample size." In 2017 American Control Conference (ACC). IEEE, 2017. http://dx.doi.org/10.23919/acc.2017.7963160.

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Kumari, Sushma, Sujoy Kumar Samanta, and Brij Saxena. "THEORETICAL ANALYSIS ON EFFICIENT MICROWAVE WARMING OF HUMAN BLOOD." In Ampere 2019. Universitat Politècnica de València, 2019. http://dx.doi.org/10.4995/ampere2019.2019.9765.

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Economical and efficient warming of pre-transfusion human blood has been a subject of extensive investigation. The objective of this study is to identify and analyze the effect of enhanced microwave warming of bank blood. The sample here has been assumed to be a 2D cylinder interacting with microwave irradiation. The mathematical interpretation for the study is performed by solving the equation of electromagnetic wave propagation along with the equation of energy balance and pertinent boundary conditions. The samples after being subjected to both lateral and radial irradiations of same intensity are investigated for the power absorption in the sample with respect to the sample size. The preliminary observations obtained are further analyzed and extended for spatial distribution scrutiny. The collaborative analysis of the spatial distributions of temperature and power in the human blood along with high heating rate and low thermal non-uniformity determine the optimal heating strategy. The observations at different sample sizes recommend radial irradiation as the optimal heating strategy for samples corresponding to OP: 1 and 3, and lateral irradiation for samples corresponding to OP: 2, respectively. Considering all the aspects, the present work recommends an efficient way for enhanced microwave assisted heating of body fluid samples (2D cylindrical geometry) with known or measurable dielectric properties.
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Turek, Steven, and Sam Anand. "A Hull Normal Approach for Determining the Size of Cylindrical Features." In ASME 2007 International Manufacturing Science and Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/msec2007-31206.

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In coordinate metrology, discrete data is sampled from a continuous form to assess the manufactured feature’s deviation from its design specifications. Although coordinate measuring machines have a high degree of accuracy, the unsampled portion of the manufactured object cannot be completely described. The definition of cylindrical size for an external feature as specified by ASME Y14.5.1M-1994 [1,2] matches the analytical definition of a minimum circumscribing cylinder (MCC) when Rule #1 is applied. Even though the MCC is a logical analysis technique for size determination, it is highly sensitive to the sampling method and any uncertainties encountered in that process. Determining the least-sum-of-squares solution is an alternative method commonly utilized in size determination. However, the least-squares formulation seeks an optimal solution not based on the cylindrical size definition [1,2], and hence has been shown to be biased [6,7]. This research presents a novel Hull Normal method for size determination of cylindrical bosses. The goal of the proposed method is to recreate the sampled surface using computational geometry methods and determine the cylinder’s axis and radius based upon the reconstructed surface. Through varying the random sample size of data from an actual measured part, repetitive analyses resulted in the Hull Normal method having a lower bias and distributions that were skewed towards the true value of the radius.
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Reports on the topic "Optimal Sample Size"

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Cressie, Noel, and Jonathan Biele. A Sample-Size Optimal Bayesian Procedure for Sequential Pharmaceutical Trials. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada248512.

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Blundell, S., and Nicole Wayant. Local spatial dispersion for multiscale modeling of geospatial data : exploring dispersion measures to determine optimal raster data sample sizes. Engineer Research and Development Center (U.S.), 2020. http://dx.doi.org/10.21079/11681/35678.

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