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Статті в журналах з теми "Stratified representative sampling"
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Iliyasu, Rufai, and Ilker Etikan. "Comparison of quota sampling and stratified random sampling." Biometrics & Biostatistics International Journal 10, no. 1 (February 25, 2021): 24–27. http://dx.doi.org/10.15406/bbij.2021.10.00326.
Повний текст джерелаАнотація:
The possibility that researchers should be able to obtain data from all cases is questionable. There is a need; therefore, this article provides a probability and non-probability sampling. In this paper we studied the differences and similarities of the two with approach that is more of fritter away time, cost sufficient with energy required throughout the sample observed. The pair shows the differences and similarities between them, different articles were reviewed to compare the two. Quota sampling and Stratified sampling are close to each other. Both require the division into groups of the target population. The main goal of both methods is to select a representative sample and facilitate sub-group research. There are major variations, however. Stratified sampling uses simple random sampling when the categories are generated; sampling of the quota uses sampling of availability. For stratified sampling, a sampling frame is necessary, but not needed for quota sampling. More specifically, stratified sampling is a method of probability sampling which enables the calculation of the sampling error. For quota samples, this is not possible. Quota sampling is therefore primarily used by market analysts rather than stratified sampling, as it is mostly cost-effective and easy to conduct and has the appealing equity of satisfying population reach. However, it disguises potentially significant bias.
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Gnat, Sebastian. "Analysis of the Impact of the Type of Sampling of Representative Properties on the Results of Mass Appraisal." Folia Oeconomica Stetinensia 20, no. 2 (December 1, 2020): 152–67. http://dx.doi.org/10.2478/foli-2020-0041.
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Abstract Research background: Mass valuation is a process in which many properties are valued simultaneously with a uniform approach. An example of a procedure used for mass real estate valuation is the Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA), which can be developed into a multiple regression model. The algorithm is based on a set of drawn representative properties. This set determines, inter alia, the quality of obtained valuations. Purpose: The objective of the study is to verify the hypothesis whether changing the method of sampling representative properties from the originally used simple random sampling to stratified sampling improves the results of the SAREMA econometric variant. Research methodology: The article presents a study that uses two methods of representative properties sampling – simple random sampling and stratified sampling. Errors of the models of valuation created taking into account both methods of sampling and different number of representative properties are compared. A key aspect of the survey is the choice of a better sampling method. Results: The study has shown that stratified sampling improves valuation results and, more specifically, allows for lower root mean square errors. Stratified sampling yielded better results in the initial phase of the study with more observations, but reducing the percentage of strata participating in the draws, despite the increase in RMSE, guaranteed lower errors than the corresponding results based on simple sampling in all variants of the study. Novelty: The article confirms the possibility of improving the results of mass property valuation by changing the scheme of representative properties sampling. The results allowed for the conclusion that stratified sampling is a better way of creating a set of representative properties.
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Sun, Zhuo, Zhixin Zhang, Min Chen, Zhen Qian, Min Cao, and Yongning Wen. "Improving the Performance of Automated Rooftop Extraction through Geospatial Stratified and Optimized Sampling." Remote Sensing 14, no. 19 (October 5, 2022): 4961. http://dx.doi.org/10.3390/rs14194961.
Повний текст джерелаАнотація:
Accurate and timely access to building rooftop information is very important for urban management. The era of big data brings new opportunities for rooftop extraction based on deep learning and high-resolution satellite imagery. However, collecting representative datasets from such big data to train deep learning models efficiently is an essential problem that still needs to be explored. In this study, geospatial stratified and optimized sampling (GSOS) based on geographical priori information and optimization of sample spatial location distribution is proposed to acquire representative samples. Specifically, the study area is stratified based on land cover to divide the rooftop-dense stratum and the rooftop-sparse stratum. Within each stratum, an equal amount of samples is collected and their spatial locations are optimized. To evaluate the effectiveness of the proposed strategy, several qualitive and quantitative experiments are conducted. As a result, compared with other common sampling approaches (e.g., random sampling, stratified random sampling, and optimized sampling), GSOS is superior in terms of the abundance and types of collected samples. Furthermore, two quantitative metrics, the F1-score and Intersection over Union (IoU), are reported for rooftop extraction based on deep learning methods and different sampling methods, in which the results based on GSOS are on average 9.88% and 13.20% higher than those based on the other sampling methods, respectively. Moreover, the proposed sampling strategy is able to obtain representative training samples for the task of building rooftop extractions and may serve as a viable method to alleviate the labour-intensive problem in the construction of rooftop benchmark datasets.
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Studnicki, M., W. Mądry, and J. Schmidt. "Comparing the efficiency of sampling strategies to establish a representative in the phenotypic-based genetic diversity core collection of orchardgrass (Dactylis glomerata L.)." Czech Journal of Genetics and Plant Breeding 49, No. 1 (February 8, 2013): 36–47. http://dx.doi.org/10.17221/9/2012-cjgpb.
Повний текст джерелаАнотація:
Establishing a core collection that represents the genetic diversity of the entire collection with a minimum loss of its original diversity and minimal redundancies is an important problem for gene bank curators and crop breeders. In this paper, we assess the representativeness of the original genetic diversity in core collections consisting of one-tenth of the entire collection obtained according to 23 sampling strategies. The study was performed using the Polish orchardgrass Dactylis glomerata L. germplasm collection as a model. The representativeness of the core collections was validated by the difference of means (MD%) and difference of mean squared Euclidean distance (d‒D%) for the studied traits in the core subsets and the entire collection. In this way, we compared the efficiency of a simple random and 22 (20 cluster-based and 2 direct cluster-based) stratified sampling strategies. Each cluster-based stratified sampling strategy is a combination of 2 clusterings, 5 allocations and 2 methods of sampling in a group. We used the accession genotypic predicted values for 8 quantitative traits tested in field trials. A sampling strategy is considered more effective for establishing core collections if the means of the traits in a core are maintained at the same level as the means in the entire collection (i.e., the mean of MD% in the simulated samples is close to zero) and, simultaneously, when the overall variation in a core collection is greater than in the entire collection (i.e., the mean of d‒D% in the simulated samples is greater than that obtained for the simple random sampling strategy). Both cluster analyses (unweighted pair group method with arithmetic mean UPGMA and Ward) were similarly useful in constructing those sampling strategies capable of establishing representative core collections. Among the allocation methods that are relatively most useful for constructing efficient samplings were proportional and D2 (including variation). Within the Ward clusters, the random sampling was better than the cluster-based sampling, but not within the UPGMA clusters.
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Kesur, Khewal Bhupendra. "Improving Precision and Reducing Runtime of Microscopic Traffic Simulators through Stratified Sampling." Journal of Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/754204.
Повний текст джерелаАнотація:
This paper examines the application of Latin Hypercube Sampling (LHS) and Antithetic Variables (AVs) to reduce the variance of estimated performance measures from microscopic traffic simulators. LHS and AV allow for a more representative coverage of input probability distributions through stratification, reducing the standard error of simulation outputs. Two methods of implementation are examined, one where stratification is applied to headways and routing decisions of individual vehicles and another where vehicle counts and entry times are more evenly sampled. The proposed methods have wider applicability in general queuing systems. LHS is found to outperform AV, and reductions of up to 71% in the standard error of estimates of traffic network performance relative to independent sampling are obtained. LHS allows for a reduction in the execution time of computationally expensive microscopic traffic simulators as fewer simulations are required to achieve a fixed level of precision with reductions of up to 84% in computing time noted on the test cases considered. The benefits of LHS are amplified for more congested networks and as the required level of precision increases.
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Huang, Man, Dan Liu, Chenjie Hong, Shigui Du, Zhanyou Luo, Changhong Li, and Yongliang Huang. "Representative Sample Sampling Method for Size Effect Experiment of Jointed Rock Mass." Geofluids 2020 (August 25, 2020): 1–8. http://dx.doi.org/10.1155/2020/8870387.
Повний текст джерелаАнотація:
The influence of size effect on the hydromechanical behavior of rock mass has long been recognized. As a result, analysis of the rock mass size effect has been developed. However, when conducting size effect studies, the representativeness of the sample is less considered. Therefore, combining the existing statistical methods and sampling methods, a comprehensive representative sampling method for rock mass is present. In this method, a large number of sample statistics of different sizes are provided in the progressive coverage method; then, the plane density of the track length is defined as the value of stratification to perform stratified sampling for representative samples. Furthermore, it is applied to a joint network model generated in accordance with the actual situation and compared with those of other methods. The sampling results show that the proposed method can provide a certain reference value for studying the scale-dependent behavior of rock mass mechanical parameters.
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McDowell, Ian, Richard Aylesworth, Margaret Stewart, Gerry Hill, and Joan Lindsay. "Study Sampling in the Canadian Study of Health and Aging." International Psychogeriatrics 13, S1 (February 2001): 19–28. http://dx.doi.org/10.1017/s1041610202007950.
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The Canadian Study of Health and Aging drew representative samples of people aged 65 or over from the community and institutions across Canada. The sample was designed to provide regional and national prevalence estimates for dementia by age and sex. Thirty-six sampling areas were used in a stratified cluster design with optimal allocation; sampling weights were developed to provide population estimates. The sample included 9,008 people aged 65 or over from the community, and 1,255 from institutions. This report describes the sampling procedures, the methods used to recruit people to the study and participation rates, the characteristics of the resulting sample, and the way in which sample weights should be used.
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Kiely, M., A. Flynn, KE Harrington, PJ Robson, and G. Cran. "Sampling description and procedures used to conduct the North/South Ireland Food Consumption Survey." Public Health Nutrition 4, no. 5a (October 2001): 1029–35. http://dx.doi.org/10.1079/phn2001183.
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AbstractObjectiveThe purpose of this survey was to establish a database of habitual food and drink consumption in a representative sample of Irish adults, aged 18–64 years. The present paper describes the sampling protocol, response rate and characteristics of the survey population in terms of sex and age groups, seasonality, geographical location, marital status, social class, socio-economic status and education level.DesignA cross-sectional food consumption survey was carried out. In the Republic of Ireland, a nationally representative sample of adults was randomly selected with a validated two-stage clustered design, using the electoral register as the sampling frame. This method produced a self-weighting or ‘epsem’ sample of individuals, where each adult who was registered to vote had an equal opportunity of being selected. Similarly, in Northern Ireland, a two-stage random sampling procedure was used. The sampling frame was the electoral register, and the sample was stratified by urban/rural and by an index of material deprivation, to ensure representation of each sector of the community. The recruitment procedure was the same in the North and South. An introductory letter with an information leaflet was posted to each selected individual and these were followed up by a visit from a fieldworker, who invited participation in the survey.SettingNorthern Ireland and Republic of Ireland between 1997 and 1999.ResultsThe response rate, which is the percentage of the total number of people who completed a 7-day food diary (n = 1379) out of the total eligible sample (n = 2177), was 63%. Non-respondents and dropouts constituted 34% and 3%, respectively, of the total eligible sample. Compared with the most recent census figures available, the sample was generally found to be representative in terms of sex and age group profiles, geographical location, marital status, seasonality, social class, socio-economic group and education level. Data on sex and age group and geographical location were collected from non-respondents for comparison with the survey sample. There were no apparent differences between them.ConclusionThe North/South Ireland Food Consumption Survey has established a Samplino relational database of habitual food and drink consumption, in addition to data on Response rate habitual physical activity, anthropometric measurements, socio-demographic factors, Demographics lifestyle, health status indicators and attitudes, in a nationally representative sample Socio-economic factors of the population of the island of Ireland.
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Gong, Yali, Huan Xie, Yanmin Jin, and Xiaohua Tong. "Assessing Multi-Temporal Global Urban Land-Cover Products Using Spatio-Temporal Stratified Sampling." ISPRS International Journal of Geo-Information 11, no. 8 (August 19, 2022): 451. http://dx.doi.org/10.3390/ijgi11080451.
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In recent years, the availability of multi-temporal global land-cover datasets has meant that they have become a key data source for evaluating land cover in many applications. Due to the high data volume of the multi-temporal land-cover datasets, probability sampling is an efficient method for validating multi-temporal global urban land-cover maps. However, the current accuracy assessment methods often work for a single-epoch dataset, and they are not suitable for multi-temporal data products. Limitations such as repeated sampling and inappropriate sample allocation can lead to inaccurate evaluation results. In this study, we propose the use of spatio-temporal stratified sampling to assess thematic mappings with respect to the temporal changes and spatial clustering. The total number of samples in the two stages, i.e., map and pixel, was obtained by using a probability sampling model. Since the proportion of the area labeled as no change is large while that of the area labeled as change is small, an optimization algorithm for determining the sample sizes of the different strata is proposed by minimizing the sum of variance of the user’s accuracy, producer’s accuracy, and proportion of area for all strata. The experimental results show that the allocation of sample size by the proposed method results in the smallest bias in the estimated accuracy, compared with the conventional sample allocation, i.e., equal allocation and proportional allocation. The proposed method was applied to multi-temporal global urban land-cover maps from 2000 to 2010, with a time interval of 5 years. Due to the spatial aggregation characteristics, the local pivotal method (LPM) is adopted to realize spatially balanced sampling, leading to more representative samples for each stratum in the spatial domain. The main contribution of our research is the proposed spatio-temporal sampling approach and the accuracy assessment conducted for the multi-temporal global urban land-cover product.
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Lafetá, Bruno Oliveira, Tamires Mousslech Andrade Penido, Nivaldo De Souza Martins, Márcio Leles Romarco de Oliveira, Danielle Piuzana Mucida, and Reynaldo Campos Santana. "SAMPLING OF CHEMICAL ATTRIBUTES IN FOREST SOILS." FLORESTA 49, no. 2 (March 29, 2019): 305. http://dx.doi.org/10.5380/rf.v49i2.57705.
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Information about sample adequacy that represents soil chemical attributes distribution are fundamental for a better rationalization of the use of correctives and fertilizers. The objective was to evaluate the variability of these attributes and to size the minimum number of composite samples to represent the fertility of forest soils. The total area planted was 9,101ha, constituted of 265 commercial eucalypt stands. The 687 soil composite samples obtained were for chemical analysis. It was evaluated the performance of two exploratory analysis techniques and six sampling procedures. The attributes P, K, Ca, Mg and S presented higher coefficient of variation (>35%). In contrast, the distributions of Al, organic matter and, mainly, pH were the most homogeneous. The sample error was smaller as the amount of composite samples increased. The representative of all chemical attributes (sample error of 5%) was achieved with a minimum of 309 (one each 29ha, 1:29) and 295 (1:31) composite samples from sampling procedures simple casual and stratified by altitude class, respectively. Both procedures were promising for soil sampling, especially, when applying the boxplot for identification and removal of outliers.
Дисертації з теми "Stratified representative sampling"
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Thackway, Richard Malcom. "Analysis of techniques for mapping environments for fauna survey." Master's thesis, 1985. http://hdl.handle.net/1885/15431.
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A discussion of environmental land classification is presented for the purpose of surveying avifaunal communities.
Surveying and mapping land uses the term environment in a special sense. Environment can be mapped into regions whose components are interacting climate terrain, geology, soils and biota. The problem of how to describe the environment for sampling fauna requires an approach which samples the inherent and known variability of all environmental regions present. Discovery of patterns between fauna and environment provide the basis for understanding species/habitat relationships and provides a valuable basis for management or more detailed studies. Two environmental mapping methods commonly employed in faunal survey and management are systematic grids and natural landscape patterns; these were compared to determine their effectiveness for classifying the environment for sampling avifaunal communities.
A detailed study was undertaken between 1982-84 in a plot of 8km2 in the Tianjara area. The plot was chosen to encompass a representative sample of the wide range of environments described by Gunn (1985). Analysis of the systematic grids involved sampling a diverse set of environmental attributes into six different grid sizes, including 100m2, 200m2, 300m2, 400m2, 500m2 and 1000m2. Topographic maps and aerial photos provided the sources for measuring the attributes. Results of several analyses showed the 300m2 grid was the most appropriate for the Tianjara area. Analysis of natural landscape patterns involved adoption of the work done by Gunn et al (1984) and led to the preparation of a land unit map for the study plot. Detailed patterns were delineated in 1:27,000 scale air photos and described using the land unit descriptions in Gunn (1985).
Results from ground site samples taken to verify the two mapping bases showed that the correspondence between map and ground data was better for sites in systematic grids than for natural landscape patterns. Notwithstanding this, a better understanding of the effects of sampling specific patches of environment was gained from examining sites in natural landscape patterns because it employed a stratified representative sampling strategy, while the systematic grids used a centric systematic sampling strategy. The effect of this was large uniform patches of habitat tended to be more oversampled by sites in systematic grids than was observed for sites in natural landscape patterns.
Examination of the relationships between the sampling bases using analyses of environment was not possible because of the lack of sufficient sites in common between the two sampling bases. Comparison of the two sampling bases was, however, possible by using avifaunal data common to both sampling bases. Analysis of the relationships between avifaunal data and environmental groups showed only minor differences between the effectiveness of the two sampling bases to provide practical and realistic descriptions of environment for describing discrete assemblages of birds.
The overall conclusion of this study is that any environmental classification, so long as it is based on relevant attributes known to be important for environmental structure and processes, will provide a valuable basis for sampling fauna. A number of points need to be stressed regarding analyses of this type; care needs to be exercised in choosing surrogate environmental attributes between the mapping and ground site data and caution is required when allocating sampling sites to avoid overemphasising area of environmental groups as more important than the inherent variability of the attributes within the environmental groups. An understanding of this problem will greatly improve the nature of sampling fauna in environmental regions.
Частини книг з теми "Stratified representative sampling"
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Neyman, Jerzy. "On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and the Method of Purposive Selection." In Springer Series in Statistics, 123–50. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-4380-9_12.
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Dalenius, T. "Introduction to Neyman (1934) On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive Selection." In Springer Series in Statistics, 115–22. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-4380-9_11.
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Roos, Vera, Anél du Plessis, and Jaco Hoffman. "Municipal Service Delivery to Older Persons: Contextualizing Opportunities for ICT Interventions." In Age-Inclusive ICT Innovation for Service Delivery in South Africa, 29–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94606-7_2.
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AbstractThis chapter has a threefold aim: (1) to contextualize older persons’ inclusivity at municipal level as outlined in Goal 11 of the United Nations Sustainable Development Goals (SDGs) and international, African regional and South African law and policy frameworks; (2) to obtain an assessment of service delivery by local government, and (3) to reflect on gaps in service delivery and offer suggestions. Stratified sampling was used and information obtained through semi-structured interviews, emailed responses and focus groups from representatives (n = 17) on three local government levels, NGO representatives (n = 5), and officials from the South African Local Government Association (SALGA) and the Department of Social Development (n = 26). A sample of older persons (n = 302) from a rural area and two large towns in North West and Gauteng provinces completed questionnaires and participated in semi-structured interviews (n = 14) and focus groups (n = 22). Findings indicated compromised service delivery related to local government officials’ systemic, managerial, and capacity challenges. Municipal services were either non-existent or age-inappropriate. Local government’s unresponsiveness leaves older people at risk—particularly those who lack social networks. We present suggestions to address the disconnect between the intent of laws and policies for inclusivity and municipal service delivery, and the service delivery experiences of older persons.
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Hankin, David G., Michael S. Mohr, and Ken B. Newman. "Basic concepts." In Sampling Theory, 11–22. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198815792.003.0002.
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This chapter provides a conceptual, visual and non-quantitative presentation of the basic principles of sampling theory which are developed in formal quantitative fashion in subsequent chapters. Included are summaries of (a) basic terminology used throughout the text (population, sample, estimator, estimate), (b) components of a sampling strategy (sampling frame, sampling design, estimator), (c) properties of estimators (bias, sampling variance, mean square error), and (d) sampling distribution of an estimator. Simple or familiar settings are used to illustrate the differences between simple frames (listings of population units from which a sample of units is selected) and complex frames (sampling units consist of groupings of population units), and to illustrate the different components of a sampling strategy. A bullseye target with associated dart throws is used to distinguish the important estimator properties of bias, sampling variance, and mean square error. The performances of randomized sampling procedures and purposive or judgment selection of “representative samples” are contrasted using two examples: (1) an historical contrast of estimated abundance of Oregon coastal coho salmon (Oncorhynchus kisutch) based on purposive representative reach surveys and on stratified random surveys, and (2) a repeatable classroom exercise pitting judgment sampling against simple random sampling for estimation of mean weight in a population of agates collected from northern California beaches.
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Curato, Nicole, David M. Farrell, Brigitte Geissel, Kimmo Grönlund, Patricia Mockler, Jean-Benoit Pilet, Alan Renwick, Jonathan Rose, Maija Setälä, and Jane Suiter. "Recruitment." In Deliberative Mini-Publics, 34–47. Policy Press, 2021. http://dx.doi.org/10.1332/policypress/9781529214109.003.0003.
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This chapter discusses the procedure of selecting participants to DMPs. It underlines the importance of a representative sample in order to guarantee diversity of opinions and participants. In comparison with other possible methods – election through voting, a corporatist system where the participants are appointed by civil society organisations and other interest groups, and self-selection where all interested people can take part – random selection is the best way of guaranteeing the necessary diversity in a DMP. The chapter highlights key aspects in the implementation of random sampling, whether pure or stratified, and the strategies that can make a DMP sample as representative as possible.
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Anderson, Raymond A. "Sample Selection." In Credit Intelligence & Modelling, 651–66. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780192844194.003.0020.
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Samples are small amounts chosen to represent a larger pool; sampling dips into the pool to choose which will be analysed, with conclusions extended to the larger pool. Trade-offs happen between i) having samples of sufficiently large and representative to enable reasonable results; ii) the costs associated with data collection and processing. (1) Overview—i) terminology—proper drawing and representation {random, stratified, bias, weight}, counts per subgroup {over-, under- and balanced sample}; repetitive {replacement, bootstrap, k-fold, jack-knife}; artificial increases {bagging, boosting, stacking}; ii) optimal and minimum sample sizes; iii) law of diminishing data returns. (2) THOR samples—i) sample types—training, hold-out, out-of-time, recent; ii) sample count guidelines; iii) review of observation windows and assignment; iv) sampling plan and outcome. (3) Afterthoughts—i) further review of un- and under-populated characteristics; ii) means of randomly extracting an exact number of cases; iii) housekeeping rules regarding code assignments for each sample.
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Foufopoulos, Johannes, Gary A. Wobeser, and Hamish McCallum. "Sampling, Experimental Design, and Statistical Analysis." In Infectious Disease Ecology and Conservation, 65–75. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780199583508.003.0004.
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Performing experiments that investigate disease in wildlife populations poses numerous logistic, statistical, and analytical challenges. Efficient study design is therefore very important and typically centers on careful consideration of the “three Rs of sampling and study design.” The first is representativeness; the individuals selected for a study must be representative of the population relevant to the research question. Second, because differences between treatments can only be indicative relative to variation within treatments, replication is needed in order to cover the range of variation in the population of interest. The number of replicates in an experiment depends on the magnitude of the parameter in question, as well as the extent of variation in the response variable. Finally, ensuring randomness through unbiased random sampling of experimental subjects is critical to ensuring representativeness. Several methods of random sampling, including simple random sampling, stratified random sampling, systematic sampling, and cluster sampling are discussed. A final consideration of experimental design explained is statistical power, or a study’s ability to detect a biologically relevant effect or difference. Once an experiment has been designed and conducted, hypothesis testing of the null and alternative hypotheses will help determine whether the patterns observed can be attributed to the infectious agent and how they can be used to guide management decisions.
Тези доповідей конференцій з теми "Stratified representative sampling"
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Ahn, Hong Joo, Ju Youl Kim, Se Chul Sohn, Kwang Yong Jee, and In Koo Lee. "A Study on the Representative Sampling Survey for the Inspection of the Clearance Level for the Radioisotope Waste." In The 11th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2007. http://dx.doi.org/10.1115/icem2007-7296.
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Utilization facilities for radioisotope (RI) are increasing annually in South Korea, and the total number was 2,723, as of December 31, 2005. The inspection of a clearance level is a very important problem in order to ensure a social reliance for releasing radioactive materials to the environment. Korean regulations for such a clearance are described in Notice No. 2001–30 of the Ministry of Science and Technology (MOST) and Notice No. 2002–67 of the Ministry of Commerce, Industry and Energy (MOCIE). Most unsealed sources in RI waste drums at a storage facility are low-level beta-emitters with short half-lives, so it is impossible to measure their inventories by a nondestructive analysis. Furthermore, RI wastes generated from hospital, educational and research institutes and industry have a heterogeneous, multiple, irregular, and a small quantity of a waste stream. This study addresses a representative (master) sampling survey and analysis plan for RI wastes because a complete enumeration of waste drums is impossible and not desirable in terms of a cost and efficiency. The existing approaches to a representative sampling include a judgmental, simple random, stratified random, systematic grid, systematic random, composite, and adaptive sampling. A representative sampling plan may combine two or more of the above sampling approaches depending on the type and distribution of a waste stream. Stratified random sampling (constrained randomization) is proven to be adequate for a sampling design of a RI waste regarding a half-life, surface dose, undertaking time to a storage facility, and type of waste. The developed sampling protocol includes estimating the number of drums within a waste stream, estimating the number of samples, and a confirmation of the required number of samples. The statistical process control for a quality assurance plan includes control charts and an upper control limit (UCL) of 95% to determine whether a clearance level is met or not.
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Nelson, Jacob, G. Austin Marrs, Greg Schmidt, Joseph A. Donndelinger, and Robert L. Nagel. "Evaluating Sampling Methods for Reusing Knowledge From Large and Ill-Structured Qualitative Data Sets." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67964.
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The desire to use ever growing qualitative data sets of user generated content in the engineering design process in a computationally effective manner makes it increasingly necessary to draw representative samples. This work investigated the ability of alternative sampling algorithms to draw samples with conformance to characteristics of the original data set. Sampling methods investigated included: random sampling, interval sampling, fixed-increment (or systematic) sampling method, and stratified sampling. Data collected through the Vehicle Owner’s Questionnaire, a survey administered by the U.S. National Highway Traffic Safety Administration, is used as a case study throughout this paper. The paper demonstrates that existing statistical methods may be used to evaluate goodness of fit for samples drawn from large bodies of qualitative data. Evaluation of goodness of fit not only provides confidence that a sample is representative of the data set from which it is drawn, but also yields valuable real-time feedback during the sampling process. This investigation revealed two interesting and counterintuitive trends in sampling algorithm performance. The first is that larger sample sizes do not necessarily lead to improved goodness of fit. The second is that depending on the details of implementation, data cleansing may degrade performance of data sampling algorithms rather than improving it. This work illustrates the importance of aligning sampling procedures to data structures and validating the conformance of samples to characteristics of the larger data set to avoid drawing erroneous conclusions based on unexpectedly biased samples of data.
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Ho, Clifford K., and Gregory J. Kolb. "Incorporating Uncertainty Into Probabilistic Performance Models of Concentrating Solar Power Plants." In ASME 2009 3rd International Conference on Energy Sustainability collocated with the Heat Transfer and InterPACK09 Conferences. ASMEDC, 2009. http://dx.doi.org/10.1115/es2009-90034.
Повний текст джерелаАнотація:
A method for applying probabilistic models to concentrating solar thermal power plants is described in this paper. Benefits of using probabilistic models include quantification of uncertainties inherent in the system and characterization of their impact on system performance and economics. Sensitivity studies using stepwise regression analysis can identify and rank the most important parameters and processes as a means to prioritize future research and activities. The probabilistic method begins with the identification of uncertain variables and the assignment of appropriate distributions for those variables. Those parameters are then sampled using a stratified method (Latin Hypercube Sampling) to ensure complete and representative sampling from each distribution. Existing models of performance, reliability, and cost are then simulated multiple times using the sampled set of parameters. The results yield a cumulative distribution function that can be used to quantify the probability of exceeding (or being less than) a particular value. Two examples, a simple cost model and a more detailed performance model of a hypothetical 100 MWe power tower, are provided to illustrate the methods.