91 resultados para stratified sampling
Resumo:
Nahhas, Wolfe, and Chen (2002, Biometrics 58, 964-971) considered optimal set size for ranked set sampling (RSS) with fixed operational costs. This framework can be very useful in practice to determine whether RSS is beneficial and to obtain the optimal set size that minimizes the variance of the population estimator for a fixed total cost. In this article, we propose a scheme of general RSS in which more than one observation can be taken from each ranked set. This is shown to be more cost-effective in some cases when the cost of ranking is not so small. We demonstrate using the example in Nahhas, Wolfe, and Chen (2002, Biometrics 58, 964-971), by taking two or more observations from one set even with the optimal set size from the RSS design can be more beneficial.
Resumo:
A new technique called the reef resource inventory (RRI) was developed to map the distribution and abundance of benthos and substratum on reefs. The rapid field sampling technique uses divers to visually estimate the percentage cover of categories of benthos and substratum along 2x20 in plotless strip-transects positioned randomly over the tops, and systematically along the edge of reefs. The purpose of this study was to compare the relative sampling accuracy of the RRI against the line intercept transect technique (LIT), an international standard for sampling reef benthos and substratum. Analysis of paired sampling with LIT and RRI at 51 sites indicated sampling accuracy was not different (P > 0.05) for 8 of the 12 benthos and substratum categories used in the study. Significant differences were attributed to small-scale patchiness and cryptic coloration of some benthos; effects associated with sampling a sparsely distributed animal along a line versus an area; difficulties in discriminating some of the benthos and substratum categories; and differences due to visual acuity since LIT measurements were taken by divers close to the seabed whereas RRI measurements were taken by divers higher in the water column. The relative cost efficiency of the RRI technique was at least three times that of LIT for all benthos and substratum categories and as much as 10 times higher for two categories. These results suggest that the RRI can be used to obtain reliable and accurate estimates of relative abundance of broad categories of reef benthos and substratum.
Resumo:
This article is motivated by a lung cancer study where a regression model is involved and the response variable is too expensive to measure but the predictor variable can be measured easily with relatively negligible cost. This situation occurs quite often in medical studies, quantitative genetics, and ecological and environmental studies. In this article, by using the idea of ranked-set sampling (RSS), we develop sampling strategies that can reduce cost and increase efficiency of the regression analysis for the above-mentioned situation. The developed method is applied retrospectively to a lung cancer study. In the lung cancer study, the interest is to investigate the association between smoking status and three biomarkers: polyphenol DNA adducts, micronuclei, and sister chromatic exchanges. Optimal sampling schemes with different optimality criteria such as A-, D-, and integrated mean square error (IMSE)-optimality are considered in the application. With set size 10 in RSS, the improvement of the optimal schemes over simple random sampling (SRS) is great. For instance, by using the optimal scheme with IMSE-optimality, the IMSEs of the estimated regression functions for the three biomarkers are reduced to about half of those incurred by using SRS.
Resumo:
The efficiency with which a small beam trawl (1 x 0.5 m mouth) sampled postlarvae and juveniles of tiger prawns Penaeus esculentus and P, semisulcatus at night was estimated in 3 tropical seagrass communities (dominated by Thalassia hemprichii, Syringodium isoetifolium and Enhalus acoroides, respectively) in the shallow waters of the Gulf of Carpentaria in northern Australia. An area of seagrass (40 x 3 m) was enclosed by a net and the beam trawl was repeatedly hand-hauled over the substrate. Net efficiency (q) was calculated using 4 methods: the unweighted Leslie, weighted Leslie, DeLury and Maximum-likelihood (ML) methods. The Maximum-likelihood is the preferred method for estimating efficiency because it makes the fewest assumptions and is not affected by zero catches. The major difference in net efficiencies was between postlarvae (mean ML q +/- 95% confidence limits = 0.66 +/- 0.16) and juveniles of both species (mean q for juveniles in water less than or equal to 1.0 m deep = 0.47 +/- 0.05), i.e. the beam trawl was more efficient at capturing postlarvae than juveniles. There was little difference in net efficiency for P, esculentus between seagrass types (T, hemprichii versus S. isoetifolium), even though the biomass and morphologies of seagrass in these communities differed greatly (biomasses were 54 and 204 g m(-2), respectively). The efficiency of the net appeared to be the same for juveniles of the 2 species in shallow water, but was lower for juvenile P, semisulcatus at high tide when the water was deeper (1.6 to 1.9 m) (0.35 +/- 0.08). The lower efficiency near the time of high tide is possibly because the prawns are more active at high than low tide, and can also escape above the net. Factors affecting net efficiency and alternative methods of estimating net efficiency are discussed.
Resumo:
Traditional comparisons between the capture efficiency of sampling devices have generally looked at the absolute differences between devices. We recommend that the signal-to-noise ratio be used when comparing the capture efficiency of benthic sampling devices. Using the signal-to-noise ratio rather than the absolute difference has the advantages that the variance is taken into account when determining how important the difference is, the hypothesis and minimum detectable difference can be made identical for all taxa, it is independent of the units used for measurement, and the sample-size calculation is independent of the variance. This new technique is illustrated by comparing the capture efficiency of a 0.05 m(2) van Veen grab and an airlift suction device, using samples taken from Heron and One Tree lagoons, Australia.
Resumo:
Between-subject and within-subject variability is ubiquitous in biology and physiology and understanding and dealing with this is one of the biggest challenges in medicine. At the same time it is difficult to investigate this variability by experiments alone. A recent modelling and simulation approach, known as population of models (POM), allows this exploration to take place by building a mathematical model consisting of multiple parameter sets calibrated against experimental data. However, finding such sets within a high-dimensional parameter space of complex electrophysiological models is computationally challenging. By placing the POM approach within a statistical framework, we develop a novel and efficient algorithm based on sequential Monte Carlo (SMC). We compare the SMC approach with Latin hypercube sampling (LHS), a method commonly adopted in the literature for obtaining the POM, in terms of efficiency and output variability in the presence of a drug block through an in-depth investigation via the Beeler-Reuter cardiac electrophysiological model. We show improved efficiency via SMC and that it produces similar responses to LHS when making out-of-sample predictions in the presence of a simulated drug block.
Resumo:
This report describes the development and simulation of a variable rate controller for a 6-degree of freedom nonlinear model. The variable rate simulation model represents an off the shelf autopilot. Flight experiment involves risks and can be expensive. Therefore a dynamic model to understand the performance characteristics of the UAS in mission simulation before actual flight test or to obtain parameters needed for the flight is important. The control and guidance is implemented in Simulink. The report tests the use of the model for air search and air sampling path planning. A GUI in which a set of mission scenarios, in which two experts (mission expert, i.e. air sampling or air search and an UAV expert) interact, is presented showing the benefits of the method.
Resumo:
We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.
Resumo:
Sampling design is critical to the quality of quantitative research, yet it does not always receive appropriate attention in nursing research. The current article details how balancing probability techniques with practical considerations produced a representative sample of Australian nursing homes (NHs). Budgetary, logistical, and statistical constraints were managed by excluding some NHs (e.g., those too difficult to access) from the sampling frame; a stratified, random sampling methodology yielded a final sample of 53 NHs from a population of 2,774. In testing the adequacy of representation of the study population, chi-square tests for goodness of fit generated nonsignificant results for distribution by distance from major city and type of organization. A significant result for state/territory was expected and was easily corrected for by the application of weights. The current article provides recommendations for conducting high-quality, probability-based samples and stresses the importance of testing the representativeness of achieved samples.
Resumo:
The rapid uptake of transcriptomic approaches in freshwater ecology has seen a wealth of data produced concerning the ways in which organisms interact with their environment on a molecular level. Typically, such studies focus either at the community level and so don’t require species identifications, or on laboratory strains of known species identity or natural populations of large, easily identifiable taxa. For chironomids, impediments still exist for applying these technologies to natural populations because they are small-bodied and often require time-consuming secondary sorting of stream material and morphological voucher preparation to confirm species diagnosis. These procedures limit the ability to maintain RNA quantity and quality in such organisms because RNA degrades rapidly and gene expression can be altered rapidly in organisms; thereby limiting the inclusion of such taxa in transcriptomic studies. Here, we demonstrate that these limitations can be overcome and outline an optimised protocol for collecting, sorting and preserving chironomid larvae that enables retention of both morphological vouchers and RNA for subsequent transcriptomics purposes. By ensuring that sorting and voucher preparation are completed within <4 hours after collection and that samples are kept cold at all times, we successfully retained both RNA and morphological vouchers from all specimens. Although not prescriptive in specific methodology, we anticipate that this paper will assist in promoting transcriptomic investigations of the sublethal impact on chironomid gene expression of changes to aquatic environments.
Resumo:
BACKGROUND As blood collection agencies (BCAs) face recurrent shortages of varying blood products, developing a panel comprising donors who are flexible in the product they donate based on same-time inventory demand could be an efficient, cost-effective inventory management strategy. Accounting for prior whole blood (WB) and plasmapheresis donation experience, this article explores current donors’ willingness to change their donation product and identifies the type of information required for such donation flexibility. STUDY DESIGN AND METHODS Telephone interviews (mean, 34 min; SD, 11 min) were conducted with 60 donors recruited via stratified purposive sampling representing six donor groups: no plasma, new to both WB and plasma, new to plasma, plasma, flexible (i.e., alternating between WB and plasma), and maximum (i.e., high frequency alternating between WB and plasma) donors. Participants responded to hypothetical scenarios and open-ended questions relating to their and other donors’ willingness to be flexible. Responses were transcribed and content was analyzed. RESULTS The most frequently endorsed categories varied between donor groups with more prominent differences emerging between the information and support that donors desired for themselves versus that for others. Most donors were willing to change donations but sought improved donation logistics and information regarding inventory levels to encourage flexibility. The factors perceived to facilitate the flexibility of other donors included providing donor-specific information and information regarding different donation types. CONCLUSION Regardless of donation history, donors are willing to be flexible with their donations. To foster a flexible donor panel, BCAs should continue to streamline the donation process and provide information relevant to donors’ experience.
Resumo:
A spatial sampling design that uses pair-copulas is presented that aims to reduce prediction uncertainty by selecting additional sampling locations based on both the spatial configuration of existing locations and the values of the observations at those locations. The novelty of the approach arises in the use of pair-copulas to estimate uncertainty at unsampled locations. Spatial pair-copulas are able to more accurately capture spatial dependence compared to other types of spatial copula models. Additionally, unlike traditional kriging variance, uncertainty estimates from the pair-copula account for influence from measurement values and not just the configuration of observations. This feature is beneficial, for example, for more accurate identification of soil contamination zones where high contamination measurements are located near measurements of varying contamination. The proposed design methodology is applied to a soil contamination example from the Swiss Jura region. A partial redesign of the original sampling configuration demonstrates the potential of the proposed methodology.
Resumo:
Quantifying nitrous oxide (N(2)O) fluxes, a potent greenhouse gas, from soils is necessary to improve our knowledge of terrestrial N(2)O losses. Developing universal sampling frequencies for calculating annual N(2)O fluxes is difficult, as fluxes are renowned for their high temporal variability. We demonstrate daily sampling was largely required to achieve annual N(2)O fluxes within 10% of the best estimate for 28 annual datasets collected from three continents, Australia, Europe and Asia. Decreasing the regularity of measurements either under- or overestimated annual N(2)O fluxes, with a maximum overestimation of 935%. Measurement frequency was lowered using a sampling strategy based on environmental factors known to affect temporal variability, but still required sampling more than once a week. Consequently, uncertainty in current global terrestrial N(2)O budgets associated with the upscaling of field-based datasets can be decreased significantly using adequate sampling frequencies.
Resumo:
Accurately quantifying total greenhouse gas emissions (e.g. methane) from natural systems such as lakes, reservoirs and wetlands requires the spatial-temporal measurement of both diffusive and ebullitive (bubbling) emissions. Traditional, manual, measurement techniques provide only limited localised assessment of methane flux, often introducing significant errors when extrapolated to the whole-of-system. In this paper, we directly address these current sampling limitations and present a novel multiple robotic boat system configured to measure the spatiotemporal release of methane to atmosphere across inland waterways. The system, consisting of multiple networked Autonomous Surface Vehicles (ASVs) and capable of persistent operation, enables scientists to remotely evaluate the performance of sampling and modelling algorithms for real-world process quantification over extended periods of time. This paper provides an overview of the multi-robot sampling system including the vehicle and gas sampling unit design. Experimental results are shown demonstrating the system’s ability to autonomously navigate and implement an exploratory sampling algorithm to measure methane emissions on two inland reservoirs.