The Relationship between Sample Sizes and Effect Sizes in Systematic Reviews in Education

ERIC Educational Resources Information Center

Slavin, Robert; Smith, Dewi

2009-01-01

Research in fields other than education has found that studies with small sample sizes tend to have larger effect sizes than those with large samples. This article examines the relationship between sample size and effect size in education. It analyzes data from 185 studies of elementary and secondary mathematics programs that met the standards of…

Reporting of sample size calculations in analgesic clinical trials: ACTTION systematic review.

PubMed

McKeown, Andrew; Gewandter, Jennifer S; McDermott, Michael P; Pawlowski, Joseph R; Poli, Joseph J; Rothstein, Daniel; Farrar, John T; Gilron, Ian; Katz, Nathaniel P; Lin, Allison H; Rappaport, Bob A; Rowbotham, Michael C; Turk, Dennis C; Dworkin, Robert H; Smith, Shannon M

2015-03-01

Sample size calculations determine the number of participants required to have sufficiently high power to detect a given treatment effect. In this review, we examined the reporting quality of sample size calculations in 172 publications of double-blind randomized controlled trials of noninvasive pharmacologic or interventional (ie, invasive) pain treatments published in European Journal of Pain, Journal of Pain, and Pain from January 2006 through June 2013. Sixty-five percent of publications reported a sample size calculation but only 38% provided all elements required to replicate the calculated sample size. In publications reporting at least 1 element, 54% provided a justification for the treatment effect used to calculate sample size, and 24% of studies with continuous outcome variables justified the variability estimate. Publications of clinical pain condition trials reported a sample size calculation more frequently than experimental pain model trials (77% vs 33%, P < .001) but did not differ in the frequency of reporting all required elements. No significant differences in reporting of any or all elements were detected between publications of trials with industry and nonindustry sponsorship. Twenty-eight percent included a discrepancy between the reported number of planned and randomized participants. This study suggests that sample size calculation reporting in analgesic trial publications is usually incomplete. Investigators should provide detailed accounts of sample size calculations in publications of clinical trials of pain treatments, which is necessary for reporting transparency and communication of pre-trial design decisions. In this systematic review of analgesic clinical trials, sample size calculations and the required elements (eg, treatment effect to be detected; power level) were incompletely reported. A lack of transparency regarding sample size calculations may raise questions about the appropriateness of the calculated sample size. Copyright © 2015 American Pain Society. All rights reserved.

Optimal flexible sample size design with robust power.

PubMed

Zhang, Lanju; Cui, Lu; Yang, Bo

2016-08-30

It is well recognized that sample size determination is challenging because of the uncertainty on the treatment effect size. Several remedies are available in the literature. Group sequential designs start with a sample size based on a conservative (smaller) effect size and allow early stop at interim looks. Sample size re-estimation designs start with a sample size based on an optimistic (larger) effect size and allow sample size increase if the observed effect size is smaller than planned. Different opinions favoring one type over the other exist. We propose an optimal approach using an appropriate optimality criterion to select the best design among all the candidate designs. Our results show that (1) for the same type of designs, for example, group sequential designs, there is room for significant improvement through our optimization approach; (2) optimal promising zone designs appear to have no advantages over optimal group sequential designs; and (3) optimal designs with sample size re-estimation deliver the best adaptive performance. We conclude that to deal with the challenge of sample size determination due to effect size uncertainty, an optimal approach can help to select the best design that provides most robust power across the effect size range of interest. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

PubMed

Hagell, Peter; Westergren, Albert

Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

Sequential sampling: a novel method in farm animal welfare assessment.

PubMed

Heath, C A E; Main, D C J; Mullan, S; Haskell, M J; Browne, W J

2016-02-01

Lameness in dairy cows is an important welfare issue. As part of a welfare assessment, herd level lameness prevalence can be estimated from scoring a sample of animals, where higher levels of accuracy are associated with larger sample sizes. As the financial cost is related to the number of cows sampled, smaller samples are preferred. Sequential sampling schemes have been used for informing decision making in clinical trials. Sequential sampling involves taking samples in stages, where sampling can stop early depending on the estimated lameness prevalence. When welfare assessment is used for a pass/fail decision, a similar approach could be applied to reduce the overall sample size. The sampling schemes proposed here apply the principles of sequential sampling within a diagnostic testing framework. This study develops three sequential sampling schemes of increasing complexity to classify 80 fully assessed UK dairy farms, each with known lameness prevalence. Using the Welfare Quality herd-size-based sampling scheme, the first 'basic' scheme involves two sampling events. At the first sampling event half the Welfare Quality sample size is drawn, and then depending on the outcome, sampling either stops or is continued and the same number of animals is sampled again. In the second 'cautious' scheme, an adaptation is made to ensure that correctly classifying a farm as 'bad' is done with greater certainty. The third scheme is the only scheme to go beyond lameness as a binary measure and investigates the potential for increasing accuracy by incorporating the number of severely lame cows into the decision. The three schemes are evaluated with respect to accuracy and average sample size by running 100 000 simulations for each scheme, and a comparison is made with the fixed size Welfare Quality herd-size-based sampling scheme. All three schemes performed almost as well as the fixed size scheme but with much smaller average sample sizes. For the third scheme, an overall association between lameness prevalence and the proportion of lame cows that were severely lame on a farm was found. However, as this association was found to not be consistent across all farms, the sampling scheme did not prove to be as useful as expected. The preferred scheme was therefore the 'cautious' scheme for which a sampling protocol has also been developed.

Analysis of methods commonly used in biomedicine for treatment versus control comparison of very small samples.

PubMed

Ristić-Djurović, Jasna L; Ćirković, Saša; Mladenović, Pavle; Romčević, Nebojša; Trbovich, Alexander M

2018-04-01

A rough estimate indicated that use of samples of size not larger than ten is not uncommon in biomedical research and that many of such studies are limited to strong effects due to sample sizes smaller than six. For data collected from biomedical experiments it is also often unknown if mathematical requirements incorporated in the sample comparison methods are satisfied. Computer simulated experiments were used to examine performance of methods for qualitative sample comparison and its dependence on the effectiveness of exposure, effect intensity, distribution of studied parameter values in the population, and sample size. The Type I and Type II errors, their average, as well as the maximal errors were considered. The sample size 9 and the t-test method with p = 5% ensured error smaller than 5% even for weak effects. For sample sizes 6-8 the same method enabled detection of weak effects with errors smaller than 20%. If the sample sizes were 3-5, weak effects could not be detected with an acceptable error; however, the smallest maximal error in the most general case that includes weak effects is granted by the standard error of the mean method. The increase of sample size from 5 to 9 led to seven times more accurate detection of weak effects. Strong effects were detected regardless of the sample size and method used. The minimal recommended sample size for biomedical experiments is 9. Use of smaller sizes and the method of their comparison should be justified by the objective of the experiment. Copyright © 2018 Elsevier B.V. All rights reserved.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

NASA Technical Reports Server (NTRS)

Rao, R. G. S.; Ulaby, F. T.

1977-01-01

The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

Sample size calculations for randomized clinical trials published in anesthesiology journals: a comparison of 2010 versus 2016.

PubMed

Chow, Jeffrey T Y; Turkstra, Timothy P; Yim, Edmund; Jones, Philip M

2018-06-01

Although every randomized clinical trial (RCT) needs participants, determining the ideal number of participants that balances limited resources and the ability to detect a real effect is difficult. Focussing on two-arm, parallel group, superiority RCTs published in six general anesthesiology journals, the objective of this study was to compare the quality of sample size calculations for RCTs published in 2010 vs 2016. Each RCT's full text was searched for the presence of a sample size calculation, and the assumptions made by the investigators were compared with the actual values observed in the results. Analyses were only performed for sample size calculations that were amenable to replication, defined as using a clearly identified outcome that was continuous or binary in a standard sample size calculation procedure. The percentage of RCTs reporting all sample size calculation assumptions increased from 51% in 2010 to 84% in 2016. The difference between the values observed in the study and the expected values used for the sample size calculation for most RCTs was usually > 10% of the expected value, with negligible improvement from 2010 to 2016. While the reporting of sample size calculations improved from 2010 to 2016, the expected values in these sample size calculations often assumed effect sizes larger than those actually observed in the study. Since overly optimistic assumptions may systematically lead to underpowered RCTs, improvements in how to calculate and report sample sizes in anesthesiology research are needed.

Requirements for Minimum Sample Size for Sensitivity and Specificity Analysis

PubMed Central

Adnan, Tassha Hilda

2016-01-01

Sensitivity and specificity analysis is commonly used for screening and diagnostic tests. The main issue researchers face is to determine the sufficient sample sizes that are related with screening and diagnostic studies. Although the formula for sample size calculation is available but concerning majority of the researchers are not mathematicians or statisticians, hence, sample size calculation might not be easy for them. This review paper provides sample size tables with regards to sensitivity and specificity analysis. These tables were derived from formulation of sensitivity and specificity test using Power Analysis and Sample Size (PASS) software based on desired type I error, power and effect size. The approaches on how to use the tables were also discussed. PMID:27891446

Study samples are too small to produce sufficiently precise reliability coefficients.

PubMed

Charter, Richard A

2003-04-01

In a survey of journal articles, test manuals, and test critique books, the author found that a mean sample size (N) of 260 participants had been used for reliability studies on 742 tests. The distribution was skewed because the median sample size for the total sample was only 90. The median sample sizes for the internal consistency, retest, and interjudge reliabilities were 182, 64, and 36, respectively. The author presented sample size statistics for the various internal consistency methods and types of tests. In general, the author found that the sample sizes that were used in the internal consistency studies were too small to produce sufficiently precise reliability coefficients, which in turn could cause imprecise estimates of examinee true-score confidence intervals. The results also suggest that larger sample sizes have been used in the last decade compared with those that were used in earlier decades.

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach

NASA Technical Reports Server (NTRS)

Hixson, M.; Bauer, M. E.; Davis, B. J. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Evaluation of four sampling schemes involving different numbers of samples and different size sampling units shows that the precision of the wheat estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling size unit.

Distribution of the two-sample t-test statistic following blinded sample size re-estimation.

PubMed

Lu, Kaifeng

2016-05-01

We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Sample size determination for estimating antibody seroconversion rate under stable malaria transmission intensity.

PubMed

Sepúlveda, Nuno; Drakeley, Chris

2015-04-03

In the last decade, several epidemiological studies have demonstrated the potential of using seroprevalence (SP) and seroconversion rate (SCR) as informative indicators of malaria burden in low transmission settings or in populations on the cusp of elimination. However, most of studies are designed to control ensuing statistical inference over parasite rates and not on these alternative malaria burden measures. SP is in essence a proportion and, thus, many methods exist for the respective sample size determination. In contrast, designing a study where SCR is the primary endpoint, is not an easy task because precision and statistical power are affected by the age distribution of a given population. Two sample size calculators for SCR estimation are proposed. The first one consists of transforming the confidence interval for SP into the corresponding one for SCR given a known seroreversion rate (SRR). The second calculator extends the previous one to the most common situation where SRR is unknown. In this situation, data simulation was used together with linear regression in order to study the expected relationship between sample size and precision. The performance of the first sample size calculator was studied in terms of the coverage of the confidence intervals for SCR. The results pointed out to eventual problems of under or over coverage for sample sizes ≤250 in very low and high malaria transmission settings (SCR ≤ 0.0036 and SCR ≥ 0.29, respectively). The correct coverage was obtained for the remaining transmission intensities with sample sizes ≥ 50. Sample size determination was then carried out for cross-sectional surveys using realistic SCRs from past sero-epidemiological studies and typical age distributions from African and non-African populations. For SCR < 0.058, African studies require a larger sample size than their non-African counterparts in order to obtain the same precision. The opposite happens for the remaining transmission intensities. With respect to the second sample size calculator, simulation unravelled the likelihood of not having enough information to estimate SRR in low transmission settings (SCR ≤ 0.0108). In that case, the respective estimates tend to underestimate the true SCR. This problem is minimized by sample sizes of no less than 500 individuals. The sample sizes determined by this second method highlighted the prior expectation that, when SRR is not known, sample sizes are increased in relation to the situation of a known SRR. In contrast to the first sample size calculation, African studies would now require lesser individuals than their counterparts conducted elsewhere, irrespective of the transmission intensity. Although the proposed sample size calculators can be instrumental to design future cross-sectional surveys, the choice of a particular sample size must be seen as a much broader exercise that involves weighting statistical precision with ethical issues, available human and economic resources, and possible time constraints. Moreover, if the sample size determination is carried out on varying transmission intensities, as done here, the respective sample sizes can also be used in studies comparing sites with different malaria transmission intensities. In conclusion, the proposed sample size calculators are a step towards the design of better sero-epidemiological studies. Their basic ideas show promise to be applied to the planning of alternative sampling schemes that may target or oversample specific age groups.

Concentrations of selected constituents in surface-water and streambed-sediment samples collected from streams in and near an area of oil and natural-gas development, south-central Texas, 2011-13

USGS Publications Warehouse

Opsahl, Stephen P.; Crow, Cassi L.

2014-01-01

During collection of streambed-sediment samples, additional samples from a subset of three sites (the SAR Elmendorf, SAR 72, and SAR McFaddin sites) were processed by using a 63-µm sieve on one aliquot and a 2-mm sieve on a second aliquot for PAH and n-alkane analyses. The purpose of analyzing PAHs and n-alkanes on a sample containing sand, silt, and clay versus a sample containing only silt and clay was to provide data that could be used to determine if these organic constituents had a greater affinity for silt- and clay-sized particles relative to sand-sized particles. The greater concentrations of PAHs in the <63-μm size-fraction samples at all three of these sites are consistent with a greater percentage of binding sites associated with fine-grained (<63 μm) sediment versus coarse-grained (<2 mm) sediment. The larger difference in total PAHs between the <2-mm and <63-μm size-fraction samples at the SAR Elmendorf site might be related to the large percentage of sand in the <2-mm size-fraction sample which was absent in the <63-μm size-fraction sample. In contrast, the <2-mm size-fraction sample collected from the SAR McFaddin site contained very little sand and was similar in particle-size composition to the <63-μm size-fraction sample.

7 CFR 51.1406 - Sample for grade or size determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., AND STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Sample for Grade Or Size Determination § 51.1406 Sample for grade or size determination. Each sample shall consist of 100 pecans. The...

Sample Size Calculations for Population Size Estimation Studies Using Multiplier Methods With Respondent-Driven Sampling Surveys.

PubMed

Fearon, Elizabeth; Chabata, Sungai T; Thompson, Jennifer A; Cowan, Frances M; Hargreaves, James R

2017-09-14

While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey. ©Elizabeth Fearon, Sungai T Chabata, Jennifer A Thompson, Frances M Cowan, James R Hargreaves. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2017.

Effects of sample size on estimates of population growth rates calculated with matrix models.

PubMed

Fiske, Ian J; Bruna, Emilio M; Bolker, Benjamin M

2008-08-28

Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities.

Approximate sample size formulas for the two-sample trimmed mean test with unequal variances.

PubMed

Luh, Wei-Ming; Guo, Jiin-Huarng

2007-05-01

Yuen's two-sample trimmed mean test statistic is one of the most robust methods to apply when variances are heterogeneous. The present study develops formulas for the sample size required for the test. The formulas are applicable for the cases of unequal variances, non-normality and unequal sample sizes. Given the specified alpha and the power (1-beta), the minimum sample size needed by the proposed formulas under various conditions is less than is given by the conventional formulas. Moreover, given a specified size of sample calculated by the proposed formulas, simulation results show that Yuen's test can achieve statistical power which is generally superior to that of the approximate t test. A numerical example is provided.

Influence of item distribution pattern and abundance on efficiency of benthic core sampling

USGS Publications Warehouse

Behney, Adam C.; O'Shaughnessy, Ryan; Eichholz, Michael W.; Stafford, Joshua D.

2014-01-01

ore sampling is a commonly used method to estimate benthic item density, but little information exists about factors influencing the accuracy and time-efficiency of this method. We simulated core sampling in a Geographic Information System framework by generating points (benthic items) and polygons (core samplers) to assess how sample size (number of core samples), core sampler size (cm2), distribution of benthic items, and item density affected the bias and precision of estimates of density, the detection probability of items, and the time-costs. When items were distributed randomly versus clumped, bias decreased and precision increased with increasing sample size and increased slightly with increasing core sampler size. Bias and precision were only affected by benthic item density at very low values (500–1,000 items/m2). Detection probability (the probability of capturing ≥ 1 item in a core sample if it is available for sampling) was substantially greater when items were distributed randomly as opposed to clumped. Taking more small diameter core samples was always more time-efficient than taking fewer large diameter samples. We are unable to present a single, optimal sample size, but provide information for researchers and managers to derive optimal sample sizes dependent on their research goals and environmental conditions.

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach. [Kansas

NASA Technical Reports Server (NTRS)

Hixson, M. M.; Bauer, M. E.; Davis, B. J.

1979-01-01

The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jomekian, A.; Faculty of Chemical Engineering, Iran University of Science and Technology; Behbahani, R.M., E-mail: behbahani@put.ac.ir

Ultra porous ZIF-8 particles synthesized using PEO/PA6 based poly(ether-block-amide) (Pebax 1657) as structure directing agent. Structural properties of ZIF-8 samples prepared under different synthesis parameters were investigated by laser particle size analysis, XRD, N{sub 2} adsorption analysis, BJH and BET tests. The overall results showed that: (1) The mean pore size of all ZIF-8 samples increased remarkably (from 0.34 nm to 1.1–2.5 nm) compared to conventionally synthesized ZIF-8 samples. (2) Exceptional BET surface area of 1869 m{sup 2}/g was obtained for a ZIF-8 sample with mean pore size of 2.5 nm. (3) Applying high concentrations of Pebax 1657 to themore » synthesis solution lead to higher surface area, larger pore size and smaller particle size for ZIF-8 samples. (4) Both, Increase in temperature and decrease in molar ratio of MeIM/Zn{sup 2+} had increasing effect on ZIF-8 particle size, pore size, pore volume, crystallinity and BET surface area of all investigated samples. - Highlights: • The pore size of ZIF-8 samples synthesized with Pebax 1657 increased remarkably. • The BET surface area of 1869 m{sup 2}/gr obtained for a ZIF-8 synthesized sample with Pebax. • Increase in temperature had increasing effect on textural properties of ZIF-8 samples. • Decrease in MeIM/Zn{sup 2+} had increasing effect on textural properties of ZIF-8 samples.« less

Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches.

PubMed

Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F

2014-07-10

In this paper, the optimal sample sizes at the cluster and person levels for each of two treatment arms are obtained for cluster randomized trials where the cost-effectiveness of treatments on a continuous scale is studied. The optimal sample sizes maximize the efficiency or power for a given budget or minimize the budget for a given efficiency or power. Optimal sample sizes require information on the intra-cluster correlations (ICCs) for effects and costs, the correlations between costs and effects at individual and cluster levels, the ratio of the variance of effects translated into costs to the variance of the costs (the variance ratio), sampling and measuring costs, and the budget. When planning, a study information on the model parameters usually is not available. To overcome this local optimality problem, the current paper also presents maximin sample sizes. The maximin sample sizes turn out to be rather robust against misspecifying the correlation between costs and effects at the cluster and individual levels but may lose much efficiency when misspecifying the variance ratio. The robustness of the maximin sample sizes against misspecifying the ICCs depends on the variance ratio. The maximin sample sizes are robust under misspecification of the ICC for costs for realistic values of the variance ratio greater than one but not robust under misspecification of the ICC for effects. Finally, we show how to calculate optimal or maximin sample sizes that yield sufficient power for a test on the cost-effectiveness of an intervention.

Determination of the optimal sample size for a clinical trial accounting for the population size.

PubMed

Stallard, Nigel; Miller, Frank; Day, Simon; Hee, Siew Wan; Madan, Jason; Zohar, Sarah; Posch, Martin

2017-07-01

The problem of choosing a sample size for a clinical trial is a very common one. In some settings, such as rare diseases or other small populations, the large sample sizes usually associated with the standard frequentist approach may be infeasible, suggesting that the sample size chosen should reflect the size of the population under consideration. Incorporation of the population size is possible in a decision-theoretic approach either explicitly by assuming that the population size is fixed and known, or implicitly through geometric discounting of the gain from future patients reflecting the expected population size. This paper develops such approaches. Building on previous work, an asymptotic expression is derived for the sample size for single and two-arm clinical trials in the general case of a clinical trial with a primary endpoint with a distribution of one parameter exponential family form that optimizes a utility function that quantifies the cost and gain per patient as a continuous function of this parameter. It is shown that as the size of the population, N, or expected size, N∗ in the case of geometric discounting, becomes large, the optimal trial size is O(N1/2) or O(N∗1/2). The sample size obtained from the asymptotic expression is also compared with the exact optimal sample size in examples with responses with Bernoulli and Poisson distributions, showing that the asymptotic approximations can also be reasonable in relatively small sample sizes. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

ENHANCEMENT OF LEARNING ON SAMPLE SIZE CALCULATION WITH A SMARTPHONE APPLICATION: A CLUSTER-RANDOMIZED CONTROLLED TRIAL.

PubMed

Ngamjarus, Chetta; Chongsuvivatwong, Virasakdi; McNeil, Edward; Holling, Heinz

2017-01-01

Sample size determination usually is taught based on theory and is difficult to understand. Using a smartphone application to teach sample size calculation ought to be more attractive to students than using lectures only. This study compared levels of understanding of sample size calculations for research studies between participants attending a lecture only versus lecture combined with using a smartphone application to calculate sample sizes, to explore factors affecting level of post-test score after training sample size calculation, and to investigate participants’ attitude toward a sample size application. A cluster-randomized controlled trial involving a number of health institutes in Thailand was carried out from October 2014 to March 2015. A total of 673 professional participants were enrolled and randomly allocated to one of two groups, namely, 341 participants in 10 workshops to control group and 332 participants in 9 workshops to intervention group. Lectures on sample size calculation were given in the control group, while lectures using a smartphone application were supplied to the test group. Participants in the intervention group had better learning of sample size calculation (2.7 points out of maximnum 10 points, 95% CI: 24 - 2.9) than the participants in the control group (1.6 points, 95% CI: 1.4 - 1.8). Participants doing research projects had a higher post-test score than those who did not have a plan to conduct research projects (0.9 point, 95% CI: 0.5 - 1.4). The majority of the participants had a positive attitude towards the use of smartphone application for learning sample size calculation.

Moment and maximum likelihood estimators for Weibull distributions under length- and area-biased sampling

Treesearch

Jeffrey H. Gove

2003-01-01

Many of the most popular sampling schemes used in forestry are probability proportional to size methods. These methods are also referred to as size biased because sampling is actually from a weighted form of the underlying population distribution. Length- and area-biased sampling are special cases of size-biased sampling where the probability weighting comes from a...

Developing the Noncentrality Parameter for Calculating Group Sample Sizes in Heterogeneous Analysis of Variance

ERIC Educational Resources Information Center

Luh, Wei-Ming; Guo, Jiin-Huarng

2011-01-01

Sample size determination is an important issue in planning research. In the context of one-way fixed-effect analysis of variance, the conventional sample size formula cannot be applied for the heterogeneous variance cases. This study discusses the sample size requirement for the Welch test in the one-way fixed-effect analysis of variance with…

Sample Size Determination for Regression Models Using Monte Carlo Methods in R

ERIC Educational Resources Information Center

Beaujean, A. Alexander

2014-01-01

A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…

The Statistics and Mathematics of High Dimension Low Sample Size Asymptotics.

PubMed

Shen, Dan; Shen, Haipeng; Zhu, Hongtu; Marron, J S

2016-10-01

The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal an asymptotic conical structure in critical sample eigendirections under the spike models with distinguishable (or indistinguishable) eigenvalues, when the sample size and/or the number of variables (or dimension) tend to infinity. The consistency of the sample eigenvectors relative to their population counterparts is determined by the ratio between the dimension and the product of the sample size with the spike size. When this ratio converges to a nonzero constant, the sample eigenvector converges to a cone, with a certain angle to its corresponding population eigenvector. In the High Dimension, Low Sample Size case, the angle between the sample eigenvector and its population counterpart converges to a limiting distribution. Several generalizations of the multi-spike covariance models are also explored, and additional theoretical results are presented.

Nomogram for sample size calculation on a straightforward basis for the kappa statistic.

PubMed

Hong, Hyunsook; Choi, Yunhee; Hahn, Seokyung; Park, Sue Kyung; Park, Byung-Joo

2014-09-01

Kappa is a widely used measure of agreement. However, it may not be straightforward in some situation such as sample size calculation due to the kappa paradox: high agreement but low kappa. Hence, it seems reasonable in sample size calculation that the level of agreement under a certain marginal prevalence is considered in terms of a simple proportion of agreement rather than a kappa value. Therefore, sample size formulae and nomograms using a simple proportion of agreement rather than a kappa under certain marginal prevalences are proposed. A sample size formula was derived using the kappa statistic under the common correlation model and goodness-of-fit statistic. The nomogram for the sample size formula was developed using SAS 9.3. The sample size formulae using a simple proportion of agreement instead of a kappa statistic and nomograms to eliminate the inconvenience of using a mathematical formula were produced. A nomogram for sample size calculation with a simple proportion of agreement should be useful in the planning stages when the focus of interest is on testing the hypothesis of interobserver agreement involving two raters and nominal outcome measures. Copyright © 2014 Elsevier Inc. All rights reserved.

Analysis of Sample Size, Counting Time, and Plot Size from an Avian Point Count Survey on Hoosier National Forest, Indiana

Treesearch

Frank R. Thompson; Monica J. Schwalbach

1995-01-01

We report results of a point count survey of breeding birds on Hoosier National Forest in Indiana. We determined sample size requirements to detect differences in means and the effects of count duration and plot size on individual detection rates. Sample size requirements ranged from 100 to >1000 points with Type I and II error rates of <0.1 and 0.2. Sample...

The quality of the reported sample size calculations in randomized controlled trials indexed in PubMed.

PubMed

Lee, Paul H; Tse, Andy C Y

2017-05-01

There are limited data on the quality of reporting of information essential for replication of the calculation as well as the accuracy of the sample size calculation. We examine the current quality of reporting of the sample size calculation in randomized controlled trials (RCTs) published in PubMed and to examine the variation in reporting across study design, study characteristics, and journal impact factor. We also reviewed the targeted sample size reported in trial registries. We reviewed and analyzed all RCTs published in December 2014 with journals indexed in PubMed. The 2014 Impact Factors for the journals were used as proxies for their quality. Of the 451 analyzed papers, 58.1% reported an a priori sample size calculation. Nearly all papers provided the level of significance (97.7%) and desired power (96.6%), and most of the papers reported the minimum clinically important effect size (73.3%). The median (inter-quartile range) of the percentage difference of the reported and calculated sample size calculation was 0.0% (IQR -4.6%;3.0%). The accuracy of the reported sample size was better for studies published in journals that endorsed the CONSORT statement and journals with an impact factor. A total of 98 papers had provided targeted sample size on trial registries and about two-third of these papers (n=62) reported sample size calculation, but only 25 (40.3%) had no discrepancy with the reported number in the trial registries. The reporting of the sample size calculation in RCTs published in PubMed-indexed journals and trial registries were poor. The CONSORT statement should be more widely endorsed. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

What is the optimum sample size for the study of peatland testate amoeba assemblages?

PubMed

Mazei, Yuri A; Tsyganov, Andrey N; Esaulov, Anton S; Tychkov, Alexander Yu; Payne, Richard J

2017-10-01

Testate amoebae are widely used in ecological and palaeoecological studies of peatlands, particularly as indicators of surface wetness. To ensure data are robust and comparable it is important to consider methodological factors which may affect results. One significant question which has not been directly addressed in previous studies is how sample size (expressed here as number of Sphagnum stems) affects data quality. In three contrasting locations in a Russian peatland we extracted samples of differing size, analysed testate amoebae and calculated a number of widely-used indices: species richness, Simpson diversity, compositional dissimilarity from the largest sample and transfer function predictions of water table depth. We found that there was a trend for larger samples to contain more species across the range of commonly-used sample sizes in ecological studies. Smaller samples sometimes failed to produce counts of testate amoebae often considered minimally adequate. It seems likely that analyses based on samples of different sizes may not produce consistent data. Decisions about sample size need to reflect trade-offs between logistics, data quality, spatial resolution and the disturbance involved in sample extraction. For most common ecological applications we suggest that samples of more than eight Sphagnum stems are likely to be desirable. Copyright © 2017 Elsevier GmbH. All rights reserved.

Sample size determination in group-sequential clinical trials with two co-primary endpoints

PubMed Central

Asakura, Koko; Hamasaki, Toshimitsu; Sugimoto, Tomoyuki; Hayashi, Kenichi; Evans, Scott R; Sozu, Takashi

2014-01-01

We discuss sample size determination in group-sequential designs with two endpoints as co-primary. We derive the power and sample size within two decision-making frameworks. One is to claim the test intervention’s benefit relative to control when superiority is achieved for the two endpoints at the same interim timepoint of the trial. The other is when the superiority is achieved for the two endpoints at any interim timepoint, not necessarily simultaneously. We evaluate the behaviors of sample size and power with varying design elements and provide a real example to illustrate the proposed sample size methods. In addition, we discuss sample size recalculation based on observed data and evaluate the impact on the power and Type I error rate. PMID:24676799

Sample Size Determination for One- and Two-Sample Trimmed Mean Tests

ERIC Educational Resources Information Center

Luh, Wei-Ming; Olejnik, Stephen; Guo, Jiin-Huarng

2008-01-01

Formulas to determine the necessary sample sizes for parametric tests of group comparisons are available from several sources and appropriate when population distributions are normal. However, in the context of nonnormal population distributions, researchers recommend Yuen's trimmed mean test, but formulas to determine sample sizes have not been…

Sample Size and Allocation of Effort in Point Count Sampling of Birds in Bottomland Hardwood Forests

Treesearch

Winston P. Smith; Daniel J. Twedt; Robert J. Cooper; David A. Wiedenfeld; Paul B. Hamel; Robert P. Ford

1995-01-01

To examine sample size requirements and optimum allocation of effort in point count sampling of bottomland hardwood forests, we computed minimum sample sizes from variation recorded during 82 point counts (May 7-May 16, 1992) from three localities containing three habitat types across three regions of the Mississippi Alluvial Valley (MAV). Also, we estimated the effect...

Monitoring Species of Concern Using Noninvasive Genetic Sampling and Capture-Recapture Methods

DTIC Science & Technology

2016-11-01

ABBREVIATIONS AICc Akaike’s Information Criterion with small sample size correction AZGFD Arizona Game and Fish Department BMGR Barry M. Goldwater...MNKA Minimum Number Known Alive N Abundance Ne Effective Population Size NGS Noninvasive Genetic Sampling NGS-CR Noninvasive Genetic...parameter estimates from capture-recapture models require sufficient sample sizes , capture probabilities and low capture biases. For NGS-CR, sample

On Using a Pilot Sample Variance for Sample Size Determination in the Detection of Differences between Two Means: Power Consideration

ERIC Educational Resources Information Center

Shieh, Gwowen

2013-01-01

The a priori determination of a proper sample size necessary to achieve some specified power is an important problem encountered frequently in practical studies. To establish the needed sample size for a two-sample "t" test, researchers may conduct the power analysis by specifying scientifically important values as the underlying population means…

Sample size calculations for case-control studies

Cancer.gov

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

Sample size and power calculations for detecting changes in malaria transmission using antibody seroconversion rate.

PubMed

Sepúlveda, Nuno; Paulino, Carlos Daniel; Drakeley, Chris

2015-12-30

Several studies have highlighted the use of serological data in detecting a reduction in malaria transmission intensity. These studies have typically used serology as an adjunct measure and no formal examination of sample size calculations for this approach has been conducted. A sample size calculator is proposed for cross-sectional surveys using data simulation from a reverse catalytic model assuming a reduction in seroconversion rate (SCR) at a given change point before sampling. This calculator is based on logistic approximations for the underlying power curves to detect a reduction in SCR in relation to the hypothesis of a stable SCR for the same data. Sample sizes are illustrated for a hypothetical cross-sectional survey from an African population assuming a known or unknown change point. Overall, data simulation demonstrates that power is strongly affected by assuming a known or unknown change point. Small sample sizes are sufficient to detect strong reductions in SCR, but invariantly lead to poor precision of estimates for current SCR. In this situation, sample size is better determined by controlling the precision of SCR estimates. Conversely larger sample sizes are required for detecting more subtle reductions in malaria transmission but those invariantly increase precision whilst reducing putative estimation bias. The proposed sample size calculator, although based on data simulation, shows promise of being easily applicable to a range of populations and survey types. Since the change point is a major source of uncertainty, obtaining or assuming prior information about this parameter might reduce both the sample size and the chance of generating biased SCR estimates.

Small sample sizes in the study of ontogenetic allometry; implications for palaeobiology

PubMed Central

Vavrek, Matthew J.

2015-01-01

Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes. PMID:25780770

Novel joint selection methods can reduce sample size for rheumatoid arthritis clinical trials with ultrasound endpoints.

PubMed

Allen, John C; Thumboo, Julian; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Tan, York Kiat

2018-03-01

To determine whether novel methods of selecting joints through (i) ultrasonography (individualized-ultrasound [IUS] method), or (ii) ultrasonography and clinical examination (individualized-composite-ultrasound [ICUS] method) translate into smaller rheumatoid arthritis (RA) clinical trial sample sizes when compared to existing methods utilizing predetermined joint sites for ultrasonography. Cohen's effect size (ES) was estimated (ES^) and a 95% CI (ES^L, ES^U) calculated on a mean change in 3-month total inflammatory score for each method. Corresponding 95% CIs [nL(ES^U), nU(ES^L)] were obtained on a post hoc sample size reflecting the uncertainty in ES^. Sample size calculations were based on a one-sample t-test as the patient numbers needed to provide 80% power at α = 0.05 to reject a null hypothesis H 0 : ES = 0 versus alternative hypotheses H 1 : ES = ES^, ES = ES^L and ES = ES^U. We aimed to provide point and interval estimates on projected sample sizes for future studies reflecting the uncertainty in our study ES^S. Twenty-four treated RA patients were followed up for 3 months. Utilizing the 12-joint approach and existing methods, the post hoc sample size (95% CI) was 22 (10-245). Corresponding sample sizes using ICUS and IUS were 11 (7-40) and 11 (6-38), respectively. Utilizing a seven-joint approach, the corresponding sample sizes using ICUS and IUS methods were nine (6-24) and 11 (6-35), respectively. Our pilot study suggests that sample size for RA clinical trials with ultrasound endpoints may be reduced using the novel methods, providing justification for larger studies to confirm these observations. © 2017 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Influences of sampling size and pattern on the uncertainty of correlation estimation between soil water content and its influencing factors

NASA Astrophysics Data System (ADS)

Lai, Xiaoming; Zhu, Qing; Zhou, Zhiwen; Liao, Kaihua

2017-12-01

In this study, seven random combination sampling strategies were applied to investigate the uncertainties in estimating the hillslope mean soil water content (SWC) and correlation coefficients between the SWC and soil/terrain properties on a tea + bamboo hillslope. One of the sampling strategies is the global random sampling and the other six are the stratified random sampling on the top, middle, toe, top + mid, top + toe and mid + toe slope positions. When each sampling strategy was applied, sample sizes were gradually reduced and each sampling size contained 3000 replicates. Under each sampling size of each sampling strategy, the relative errors (REs) and coefficients of variation (CVs) of the estimated hillslope mean SWC and correlation coefficients between the SWC and soil/terrain properties were calculated to quantify the accuracy and uncertainty. The results showed that the uncertainty of the estimations decreased as the sampling size increasing. However, larger sample sizes were required to reduce the uncertainty in correlation coefficient estimation than in hillslope mean SWC estimation. Under global random sampling, 12 randomly sampled sites on this hillslope were adequate to estimate the hillslope mean SWC with RE and CV ≤10%. However, at least 72 randomly sampled sites were needed to ensure the estimated correlation coefficients with REs and CVs ≤10%. Comparing with all sampling strategies, reducing sampling sites on the middle slope had the least influence on the estimation of hillslope mean SWC and correlation coefficients. Under this strategy, 60 sites (10 on the middle slope and 50 on the top and toe slopes) were enough to ensure the estimated correlation coefficients with REs and CVs ≤10%. This suggested that when designing the SWC sampling, the proportion of sites on the middle slope can be reduced to 16.7% of the total number of sites. Findings of this study will be useful for the optimal SWC sampling design.

Biostatistics Series Module 5: Determining Sample Size

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Determining the appropriate sample size for a study, whatever be its type, is a fundamental aspect of biomedical research. An adequate sample ensures that the study will yield reliable information, regardless of whether the data ultimately suggests a clinically important difference between the interventions or elements being studied. The probability of Type 1 and Type 2 errors, the expected variance in the sample and the effect size are the essential determinants of sample size in interventional studies. Any method for deriving a conclusion from experimental data carries with it some risk of drawing a false conclusion. Two types of false conclusion may occur, called Type 1 and Type 2 errors, whose probabilities are denoted by the symbols σ and β. A Type 1 error occurs when one concludes that a difference exists between the groups being compared when, in reality, it does not. This is akin to a false positive result. A Type 2 error occurs when one concludes that difference does not exist when, in reality, a difference does exist, and it is equal to or larger than the effect size defined by the alternative to the null hypothesis. This may be viewed as a false negative result. When considering the risk of Type 2 error, it is more intuitive to think in terms of power of the study or (1 − β). Power denotes the probability of detecting a difference when a difference does exist between the groups being compared. Smaller α or larger power will increase sample size. Conventional acceptable values for power and α are 80% or above and 5% or below, respectively, when calculating sample size. Increasing variance in the sample tends to increase the sample size required to achieve a given power level. The effect size is the smallest clinically important difference that is sought to be detected and, rather than statistical convention, is a matter of past experience and clinical judgment. Larger samples are required if smaller differences are to be detected. Although the principles are long known, historically, sample size determination has been difficult, because of relatively complex mathematical considerations and numerous different formulas. However, of late, there has been remarkable improvement in the availability, capability, and user-friendliness of power and sample size determination software. Many can execute routines for determination of sample size and power for a wide variety of research designs and statistical tests. With the drudgery of mathematical calculation gone, researchers must now concentrate on determining appropriate sample size and achieving these targets, so that study conclusions can be accepted as meaningful. PMID:27688437

Sensitivity and specificity of normality tests and consequences on reference interval accuracy at small sample size: a computer-simulation study.

PubMed

Le Boedec, Kevin

2016-12-01

According to international guidelines, parametric methods must be chosen for RI construction when the sample size is small and the distribution is Gaussian. However, normality tests may not be accurate at small sample size. The purpose of the study was to evaluate normality test performance to properly identify samples extracted from a Gaussian population at small sample sizes, and assess the consequences on RI accuracy of applying parametric methods to samples that falsely identified the parent population as Gaussian. Samples of n = 60 and n = 30 values were randomly selected 100 times from simulated Gaussian, lognormal, and asymmetric populations of 10,000 values. The sensitivity and specificity of 4 normality tests were compared. Reference intervals were calculated using 6 different statistical methods from samples that falsely identified the parent population as Gaussian, and their accuracy was compared. Shapiro-Wilk and D'Agostino-Pearson tests were the best performing normality tests. However, their specificity was poor at sample size n = 30 (specificity for P < .05: .51 and .50, respectively). The best significance levels identified when n = 30 were 0.19 for Shapiro-Wilk test and 0.18 for D'Agostino-Pearson test. Using parametric methods on samples extracted from a lognormal population but falsely identified as Gaussian led to clinically relevant inaccuracies. At small sample size, normality tests may lead to erroneous use of parametric methods to build RI. Using nonparametric methods (or alternatively Box-Cox transformation) on all samples regardless of their distribution or adjusting, the significance level of normality tests depending on sample size would limit the risk of constructing inaccurate RI. © 2016 American Society for Veterinary Clinical Pathology.

Electrical and magnetic properties of nano-sized magnesium ferrite

NASA Astrophysics Data System (ADS)

T, Smitha; X, Sheena; J, Binu P.; Mohammed, E. M.

2015-02-01

Nano-sized magnesium ferrite was synthesized using sol-gel techniques. Structural characterization was done using X-ray diffractometer and Fourier Transform Infrared Spectrometer. Vibration Sample Magnetometer was used to record the magnetic measurements. XRD analysis reveals the prepared sample is single phasic without any impurity. Particle size calculation shows the average crystallite size of the sample is 19nm. FTIR analysis confirmed spinel structure of the prepared samples. Magnetic measurement study shows that the sample is ferromagnetic with high degree of isotropy. Hysterisis loop was traced at temperatures 100K and 300K. DC electrical resistivity measurements show semiconducting nature of the sample.

76 FR 56141 - Notice of Intent To Request New Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-12

... level surveys of similar scope and size. The sample for each selected community will be strategically... of 2 hours per sample community. Full Study: The maximum sample size for the full study is 2,812... questionnaires. The initial sample size for this phase of the research is 100 respondents (10 respondents per...

Sample allocation balancing overall representativeness and stratum precision.

PubMed

Diaz-Quijano, Fredi Alexander

2018-05-07

In large-scale surveys, it is often necessary to distribute a preset sample size among a number of strata. Researchers must make a decision between prioritizing overall representativeness or precision of stratum estimates. Hence, I evaluated different sample allocation strategies based on stratum size. The strategies evaluated herein included allocation proportional to stratum population; equal sample for all strata; and proportional to the natural logarithm, cubic root, and square root of the stratum population. This study considered the fact that, from a preset sample size, the dispersion index of stratum sampling fractions is correlated with the population estimator error and the dispersion index of stratum-specific sampling errors would measure the inequality in precision distribution. Identification of a balanced and efficient strategy was based on comparing those both dispersion indices. Balance and efficiency of the strategies changed depending on overall sample size. As the sample to be distributed increased, the most efficient allocation strategies were equal sample for each stratum; proportional to the logarithm, to the cubic root, to square root; and that proportional to the stratum population, respectively. Depending on sample size, each of the strategies evaluated could be considered in optimizing the sample to keep both overall representativeness and stratum-specific precision. Copyright © 2018 Elsevier Inc. All rights reserved.

Effects of tree-to-tree variations on sap flux-based transpiration estimates in a forested watershed

NASA Astrophysics Data System (ADS)

Kume, Tomonori; Tsuruta, Kenji; Komatsu, Hikaru; Kumagai, Tomo'omi; Higashi, Naoko; Shinohara, Yoshinori; Otsuki, Kyoichi

2010-05-01

To estimate forest stand-scale water use, we assessed how sample sizes affect confidence of stand-scale transpiration (E) estimates calculated from sap flux (Fd) and sapwood area (AS_tree) measurements of individual trees. In a Japanese cypress plantation, we measured Fd and AS_tree in all trees (n = 58) within a 20 × 20 m study plot, which was divided into four 10 × 10 subplots. We calculated E from stand AS_tree (AS_stand) and mean stand Fd (JS) values. Using Monte Carlo analyses, we examined potential errors associated with sample sizes in E, AS_stand, and JS by using the original AS_tree and Fd data sets. Consequently, we defined optimal sample sizes of 10 and 15 for AS_stand and JS estimates, respectively, in the 20 × 20 m plot. Sample sizes greater than the optimal sample sizes did not decrease potential errors. The optimal sample sizes for JS changed according to plot size (e.g., 10 × 10 m and 10 × 20 m), while the optimal sample sizes for AS_stand did not. As well, the optimal sample sizes for JS did not change in different vapor pressure deficit conditions. In terms of E estimates, these results suggest that the tree-to-tree variations in Fd vary among different plots, and that plot size to capture tree-to-tree variations in Fd is an important factor. This study also discusses planning balanced sampling designs to extrapolate stand-scale estimates to catchment-scale estimates.

Sample size and power for cost-effectiveness analysis (part 1).

PubMed

Glick, Henry A

2011-03-01

Basic sample size and power formulae for cost-effectiveness analysis have been established in the literature. These formulae are reviewed and the similarities and differences between sample size and power for cost-effectiveness analysis and for the analysis of other continuous variables such as changes in blood pressure or weight are described. The types of sample size and power tables that are commonly calculated for cost-effectiveness analysis are also described and the impact of varying the assumed parameter values on the resulting sample size and power estimates is discussed. Finally, the way in which the data for these calculations may be derived are discussed.

Estimation of sample size and testing power (Part 4).

PubMed

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-01-01

Sample size estimation is necessary for any experimental or survey research. An appropriate estimation of sample size based on known information and statistical knowledge is of great significance. This article introduces methods of sample size estimation of difference test for data with the design of one factor with two levels, including sample size estimation formulas and realization based on the formulas and the POWER procedure of SAS software for quantitative data and qualitative data with the design of one factor with two levels. In addition, this article presents examples for analysis, which will play a leading role for researchers to implement the repetition principle during the research design phase.

[Formal sample size calculation and its limited validity in animal studies of medical basic research].

PubMed

Mayer, B; Muche, R

2013-01-01

Animal studies are highly relevant for basic medical research, although their usage is discussed controversially in public. Thus, an optimal sample size for these projects should be aimed at from a biometrical point of view. Statistical sample size calculation is usually the appropriate methodology in planning medical research projects. However, required information is often not valid or only available during the course of an animal experiment. This article critically discusses the validity of formal sample size calculation for animal studies. Within the discussion, some requirements are formulated to fundamentally regulate the process of sample size determination for animal experiments.

A sequential bioequivalence design with a potential ethical advantage.

PubMed

Fuglsang, Anders

2014-07-01

This paper introduces a two-stage approach for evaluation of bioequivalence, where, in contrast to the designs of Diane Potvin and co-workers, two stages are mandatory regardless of the data obtained at stage 1. The approach is derived from Potvin's method C. It is shown that under circumstances with relatively high variability and relatively low initial sample size, this method has an advantage over Potvin's approaches in terms of sample sizes while controlling type I error rates at or below 5% with a minute occasional trade-off in power. Ethically and economically, the method may thus be an attractive alternative to the Potvin designs. It is also shown that when using the method introduced here, average total sample sizes are rather independent of initial sample size. Finally, it is shown that when a futility rule in terms of sample size for stage 2 is incorporated into this method, i.e., when a second stage can be abolished due to sample size considerations, there is often an advantage in terms of power or sample size as compared to the previously published methods.

Sample Size in Qualitative Interview Studies: Guided by Information Power.

PubMed

Malterud, Kirsti; Siersma, Volkert Dirk; Guassora, Ann Dorrit

2015-11-27

Sample sizes must be ascertained in qualitative studies like in quantitative studies but not by the same means. The prevailing concept for sample size in qualitative studies is "saturation." Saturation is closely tied to a specific methodology, and the term is inconsistently applied. We propose the concept "information power" to guide adequate sample size for qualitative studies. Information power indicates that the more information the sample holds, relevant for the actual study, the lower amount of participants is needed. We suggest that the size of a sample with sufficient information power depends on (a) the aim of the study, (b) sample specificity, (c) use of established theory, (d) quality of dialogue, and (e) analysis strategy. We present a model where these elements of information and their relevant dimensions are related to information power. Application of this model in the planning and during data collection of a qualitative study is discussed. © The Author(s) 2015.

Variation in aluminum, iron, and particle concentrations in oxic groundwater samples collected by use of tangential-flow ultrafiltration with low-flow sampling

NASA Astrophysics Data System (ADS)

Szabo, Zoltan; Oden, Jeannette H.; Gibs, Jacob; Rice, Donald E.; Ding, Yuan

2002-02-01

Particulates that move with ground water and those that are artificially mobilized during well purging could be incorporated into water samples during collection and could cause trace-element concentrations to vary in unfiltered samples, and possibly in filtered samples (typically 0.45-um (micron) pore size) as well, depending on the particle-size fractions present. Therefore, measured concentrations may not be representative of those in the aquifer. Ground water may contain particles of various sizes and shapes that are broadly classified as colloids, which do not settle from water, and particulates, which do. In order to investigate variations in trace-element concentrations in ground-water samples as a function of particle concentrations and particle-size fractions, the U.S. Geological Survey, in cooperation with the U.S. Air Force, collected samples from five wells completed in the unconfined, oxic Kirkwood-Cohansey aquifer system of the New Jersey Coastal Plain. Samples were collected by purging with a portable pump at low flow (0.2-0.5 liters per minute and minimal drawdown, ideally less than 0.5 foot). Unfiltered samples were collected in the following sequence: (1) within the first few minutes of pumping, (2) after initial turbidity declined and about one to two casing volumes of water had been purged, and (3) after turbidity values had stabilized at less than 1 to 5 Nephelometric Turbidity Units. Filtered samples were split concurrently through (1) a 0.45-um pore size capsule filter, (2) a 0.45-um pore size capsule filter and a 0.0029-um pore size tangential-flow filter in sequence, and (3), in selected cases, a 0.45-um and a 0.05-um pore size capsule filter in sequence. Filtered samples were collected concurrently with the unfiltered sample that was collected when turbidity values stabilized. Quality-assurance samples consisted of sequential duplicates (about 25 percent) and equipment blanks. Concentrations of particles were determined by light scattering.

Reexamining Sample Size Requirements for Multivariate, Abundance-Based Community Research: When Resources are Limited, the Research Does Not Have to Be.

PubMed

Forcino, Frank L; Leighton, Lindsey R; Twerdy, Pamela; Cahill, James F

2015-01-01

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.

Frictional behaviour of sandstone: A sample-size dependent triaxial investigation

NASA Astrophysics Data System (ADS)

Roshan, Hamid; Masoumi, Hossein; Regenauer-Lieb, Klaus

2017-01-01

Frictional behaviour of rocks from the initial stage of loading to final shear displacement along the formed shear plane has been widely investigated in the past. However the effect of sample size on such frictional behaviour has not attracted much attention. This is mainly related to the limitations in rock testing facilities as well as the complex mechanisms involved in sample-size dependent frictional behaviour of rocks. In this study, a suite of advanced triaxial experiments was performed on Gosford sandstone samples at different sizes and confining pressures. The post-peak response of the rock along the formed shear plane has been captured for the analysis with particular interest in sample-size dependency. Several important phenomena have been observed from the results of this study: a) the rate of transition from brittleness to ductility in rock is sample-size dependent where the relatively smaller samples showed faster transition toward ductility at any confining pressure; b) the sample size influences the angle of formed shear band and c) the friction coefficient of the formed shear plane is sample-size dependent where the relatively smaller sample exhibits lower friction coefficient compared to larger samples. We interpret our results in terms of a thermodynamics approach in which the frictional properties for finite deformation are viewed as encompassing a multitude of ephemeral slipping surfaces prior to the formation of the through going fracture. The final fracture itself is seen as a result of the self-organisation of a sufficiently large ensemble of micro-slip surfaces and therefore consistent in terms of the theory of thermodynamics. This assumption vindicates the use of classical rock mechanics experiments to constrain failure of pressure sensitive rocks and the future imaging of these micro-slips opens an exciting path for research in rock failure mechanisms.

Comparison of Sample Size by Bootstrap and by Formulas Based on Normal Distribution Assumption.

PubMed

Wang, Zuozhen

2018-01-01

Bootstrapping technique is distribution-independent, which provides an indirect way to estimate the sample size for a clinical trial based on a relatively smaller sample. In this paper, sample size estimation to compare two parallel-design arms for continuous data by bootstrap procedure are presented for various test types (inequality, non-inferiority, superiority, and equivalence), respectively. Meanwhile, sample size calculation by mathematical formulas (normal distribution assumption) for the identical data are also carried out. Consequently, power difference between the two calculation methods is acceptably small for all the test types. It shows that the bootstrap procedure is a credible technique for sample size estimation. After that, we compared the powers determined using the two methods based on data that violate the normal distribution assumption. To accommodate the feature of the data, the nonparametric statistical method of Wilcoxon test was applied to compare the two groups in the data during the process of bootstrap power estimation. As a result, the power estimated by normal distribution-based formula is far larger than that by bootstrap for each specific sample size per group. Hence, for this type of data, it is preferable that the bootstrap method be applied for sample size calculation at the beginning, and that the same statistical method as used in the subsequent statistical analysis is employed for each bootstrap sample during the course of bootstrap sample size estimation, provided there is historical true data available that can be well representative of the population to which the proposed trial is planning to extrapolate.

A Note on Sample Size and Solution Propriety for Confirmatory Factor Analytic Models

ERIC Educational Resources Information Center

Jackson, Dennis L.; Voth, Jennifer; Frey, Marc P.

2013-01-01

Determining an appropriate sample size for use in latent variable modeling techniques has presented ongoing challenges to researchers. In particular, small sample sizes are known to present concerns over sampling error for the variances and covariances on which model estimation is based, as well as for fit indexes and convergence failures. The…

Sample size of the reference sample in a case-augmented study.

PubMed

Ghosh, Palash; Dewanji, Anup

2017-05-01

The case-augmented study, in which a case sample is augmented with a reference (random) sample from the source population with only covariates information known, is becoming popular in different areas of applied science such as pharmacovigilance, ecology, and econometrics. In general, the case sample is available from some source (for example, hospital database, case registry, etc.); however, the reference sample is required to be drawn from the corresponding source population. The required minimum size of the reference sample is an important issue in this regard. In this work, we address the minimum sample size calculation and discuss related issues. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Designing a two-rank acceptance sampling plan for quality inspection of geospatial data products

NASA Astrophysics Data System (ADS)

Tong, Xiaohua; Wang, Zhenhua; Xie, Huan; Liang, Dan; Jiang, Zuoqin; Li, Jinchao; Li, Jun

2011-10-01

To address the disadvantages of classical sampling plans designed for traditional industrial products, we originally propose a two-rank acceptance sampling plan (TRASP) for the inspection of geospatial data outputs based on the acceptance quality level (AQL). The first rank sampling plan is to inspect the lot consisting of map sheets, and the second is to inspect the lot consisting of features in an individual map sheet. The TRASP design is formulated as an optimization problem with respect to sample size and acceptance number, which covers two lot size cases. The first case is for a small lot size with nonconformities being modeled by a hypergeometric distribution function, and the second is for a larger lot size with nonconformities being modeled by a Poisson distribution function. The proposed TRASP is illustrated through two empirical case studies. Our analysis demonstrates that: (1) the proposed TRASP provides a general approach for quality inspection of geospatial data outputs consisting of non-uniform items and (2) the proposed acceptance sampling plan based on TRASP performs better than other classical sampling plans. It overcomes the drawbacks of percent sampling, i.e., "strictness for large lot size, toleration for small lot size," and those of a national standard used specifically for industrial outputs, i.e., "lots with different sizes corresponding to the same sampling plan."

Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

ERIC Educational Resources Information Center

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

A Typology of Mixed Methods Sampling Designs in Social Science Research

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Collins, Kathleen M. T.

2007-01-01

This paper provides a framework for developing sampling designs in mixed methods research. First, we present sampling schemes that have been associated with quantitative and qualitative research. Second, we discuss sample size considerations and provide sample size recommendations for each of the major research designs for quantitative and…

[Comparison study on sampling methods of Oncomelania hupensis snail survey in marshland schistosomiasis epidemic areas in China].

PubMed

An, Zhao; Wen-Xin, Zhang; Zhong, Yao; Yu-Kuan, Ma; Qing, Liu; Hou-Lang, Duan; Yi-di, Shang

2016-06-29

To optimize and simplify the survey method of Oncomelania hupensis snail in marshland endemic region of schistosomiasis and increase the precision, efficiency and economy of the snail survey. A quadrate experimental field was selected as the subject of 50 m×50 m size in Chayegang marshland near Henghu farm in the Poyang Lake region and a whole-covered method was adopted to survey the snails. The simple random sampling, systematic sampling and stratified random sampling methods were applied to calculate the minimum sample size, relative sampling error and absolute sampling error. The minimum sample sizes of the simple random sampling, systematic sampling and stratified random sampling methods were 300, 300 and 225, respectively. The relative sampling errors of three methods were all less than 15%. The absolute sampling errors were 0.221 7, 0.302 4 and 0.047 8, respectively. The spatial stratified sampling with altitude as the stratum variable is an efficient approach of lower cost and higher precision for the snail survey.

Reduced Sampling Size with Nanopipette for Tapping-Mode Scanning Probe Electrospray Ionization Mass Spectrometry Imaging

PubMed Central

Kohigashi, Tsuyoshi; Otsuka, Yoichi; Shimazu, Ryo; Matsumoto, Takuya; Iwata, Futoshi; Kawasaki, Hideya; Arakawa, Ryuichi

2016-01-01

Mass spectrometry imaging (MSI) with ambient sampling and ionization can rapidly and easily capture the distribution of chemical components in a solid sample. Because the spatial resolution of MSI is limited by the size of the sampling area, reducing sampling size is an important goal for high resolution MSI. Here, we report the first use of a nanopipette for sampling and ionization by tapping-mode scanning probe electrospray ionization (t-SPESI). The spot size of the sampling area of a dye molecular film on a glass substrate was decreased to 6 μm on average by using a nanopipette. On the other hand, ionization efficiency increased with decreasing solvent flow rate. Our results indicate the compatibility between a reduced sampling area and the ionization efficiency using a nanopipette. MSI of micropatterns of ink on a glass and a polymer substrate were also demonstrated. PMID:28101441

Drying step optimization to obtain large-size transparent magnesium-aluminate spinel samples

NASA Astrophysics Data System (ADS)

Petit, Johan; Lallemant, Lucile

2017-05-01

In the transparent ceramics processing, the green body elaboration step is probably the most critical one. Among the known techniques, wet shaping processes are particularly interesting because they enable the particles to find an optimum position on their own. Nevertheless, the presence of water molecules leads to drying issues. During the water removal, its concentration gradient induces cracks limiting the sample size: laboratory samples are generally less damaged because of their small size but upscaling the samples for industrial applications lead to an increasing cracking probability. Thanks to the drying step optimization, large size spinel samples were obtained.

[Practical aspects regarding sample size in clinical research].

PubMed

Vega Ramos, B; Peraza Yanes, O; Herrera Correa, G; Saldívar Toraya, S

1996-01-01

The knowledge of the right sample size let us to be sure if the published results in medical papers had a suitable design and a proper conclusion according to the statistics analysis. To estimate the sample size we must consider the type I error, type II error, variance, the size of the effect, significance and power of the test. To decide what kind of mathematics formula will be used, we must define what kind of study we have, it means if its a prevalence study, a means values one or a comparative one. In this paper we explain some basic topics of statistics and we describe four simple samples of estimation of sample size.

Breaking Free of Sample Size Dogma to Perform Innovative Translational Research

PubMed Central

Bacchetti, Peter; Deeks, Steven G.; McCune, Joseph M.

2011-01-01

Innovative clinical and translational research is often delayed or prevented by reviewers’ expectations that any study performed in humans must be shown in advance to have high statistical power. This supposed requirement is not justifiable and is contradicted by the reality that increasing sample size produces diminishing marginal returns. Studies of new ideas often must start small (sometimes even with an N of 1) because of cost and feasibility concerns, and recent statistical work shows that small sample sizes for such research can produce more projected scientific value per dollar spent than larger sample sizes. Renouncing false dogma about sample size would remove a serious barrier to innovation and translation. PMID:21677197

Effects of Calibration Sample Size and Item Bank Size on Ability Estimation in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Sahin, Alper; Weiss, David J.

2015-01-01

This study aimed to investigate the effects of calibration sample size and item bank size on examinee ability estimation in computerized adaptive testing (CAT). For this purpose, a 500-item bank pre-calibrated using the three-parameter logistic model with 10,000 examinees was simulated. Calibration samples of varying sizes (150, 250, 350, 500,…

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

PubMed

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure of relative efficiency might be less than the measure in the literature under some conditions, underestimating the relative efficiency. The relative efficiency of unequal versus equal cluster sizes defined using the noncentrality parameter suggests a sample size approach that is a flexible alternative and a useful complement to existing methods.

Sample size determination for equivalence assessment with multiple endpoints.

PubMed

Sun, Anna; Dong, Xiaoyu; Tsong, Yi

2014-01-01

Equivalence assessment between a reference and test treatment is often conducted by two one-sided tests (TOST). The corresponding power function and sample size determination can be derived from a joint distribution of the sample mean and sample variance. When an equivalence trial is designed with multiple endpoints, it often involves several sets of two one-sided tests. A naive approach for sample size determination in this case would select the largest sample size required for each endpoint. However, such a method ignores the correlation among endpoints. With the objective to reject all endpoints and when the endpoints are uncorrelated, the power function is the production of all power functions for individual endpoints. With correlated endpoints, the sample size and power should be adjusted for such a correlation. In this article, we propose the exact power function for the equivalence test with multiple endpoints adjusted for correlation under both crossover and parallel designs. We further discuss the differences in sample size for the naive method without and with correlation adjusted methods and illustrate with an in vivo bioequivalence crossover study with area under the curve (AUC) and maximum concentration (Cmax) as the two endpoints.

Large sample area and size are needed for forest soil seed bank studies to ensure low discrepancy with standing vegetation.

PubMed

Shen, You-xin; Liu, Wei-li; Li, Yu-hui; Guan, Hui-lin

2014-01-01

A large number of small-sized samples invariably shows that woody species are absent from forest soil seed banks, leading to a large discrepancy with the seedling bank on the forest floor. We ask: 1) Does this conventional sampling strategy limit the detection of seeds of woody species? 2) Are large sample areas and sample sizes needed for higher recovery of seeds of woody species? We collected 100 samples that were 10 cm (length) × 10 cm (width) × 10 cm (depth), referred to as larger number of small-sized samples (LNSS) in a 1 ha forest plot, and placed them to germinate in a greenhouse, and collected 30 samples that were 1 m × 1 m × 10 cm, referred to as small number of large-sized samples (SNLS) and placed them (10 each) in a nearby secondary forest, shrub land and grass land. Only 15.7% of woody plant species of the forest stand were detected by the 100 LNSS, contrasting with 22.9%, 37.3% and 20.5% woody plant species being detected by SNLS in the secondary forest, shrub land and grassland, respectively. The increased number of species vs. sampled areas confirmed power-law relationships for forest stand, the LNSS and SNLS at all three recipient sites. Our results, although based on one forest, indicate that conventional LNSS did not yield a high percentage of detection for woody species, but SNLS strategy yielded a higher percentage of detection for woody species in the seed bank if samples were exposed to a better field germination environment. A 4 m2 minimum sample area derived from power equations is larger than the sampled area in most studies in the literature. Increased sample size also is needed to obtain an increased sample area if the number of samples is to remain relatively low.

A normative inference approach for optimal sample sizes in decisions from experience

PubMed Central

Ostwald, Dirk; Starke, Ludger; Hertwig, Ralph

2015-01-01

“Decisions from experience” (DFE) refers to a body of work that emerged in research on behavioral decision making over the last decade. One of the major experimental paradigms employed to study experience-based choice is the “sampling paradigm,” which serves as a model of decision making under limited knowledge about the statistical structure of the world. In this paradigm respondents are presented with two payoff distributions, which, in contrast to standard approaches in behavioral economics, are specified not in terms of explicit outcome-probability information, but by the opportunity to sample outcomes from each distribution without economic consequences. Participants are encouraged to explore the distributions until they feel confident enough to decide from which they would prefer to draw from in a final trial involving real monetary payoffs. One commonly employed measure to characterize the behavior of participants in the sampling paradigm is the sample size, that is, the number of outcome draws which participants choose to obtain from each distribution prior to terminating sampling. A natural question that arises in this context concerns the “optimal” sample size, which could be used as a normative benchmark to evaluate human sampling behavior in DFE. In this theoretical study, we relate the DFE sampling paradigm to the classical statistical decision theoretic literature and, under a probabilistic inference assumption, evaluate optimal sample sizes for DFE. In our treatment we go beyond analytically established results by showing how the classical statistical decision theoretic framework can be used to derive optimal sample sizes under arbitrary, but numerically evaluable, constraints. Finally, we critically evaluate the value of deriving optimal sample sizes under this framework as testable predictions for the experimental study of sampling behavior in DFE. PMID:26441720

Estimating population size with correlated sampling unit estimates

Treesearch

David C. Bowden; Gary C. White; Alan B. Franklin; Joseph L. Ganey

2003-01-01

Finite population sampling theory is useful in estimating total population size (abundance) from abundance estimates of each sampled unit (quadrat). We develop estimators that allow correlated quadrat abundance estimates, even for quadrats in different sampling strata. Correlated quadrat abundance estimates based on mark–recapture or distance sampling methods occur...

Estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean.

PubMed

Schillaci, Michael A; Schillaci, Mario E

2009-02-01

The use of small sample sizes in human and primate evolutionary research is commonplace. Estimating how well small samples represent the underlying population, however, is not commonplace. Because the accuracy of determinations of taxonomy, phylogeny, and evolutionary process are dependant upon how well the study sample represents the population of interest, characterizing the uncertainty, or potential error, associated with analyses of small sample sizes is essential. We present a method for estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean using small (n<10) or very small (n < or = 5) sample sizes. This method can be used by researchers to determine post hoc the probability that their sample is a meaningful approximation of the population parameter. We tested the method using a large craniometric data set commonly used by researchers in the field. Given our results, we suggest that sample estimates of the population mean can be reasonable and meaningful even when based on small, and perhaps even very small, sample sizes.

Relationships between media use, body fatness and physical activity in children and youth: a meta-analysis.

PubMed

Marshall, S J; Biddle, S J H; Gorely, T; Cameron, N; Murdey, I

2004-10-01

To review the empirical evidence of associations between television (TV) viewing, video/computer game use and (a) body fatness, and (b) physical activity. Meta-analysis. Published English-language studies were located from computerized literature searches, bibliographies of primary studies and narrative reviews, and manual searches of personal archives. Included studies presented at least one empirical association between TV viewing, video/computer game use and body fatness or physical activity among samples of children and youth aged 3-18 y. The mean sample-weighted corrected effect size (Pearson r). Based on data from 52 independent samples, the mean sample-weighted effect size between TV viewing and body fatness was 0.066 (95% CI=0.056-0.078; total N=44,707). The sample-weighted fully corrected effect size was 0.084. Based on data from six independent samples, the mean sample-weighted effect size between video/computer game use and body fatness was 0.070 (95% CI=-0.048 to 0.188; total N=1,722). The sample-weighted fully corrected effect size was 0.128. Based on data from 39 independent samples, the mean sample-weighted effect size between TV viewing and physical activity was -0.096 (95% CI=-0.080 to -0.112; total N=141,505). The sample-weighted fully corrected effect size was -0.129. Based on data from 10 independent samples, the mean sample-weighted effect size between video/computer game use and physical activity was -0.104 (95% CI=-0.080 to -0.128; total N=119,942). The sample-weighted fully corrected effect size was -0.141. A statistically significant relationship exists between TV viewing and body fatness among children and youth although it is likely to be too small to be of substantial clinical relevance. The relationship between TV viewing and physical activity is small but negative. The strength of these relationships remains virtually unchanged even after correcting for common sources of bias known to impact study outcomes. While the total amount of time per day engaged in sedentary behavior is inevitably prohibitive of physical activity, media-based inactivity may be unfairly implicated in recent epidemiologic trends of overweight and obesity among children and youth. Relationships between sedentary behavior and health are unlikely to be explained using single markers of inactivity, such as TV viewing or video/computer game use.

Assessment of sampling stability in ecological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.

1988-01-01

A simulation study was undertaken to assess the sampling stability of the variable loadings in linear discriminant function analysis. A factorial design was used for the factors of multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. A review of 60 published studies and 142 individual analyses indicated that sample sizes in ecological studies often have met that requirement. However, individual group sample sizes frequently were very unequal, and checks of assumptions usually were not reported. The authors recommend that ecologists obtain group sample sizes that are at least three times as large as the number of variables measured.

A note on sample size calculation for mean comparisons based on noncentral t-statistics.

PubMed

Chow, Shein-Chung; Shao, Jun; Wang, Hansheng

2002-11-01

One-sample and two-sample t-tests are commonly used in analyzing data from clinical trials in comparing mean responses from two drug products. During the planning stage of a clinical study, a crucial step is the sample size calculation, i.e., the determination of the number of subjects (patients) needed to achieve a desired power (e.g., 80%) for detecting a clinically meaningful difference in the mean drug responses. Based on noncentral t-distributions, we derive some sample size calculation formulas for testing equality, testing therapeutic noninferiority/superiority, and testing therapeutic equivalence, under the popular one-sample design, two-sample parallel design, and two-sample crossover design. Useful tables are constructed and some examples are given for illustration.

A computer program for sample size computations for banding studies

USGS Publications Warehouse

Wilson, K.R.; Nichols, J.D.; Hines, J.E.

1989-01-01

Sample sizes necessary for estimating survival rates of banded birds, adults and young, are derived based on specified levels of precision. The banding study can be new or ongoing. The desired coefficient of variation (CV) for annual survival estimates, the CV for mean annual survival estimates, and the length of the study must be specified to compute sample sizes. A computer program is available for computation of the sample sizes, and a description of the input and output is provided.

Determination of the influence of dispersion pattern of pesticide-resistant individuals on the reliability of resistance estimates using different sampling plans.

PubMed

Shah, R; Worner, S P; Chapman, R B

2012-10-01

Pesticide resistance monitoring includes resistance detection and subsequent documentation/ measurement. Resistance detection would require at least one (≥1) resistant individual(s) to be present in a sample to initiate management strategies. Resistance documentation, on the other hand, would attempt to get an estimate of the entire population (≥90%) of the resistant individuals. A computer simulation model was used to compare the efficiency of simple random and systematic sampling plans to detect resistant individuals and to document their frequencies when the resistant individuals were randomly or patchily distributed. A patchy dispersion pattern of resistant individuals influenced the sampling efficiency of systematic sampling plans while the efficiency of random sampling was independent of such patchiness. When resistant individuals were randomly distributed, sample sizes required to detect at least one resistant individual (resistance detection) with a probability of 0.95 were 300 (1%) and 50 (10% and 20%); whereas, when resistant individuals were patchily distributed, using systematic sampling, sample sizes required for such detection were 6000 (1%), 600 (10%) and 300 (20%). Sample sizes of 900 and 400 would be required to detect ≥90% of resistant individuals (resistance documentation) with a probability of 0.95 when resistant individuals were randomly dispersed and present at a frequency of 10% and 20%, respectively; whereas, when resistant individuals were patchily distributed, using systematic sampling, a sample size of 3000 and 1500, respectively, was necessary. Small sample sizes either underestimated or overestimated the resistance frequency. A simple random sampling plan is, therefore, recommended for insecticide resistance detection and subsequent documentation.

The relationship between national-level carbon dioxide emissions and population size: an assessment of regional and temporal variation, 1960-2005.

PubMed

Jorgenson, Andrew K; Clark, Brett

2013-01-01

This study examines the regional and temporal differences in the statistical relationship between national-level carbon dioxide emissions and national-level population size. The authors analyze panel data from 1960 to 2005 for a diverse sample of nations, and employ descriptive statistics and rigorous panel regression modeling techniques. Initial descriptive analyses indicate that all regions experienced overall increases in carbon emissions and population size during the 45-year period of investigation, but with notable differences. For carbon emissions, the sample of countries in Asia experienced the largest percent increase, followed by countries in Latin America, Africa, and lastly the sample of relatively affluent countries in Europe, North America, and Oceania combined. For population size, the sample of countries in Africa experienced the largest percent increase, followed countries in Latin America, Asia, and the combined sample of countries in Europe, North America, and Oceania. Findings for two-way fixed effects panel regression elasticity models of national-level carbon emissions indicate that the estimated elasticity coefficient for population size is much smaller for nations in Africa than for nations in other regions of the world. Regarding potential temporal changes, from 1960 to 2005 the estimated elasticity coefficient for population size decreased by 25% for the sample of Africa countries, 14% for the sample of Asia countries, 6.5% for the sample of Latin America countries, but remained the same in size for the sample of countries in Europe, North America, and Oceania. Overall, while population size continues to be the primary driver of total national-level anthropogenic carbon dioxide emissions, the findings for this study highlight the need for future research and policies to recognize that the actual impacts of population size on national-level carbon emissions differ across both time and region.

Sample size calculation for a proof of concept study.

PubMed

Yin, Yin

2002-05-01

Sample size calculation is vital for a confirmatory clinical trial since the regulatory agencies require the probability of making Type I error to be significantly small, usually less than 0.05 or 0.025. However, the importance of the sample size calculation for studies conducted by a pharmaceutical company for internal decision making, e.g., a proof of concept (PoC) study, has not received enough attention. This article introduces a Bayesian method that identifies the information required for planning a PoC and the process of sample size calculation. The results will be presented in terms of the relationships between the regulatory requirements, the probability of reaching the regulatory requirements, the goalpost for PoC, and the sample size used for PoC.

Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.

PubMed

Morgan, Timothy M; Case, L Douglas

2013-07-05

In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time. We show how sample sizes can be calculated by making conservative assumptions regarding the correlations for a variety of covariance structures. The most conservative choice for the correlation depends on the covariance structure and the number of repeated measures. In the absence of good estimates of the correlations, the sample size is often based on a two-sample t-test, making the 'ultra' conservative and unrealistic assumption that there are zero correlations between the baseline and follow-up measures while at the same time assuming there are perfect correlations between the follow-up measures. Compared to the case of taking a single measurement, substantial savings in sample size can be realized by accounting for the repeated measures, even with very conservative assumptions regarding the parameters of the assumed correlation matrix. Assuming compound symmetry, the sample size from the two-sample t-test calculation can be reduced at least 44%, 56%, and 61% for repeated measures analysis of covariance by taking 2, 3, and 4 follow-up measures, respectively. The results offer a rational basis for determining a fairly conservative, yet efficient, sample size for clinical trials with repeated measures and a baseline value.

Sample size, confidence, and contingency judgement.

PubMed

Clément, Mélanie; Mercier, Pierre; Pastò, Luigi

2002-06-01

According to statistical models, the acquisition function of contingency judgement is due to confidence increasing with sample size. According to associative models, the function reflects the accumulation of associative strength on which the judgement is based. Which view is right? Thirty university students assessed the relation between a fictitious medication and a symptom of skin discoloration in conditions that varied sample size (4, 6, 8 or 40 trials) and contingency (delta P = .20, .40, .60 or .80). Confidence was also collected. Contingency judgement was lower for smaller samples, while confidence level correlated inversely with sample size. This dissociation between contingency judgement and confidence contradicts the statistical perspective.

An internal pilot design for prospective cancer screening trials with unknown disease prevalence.

PubMed

Brinton, John T; Ringham, Brandy M; Glueck, Deborah H

2015-10-13

For studies that compare the diagnostic accuracy of two screening tests, the sample size depends on the prevalence of disease in the study population, and on the variance of the outcome. Both parameters may be unknown during the design stage, which makes finding an accurate sample size difficult. To solve this problem, we propose adapting an internal pilot design. In this adapted design, researchers will accrue some percentage of the planned sample size, then estimate both the disease prevalence and the variances of the screening tests. The updated estimates of the disease prevalence and variance are used to conduct a more accurate power and sample size calculation. We demonstrate that in large samples, the adapted internal pilot design produces no Type I inflation. For small samples (N less than 50), we introduce a novel adjustment of the critical value to control the Type I error rate. We apply the method to two proposed prospective cancer screening studies: 1) a small oral cancer screening study in individuals with Fanconi anemia and 2) a large oral cancer screening trial. Conducting an internal pilot study without adjusting the critical value can cause Type I error rate inflation in small samples, but not in large samples. An internal pilot approach usually achieves goal power and, for most studies with sample size greater than 50, requires no Type I error correction. Further, we have provided a flexible and accurate approach to bound Type I error below a goal level for studies with small sample size.

Does increasing the size of bi-weekly samples of records influence results when using the Global Trigger Tool? An observational study of retrospective record reviews of two different sample sizes.

PubMed

Mevik, Kjersti; Griffin, Frances A; Hansen, Tonje E; Deilkås, Ellen T; Vonen, Barthold

2016-04-25

To investigate the impact of increasing sample of records reviewed bi-weekly with the Global Trigger Tool method to identify adverse events in hospitalised patients. Retrospective observational study. A Norwegian 524-bed general hospital trust. 1920 medical records selected from 1 January to 31 December 2010. Rate, type and severity of adverse events identified in two different samples sizes of records selected as 10 and 70 records, bi-weekly. In the large sample, 1.45 (95% CI 1.07 to 1.97) times more adverse events per 1000 patient days (39.3 adverse events/1000 patient days) were identified than in the small sample (27.2 adverse events/1000 patient days). Hospital-acquired infections were the most common category of adverse events in both the samples, and the distributions of the other categories of adverse events did not differ significantly between the samples. The distribution of severity level of adverse events did not differ between the samples. The findings suggest that while the distribution of categories and severity are not dependent on the sample size, the rate of adverse events is. Further studies are needed to conclude if the optimal sample size may need to be adjusted based on the hospital size in order to detect a more accurate rate of adverse events. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Estimation After a Group Sequential Trial.

PubMed

Milanzi, Elasma; Molenberghs, Geert; Alonso, Ariel; Kenward, Michael G; Tsiatis, Anastasios A; Davidian, Marie; Verbeke, Geert

2015-10-01

Group sequential trials are one important instance of studies for which the sample size is not fixed a priori but rather takes one of a finite set of pre-specified values, dependent on the observed data. Much work has been devoted to the inferential consequences of this design feature. Molenberghs et al (2012) and Milanzi et al (2012) reviewed and extended the existing literature, focusing on a collection of seemingly disparate, but related, settings, namely completely random sample sizes, group sequential studies with deterministic and random stopping rules, incomplete data, and random cluster sizes. They showed that the ordinary sample average is a viable option for estimation following a group sequential trial, for a wide class of stopping rules and for random outcomes with a distribution in the exponential family. Their results are somewhat surprising in the sense that the sample average is not optimal, and further, there does not exist an optimal, or even, unbiased linear estimator. However, the sample average is asymptotically unbiased, both conditionally upon the observed sample size as well as marginalized over it. By exploiting ignorability they showed that the sample average is the conventional maximum likelihood estimator. They also showed that a conditional maximum likelihood estimator is finite sample unbiased, but is less efficient than the sample average and has the larger mean squared error. Asymptotically, the sample average and the conditional maximum likelihood estimator are equivalent. This previous work is restricted, however, to the situation in which the the random sample size can take only two values, N = n or N = 2 n . In this paper, we consider the more practically useful setting of sample sizes in a the finite set { n 1 , n 2 , …, n L }. It is shown that the sample average is then a justifiable estimator , in the sense that it follows from joint likelihood estimation, and it is consistent and asymptotically unbiased. We also show why simulations can give the false impression of bias in the sample average when considered conditional upon the sample size. The consequence is that no corrections need to be made to estimators following sequential trials. When small-sample bias is of concern, the conditional likelihood estimator provides a relatively straightforward modification to the sample average. Finally, it is shown that classical likelihood-based standard errors and confidence intervals can be applied, obviating the need for technical corrections.

The cost of large numbers of hypothesis tests on power, effect size and sample size.

PubMed

Lazzeroni, L C; Ray, A

2012-01-01

Advances in high-throughput biology and computer science are driving an exponential increase in the number of hypothesis tests in genomics and other scientific disciplines. Studies using current genotyping platforms frequently include a million or more tests. In addition to the monetary cost, this increase imposes a statistical cost owing to the multiple testing corrections needed to avoid large numbers of false-positive results. To safeguard against the resulting loss of power, some have suggested sample sizes on the order of tens of thousands that can be impractical for many diseases or may lower the quality of phenotypic measurements. This study examines the relationship between the number of tests on the one hand and power, detectable effect size or required sample size on the other. We show that once the number of tests is large, power can be maintained at a constant level, with comparatively small increases in the effect size or sample size. For example at the 0.05 significance level, a 13% increase in sample size is needed to maintain 80% power for ten million tests compared with one million tests, whereas a 70% increase in sample size is needed for 10 tests compared with a single test. Relative costs are less when measured by increases in the detectable effect size. We provide an interactive Excel calculator to compute power, effect size or sample size when comparing study designs or genome platforms involving different numbers of hypothesis tests. The results are reassuring in an era of extreme multiple testing.

Sample size calculations for cluster randomised crossover trials in Australian and New Zealand intensive care research.

PubMed

Arnup, Sarah J; McKenzie, Joanne E; Pilcher, David; Bellomo, Rinaldo; Forbes, Andrew B

2018-06-01

The cluster randomised crossover (CRXO) design provides an opportunity to conduct randomised controlled trials to evaluate low risk interventions in the intensive care setting. Our aim is to provide a tutorial on how to perform a sample size calculation for a CRXO trial, focusing on the meaning of the elements required for the calculations, with application to intensive care trials. We use all-cause in-hospital mortality from the Australian and New Zealand Intensive Care Society Adult Patient Database clinical registry to illustrate the sample size calculations. We show sample size calculations for a two-intervention, two 12-month period, cross-sectional CRXO trial. We provide the formulae, and examples of their use, to determine the number of intensive care units required to detect a risk ratio (RR) with a designated level of power between two interventions for trials in which the elements required for sample size calculations remain constant across all ICUs (unstratified design); and in which there are distinct groups (strata) of ICUs that differ importantly in the elements required for sample size calculations (stratified design). The CRXO design markedly reduces the sample size requirement compared with the parallel-group, cluster randomised design for the example cases. The stratified design further reduces the sample size requirement compared with the unstratified design. The CRXO design enables the evaluation of routinely used interventions that can bring about small, but important, improvements in patient care in the intensive care setting.

Neuromuscular dose-response studies: determining sample size.

PubMed

Kopman, A F; Lien, C A; Naguib, M

2011-02-01

Investigators planning dose-response studies of neuromuscular blockers have rarely used a priori power analysis to determine the minimal sample size their protocols require. Institutional Review Boards and peer-reviewed journals now generally ask for this information. This study outlines a proposed method for meeting these requirements. The slopes of the dose-response relationships of eight neuromuscular blocking agents were determined using regression analysis. These values were substituted for γ in the Hill equation. When this is done, the coefficient of variation (COV) around the mean value of the ED₅₀ for each drug is easily calculated. Using these values, we performed an a priori one-sample two-tailed t-test of the means to determine the required sample size when the allowable error in the ED₅₀ was varied from ±10-20%. The COV averaged 22% (range 15-27%). We used a COV value of 25% in determining the sample size. If the allowable error in finding the mean ED₅₀ is ±15%, a sample size of 24 is needed to achieve a power of 80%. Increasing 'accuracy' beyond this point requires increasing greater sample sizes (e.g. an 'n' of 37 for a ±12% error). On the basis of the results of this retrospective analysis, a total sample size of not less than 24 subjects should be adequate for determining a neuromuscular blocking drug's clinical potency with a reasonable degree of assurance.

Sample size considerations for paired experimental design with incomplete observations of continuous outcomes.

PubMed

Zhu, Hong; Xu, Xiaohan; Ahn, Chul

2017-01-01

Paired experimental design is widely used in clinical and health behavioral studies, where each study unit contributes a pair of observations. Investigators often encounter incomplete observations of paired outcomes in the data collected. Some study units contribute complete pairs of observations, while the others contribute either pre- or post-intervention observations. Statistical inference for paired experimental design with incomplete observations of continuous outcomes has been extensively studied in literature. However, sample size method for such study design is sparsely available. We derive a closed-form sample size formula based on the generalized estimating equation approach by treating the incomplete observations as missing data in a linear model. The proposed method properly accounts for the impact of mixed structure of observed data: a combination of paired and unpaired outcomes. The sample size formula is flexible to accommodate different missing patterns, magnitude of missingness, and correlation parameter values. We demonstrate that under complete observations, the proposed generalized estimating equation sample size estimate is the same as that based on the paired t-test. In the presence of missing data, the proposed method would lead to a more accurate sample size estimate comparing with the crude adjustment. Simulation studies are conducted to evaluate the finite-sample performance of the generalized estimating equation sample size formula. A real application example is presented for illustration.

Probability of coincidental similarity among the orbits of small bodies - I. Pairing

NASA Astrophysics Data System (ADS)

Jopek, Tadeusz Jan; Bronikowska, Małgorzata

2017-09-01

Probability of coincidental clustering among orbits of comets, asteroids and meteoroids depends on many factors like: the size of the orbital sample searched for clusters or the size of the identified group, it is different for groups of 2,3,4,… members. Probability of coincidental clustering is assessed by the numerical simulation, therefore, it depends also on the method used for the synthetic orbits generation. We have tested the impact of some of these factors. For a given size of the orbital sample we have assessed probability of random pairing among several orbital populations of different sizes. We have found how these probabilities vary with the size of the orbital samples. Finally, keeping fixed size of the orbital sample we have shown that the probability of random pairing can be significantly different for the orbital samples obtained by different observation techniques. Also for the user convenience we have obtained several formulae which, for given size of the orbital sample can be used to calculate the similarity threshold corresponding to the small value of the probability of coincidental similarity among two orbits.

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

PubMed

Cui, Zaixu; Gong, Gaolang

2018-06-02

Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accuracies. However, the effects of the ML regression algorithm and sample size on individualized behavioral/cognitive prediction performance have not been comprehensively assessed. To address this issue, the present study included six commonly used ML regression algorithms: ordinary least squares (OLS) regression, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic-net regression, linear support vector regression (LSVR), and relevance vector regression (RVR), to perform specific behavioral/cognitive predictions based on different sample sizes. Specifically, the publicly available resting-state functional MRI (rs-fMRI) dataset from the Human Connectome Project (HCP) was used, and whole-brain resting-state functional connectivity (rsFC) or rsFC strength (rsFCS) were extracted as prediction features. Twenty-five sample sizes (ranged from 20 to 700) were studied by sub-sampling from the entire HCP cohort. The analyses showed that rsFC-based LASSO regression performed remarkably worse than the other algorithms, and rsFCS-based OLS regression performed markedly worse than the other algorithms. Regardless of the algorithm and feature type, both the prediction accuracy and its stability exponentially increased with increasing sample size. The specific patterns of the observed algorithm and sample size effects were well replicated in the prediction using re-testing fMRI data, data processed by different imaging preprocessing schemes, and different behavioral/cognitive scores, thus indicating excellent robustness/generalization of the effects. The current findings provide critical insight into how the selected ML regression algorithm and sample size influence individualized predictions of behavior/cognition and offer important guidance for choosing the ML regression algorithm or sample size in relevant investigations. Copyright © 2018 Elsevier Inc. All rights reserved.

Detecting spatial structures in throughfall data: the effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-04-01

In the last three decades, an increasing number of studies analyzed spatial patterns in throughfall to investigate the consequences of rainfall redistribution for biogeochemical and hydrological processes in forests. In the majority of cases, variograms were used to characterize the spatial properties of the throughfall data. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and an appropriate layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation methods on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with heavy outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling), and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the numbers recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes << 200, our current knowledge about throughfall spatial variability stands on shaky ground.

Detecting spatial structures in throughfall data: The effect of extent, sample size, sampling design, and variogram estimation method

NASA Astrophysics Data System (ADS)

Voss, Sebastian; Zimmermann, Beate; Zimmermann, Alexander

2016-09-01

In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non-Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous throughfall studies relied on method-of-moments variogram estimation and sample sizes ≪200, currently available data are prone to large uncertainties.

Sampling guidelines for oral fluid-based surveys of group-housed animals.

PubMed

Rotolo, Marisa L; Sun, Yaxuan; Wang, Chong; Giménez-Lirola, Luis; Baum, David H; Gauger, Phillip C; Harmon, Karen M; Hoogland, Marlin; Main, Rodger; Zimmerman, Jeffrey J

2017-09-01

Formulas and software for calculating sample size for surveys based on individual animal samples are readily available. However, sample size formulas are not available for oral fluids and other aggregate samples that are increasingly used in production settings. Therefore, the objective of this study was to develop sampling guidelines for oral fluid-based porcine reproductive and respiratory syndrome virus (PRRSV) surveys in commercial swine farms. Oral fluid samples were collected in 9 weekly samplings from all pens in 3 barns on one production site beginning shortly after placement of weaned pigs. Samples (n=972) were tested by real-time reverse-transcription PCR (RT-rtPCR) and the binary results analyzed using a piecewise exponential survival model for interval-censored, time-to-event data with misclassification. Thereafter, simulation studies were used to study the barn-level probability of PRRSV detection as a function of sample size, sample allocation (simple random sampling vs fixed spatial sampling), assay diagnostic sensitivity and specificity, and pen-level prevalence. These studies provided estimates of the probability of detection by sample size and within-barn prevalence. Detection using fixed spatial sampling was as good as, or better than, simple random sampling. Sampling multiple barns on a site increased the probability of detection with the number of barns sampled. These results are relevant to PRRSV control or elimination projects at the herd, regional, or national levels, but the results are also broadly applicable to contagious pathogens of swine for which oral fluid tests of equivalent performance are available. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

40 CFR 80.127 - Sample size guidelines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Sample size guidelines. 80.127 Section 80.127 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) REGULATION OF FUELS AND FUEL ADDITIVES Attest Engagements § 80.127 Sample size guidelines. In performing the...

Suitability of river delta sediment as proppant, Missouri and Niobrara Rivers, Nebraska and South Dakota, 2015

USGS Publications Warehouse

Zelt, Ronald B.; Hobza, Christopher M.; Burton, Bethany L.; Schaepe, Nathaniel J.; Piatak, Nadine

2017-11-16

Sediment management is a challenge faced by reservoir managers who have several potential options, including dredging, for mitigation of storage capacity lost to sedimentation. As sediment is removed from reservoir storage, potential use of the sediment for socioeconomic or ecological benefit could potentially defray some costs of its removal. Rivers that transport a sandy sediment load will deposit the sand load along a reservoir-headwaters reach where the current of the river slackens progressively as its bed approaches and then descends below the reservoir water level. Given a rare combination of factors, a reservoir deposit of alluvial sand has potential to be suitable for use as proppant for hydraulic fracturing in unconventional oil and gas development. In 2015, the U.S. Geological Survey began a program of researching potential sources of proppant sand from reservoirs, with an initial focus on the Missouri River subbasins that receive sand loads from the Nebraska Sand Hills. This report documents the methods and results of assessments of the suitability of river delta sediment as proppant for a pilot study area in the delta headwaters of Lewis and Clark Lake, Nebraska and South Dakota. Results from surface-geophysical surveys of electrical resistivity guided borings to collect 3.7-meter long cores at 25 sites on delta sandbars using the direct-push method to recover duplicate, 3.8-centimeter-diameter cores in April 2015. In addition, the U.S. Geological Survey collected samples of upstream sand sources in the lower Niobrara River valley.At the laboratory, samples were dried, weighed, washed, dried, and weighed again. Exploratory analysis of natural sand for determining its suitability as a proppant involved application of a modified subset of the standard protocols known as American Petroleum Institute (API) Recommended Practice (RP) 19C. The RP19C methods were not intended for exploration-stage evaluation of raw materials. Results for the washed samples are not directly applicable to evaluations of suitability for use as fracture sand because, except for particle-size distribution, the API-recommended practices for assessing proppant properties (sphericity, roundness, bulk density, and crush resistance) require testing of specific proppant size classes. An optical imaging particle-size analyzer was used to make measurements of particle-size distribution and particle shape. Measured samples were sieved to separate the dominant-size fraction, and the separated subsample was further tested for roundness, sphericity, bulk density, and crush resistance.For the bulk washed samples collected from the Missouri River delta, the geometric mean size averaged 0.27 millimeters (mm), 80 percent of the samples were predominantly sand in the API 40/70 size class, and 17 percent were predominantly sand in the API 70/140 size class. Distributions of geometric mean size among the four sandbar complexes were similar, but samples collected from sandbar complex B were slightly coarser sand than those from the other three complexes. The average geometric mean sizes among the four sandbar complexes ranged only from 0.26 to 0.30 mm. For 22 main-stem sampling locations along the lower Niobrara River, geometric mean size averaged 0.26 mm, an average of 61 percent was sand in the API 40/70 size class, and 28 percent was sand in the API 70/140 size class. Average composition for lower Niobrara River samples was 48 percent medium sand, 37 percent fine sand, and about 7 percent each very fine sand and coarse sand fractions. On average, samples were moderately well sorted.Particle shape and strength were assessed for the dominant-size class of each sample. For proppant strength, crush resistance was tested at a predetermined level of stress (34.5 megapascals [MPa], or 5,000 pounds-force per square inch). To meet the API minimum requirement for proppant, after the crush test not more than 10 percent of the tested sample should be finer than the precrush dominant-size class. For particle shape, all samples surpassed the recommended minimum criteria for sphericity and roundness, with most samples being well-rounded. For proppant strength, of 57 crush-resistance tested Missouri River delta samples of 40/70-sized sand, 23 (40 percent) were interpreted as meeting the minimum criterion at 34.5 MPa, or 5,000 pounds-force per square inch. Of 12 tested samples of 70/140-sized sand, 9 (75 percent) of the Missouri River delta samples had less than 10 percent fines by volume following crush testing, achieving the minimum criterion at 34.5 MPa. Crush resistance for delta samples was strongest at sandbar complex A, where 67 percent of tested samples met the 10-percent fines criterion at the 34.5-MPa threshold. This frequency was higher than was indicated by samples from sandbar complexes B, C, and D that had rates of 50, 46, and 42 percent, respectively. The group of sandbar complex A samples also contained the largest percentages of samples dominated by the API 70/140 size class, which overall had a higher percentage of samples meeting the minimum criterion compared to samples dominated by coarser size classes; however, samples from sandbar complex A that had the API 40/70 size class tested also had a higher rate for meeting the minimum criterion (57 percent) than did samples from sandbar complexes B, C, and D (50, 43, and 40 percent, respectively). For samples collected along the lower Niobrara River, of the 25 tested samples of 40/70-sized sand, 9 samples passed the API minimum criterion at 34.5 MPa, but only 3 samples passed the more-stringent criterion of 8 percent postcrush fines. All four tested samples of 70/140 sand passed the minimum criterion at 34.5 MPa, with postcrush fines percentage of at most 4.1 percent.For two reaches of the lower Niobrara River, where hydraulic sorting was energized artificially by the hydraulic head drop at and immediately downstream from Spencer Dam, suitability of channel deposits for potential use as fracture sand was confirmed by test results. All reach A washed samples were well-rounded and had sphericity scores above 0.65, and samples for 80 percent of sampled locations met the crush-resistance criterion at the 34.5-MPa stress level. A conservative lower-bound estimate of sand volume in the reach A deposits was about 86,000 cubic meters. All reach B samples were well-rounded but sphericity averaged 0.63, a little less than the average for upstream reaches A and SP. All four samples tested passed the crush-resistance test at 34.5 MPa. Of three reach B sandbars, two had no more than 3 percent fines after the crush test, surpassing more stringent criteria for crush resistance that accept a maximum of 6 percent fines following the crush test for the API 70/140 size class.Relative to the crush-resistance test results for the API 40/70 size fraction of two samples of mine output from Loup River settling-basin dredge spoils near Genoa, Nebr., four of five reach A sample locations compared favorably. The four samples had increases in fines composition of 1.6–5.9 percentage points, whereas fines in the two mine-output samples increased by an average 6.8 percentage points.

Sample Size for Tablet Compression and Capsule Filling Events During Process Validation.

PubMed

Charoo, Naseem Ahmad; Durivage, Mark; Rahman, Ziyaur; Ayad, Mohamad Haitham

2017-12-01

During solid dosage form manufacturing, the uniformity of dosage units (UDU) is ensured by testing samples at 2 stages, that is, blend stage and tablet compression or capsule/powder filling stage. The aim of this work is to propose a sample size selection approach based on quality risk management principles for process performance qualification (PPQ) and continued process verification (CPV) stages by linking UDU to potential formulation and process risk factors. Bayes success run theorem appeared to be the most appropriate approach among various methods considered in this work for computing sample size for PPQ. The sample sizes for high-risk (reliability level of 99%), medium-risk (reliability level of 95%), and low-risk factors (reliability level of 90%) were estimated to be 299, 59, and 29, respectively. Risk-based assignment of reliability levels was supported by the fact that at low defect rate, the confidence to detect out-of-specification units would decrease which must be supplemented with an increase in sample size to enhance the confidence in estimation. Based on level of knowledge acquired during PPQ and the level of knowledge further required to comprehend process, sample size for CPV was calculated using Bayesian statistics to accomplish reduced sampling design for CPV. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Rasch fit statistics and sample size considerations for polytomous data.

PubMed

Smith, Adam B; Rush, Robert; Fallowfield, Lesley J; Velikova, Galina; Sharpe, Michael

2008-05-29

Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data. Data were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire - 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model. The results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data. It was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges.

Rasch fit statistics and sample size considerations for polytomous data

PubMed Central

Smith, Adam B; Rush, Robert; Fallowfield, Lesley J; Velikova, Galina; Sharpe, Michael

2008-01-01

Background Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data. Methods Data were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire – 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model. Results The results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data. Conclusion It was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges. PMID:18510722

Sample size considerations using mathematical models: an example with Chlamydia trachomatis infection and its sequelae pelvic inflammatory disease.

PubMed

Herzog, Sereina A; Low, Nicola; Berghold, Andrea

2015-06-19

The success of an intervention to prevent the complications of an infection is influenced by the natural history of the infection. Assumptions about the temporal relationship between infection and the development of sequelae can affect the predicted effect size of an intervention and the sample size calculation. This study investigates how a mathematical model can be used to inform sample size calculations for a randomised controlled trial (RCT) using the example of Chlamydia trachomatis infection and pelvic inflammatory disease (PID). We used a compartmental model to imitate the structure of a published RCT. We considered three different processes for the timing of PID development, in relation to the initial C. trachomatis infection: immediate, constant throughout, or at the end of the infectious period. For each process we assumed that, of all women infected, the same fraction would develop PID in the absence of an intervention. We examined two sets of assumptions used to calculate the sample size in a published RCT that investigated the effect of chlamydia screening on PID incidence. We also investigated the influence of the natural history parameters of chlamydia on the required sample size. The assumed event rates and effect sizes used for the sample size calculation implicitly determined the temporal relationship between chlamydia infection and PID in the model. Even small changes in the assumed PID incidence and relative risk (RR) led to considerable differences in the hypothesised mechanism of PID development. The RR and the sample size needed per group also depend on the natural history parameters of chlamydia. Mathematical modelling helps to understand the temporal relationship between an infection and its sequelae and can show how uncertainties about natural history parameters affect sample size calculations when planning a RCT.

How Large Should a Statistical Sample Be?

ERIC Educational Resources Information Center

Menil, Violeta C.; Ye, Ruili

2012-01-01

This study serves as a teaching aid for teachers of introductory statistics. The aim of this study was limited to determining various sample sizes when estimating population proportion. Tables on sample sizes were generated using a C[superscript ++] program, which depends on population size, degree of precision or error level, and confidence…

Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications.

PubMed

Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz

2014-07-01

Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Blinded sample size re-estimation in three-arm trials with 'gold standard' design.

PubMed

Mütze, Tobias; Friede, Tim

2017-10-15

In this article, we study blinded sample size re-estimation in the 'gold standard' design with internal pilot study for normally distributed outcomes. The 'gold standard' design is a three-arm clinical trial design that includes an active and a placebo control in addition to an experimental treatment. We focus on the absolute margin approach to hypothesis testing in three-arm trials at which the non-inferiority of the experimental treatment and the assay sensitivity are assessed by pairwise comparisons. We compare several blinded sample size re-estimation procedures in a simulation study assessing operating characteristics including power and type I error. We find that sample size re-estimation based on the popular one-sample variance estimator results in overpowered trials. Moreover, sample size re-estimation based on unbiased variance estimators such as the Xing-Ganju variance estimator results in underpowered trials, as it is expected because an overestimation of the variance and thus the sample size is in general required for the re-estimation procedure to eventually meet the target power. To overcome this problem, we propose an inflation factor for the sample size re-estimation with the Xing-Ganju variance estimator and show that this approach results in adequately powered trials. Because of favorable features of the Xing-Ganju variance estimator such as unbiasedness and a distribution independent of the group means, the inflation factor does not depend on the nuisance parameter and, therefore, can be calculated prior to a trial. Moreover, we prove that the sample size re-estimation based on the Xing-Ganju variance estimator does not bias the effect estimate. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Comparing fixed sampling with minimizer sampling when using k-mer indexes to find maximal exact matches.

PubMed

Almutairy, Meznah; Torng, Eric

2018-01-01

Bioinformatics applications and pipelines increasingly use k-mer indexes to search for similar sequences. The major problem with k-mer indexes is that they require lots of memory. Sampling is often used to reduce index size and query time. Most applications use one of two major types of sampling: fixed sampling and minimizer sampling. It is well known that fixed sampling will produce a smaller index, typically by roughly a factor of two, whereas it is generally assumed that minimizer sampling will produce faster query times since query k-mers can also be sampled. However, no direct comparison of fixed and minimizer sampling has been performed to verify these assumptions. We systematically compare fixed and minimizer sampling using the human genome as our database. We use the resulting k-mer indexes for fixed sampling and minimizer sampling to find all maximal exact matches between our database, the human genome, and three separate query sets, the mouse genome, the chimp genome, and an NGS data set. We reach the following conclusions. First, using larger k-mers reduces query time for both fixed sampling and minimizer sampling at a cost of requiring more space. If we use the same k-mer size for both methods, fixed sampling requires typically half as much space whereas minimizer sampling processes queries only slightly faster. If we are allowed to use any k-mer size for each method, then we can choose a k-mer size such that fixed sampling both uses less space and processes queries faster than minimizer sampling. The reason is that although minimizer sampling is able to sample query k-mers, the number of shared k-mer occurrences that must be processed is much larger for minimizer sampling than fixed sampling. In conclusion, we argue that for any application where each shared k-mer occurrence must be processed, fixed sampling is the right sampling method.

Comparing fixed sampling with minimizer sampling when using k-mer indexes to find maximal exact matches

PubMed Central

Torng, Eric

2018-01-01

Bioinformatics applications and pipelines increasingly use k-mer indexes to search for similar sequences. The major problem with k-mer indexes is that they require lots of memory. Sampling is often used to reduce index size and query time. Most applications use one of two major types of sampling: fixed sampling and minimizer sampling. It is well known that fixed sampling will produce a smaller index, typically by roughly a factor of two, whereas it is generally assumed that minimizer sampling will produce faster query times since query k-mers can also be sampled. However, no direct comparison of fixed and minimizer sampling has been performed to verify these assumptions. We systematically compare fixed and minimizer sampling using the human genome as our database. We use the resulting k-mer indexes for fixed sampling and minimizer sampling to find all maximal exact matches between our database, the human genome, and three separate query sets, the mouse genome, the chimp genome, and an NGS data set. We reach the following conclusions. First, using larger k-mers reduces query time for both fixed sampling and minimizer sampling at a cost of requiring more space. If we use the same k-mer size for both methods, fixed sampling requires typically half as much space whereas minimizer sampling processes queries only slightly faster. If we are allowed to use any k-mer size for each method, then we can choose a k-mer size such that fixed sampling both uses less space and processes queries faster than minimizer sampling. The reason is that although minimizer sampling is able to sample query k-mers, the number of shared k-mer occurrences that must be processed is much larger for minimizer sampling than fixed sampling. In conclusion, we argue that for any application where each shared k-mer occurrence must be processed, fixed sampling is the right sampling method. PMID:29389989

Four hundred or more participants needed for stable contingency table estimates of clinical prediction rule performance.

PubMed

Kent, Peter; Boyle, Eleanor; Keating, Jennifer L; Albert, Hanne B; Hartvigsen, Jan

2017-02-01

To quantify variability in the results of statistical analyses based on contingency tables and discuss the implications for the choice of sample size for studies that derive clinical prediction rules. An analysis of three pre-existing sets of large cohort data (n = 4,062-8,674) was performed. In each data set, repeated random sampling of various sample sizes, from n = 100 up to n = 2,000, was performed 100 times at each sample size and the variability in estimates of sensitivity, specificity, positive and negative likelihood ratios, posttest probabilities, odds ratios, and risk/prevalence ratios for each sample size was calculated. There were very wide, and statistically significant, differences in estimates derived from contingency tables from the same data set when calculated in sample sizes below 400 people, and typically, this variability stabilized in samples of 400-600 people. Although estimates of prevalence also varied significantly in samples below 600 people, that relationship only explains a small component of the variability in these statistical parameters. To reduce sample-specific variability, contingency tables should consist of 400 participants or more when used to derive clinical prediction rules or test their performance. Copyright © 2016 Elsevier Inc. All rights reserved.

Methods for sample size determination in cluster randomized trials

PubMed Central

Rutterford, Clare; Copas, Andrew; Eldridge, Sandra

2015-01-01

Background: The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster. The assumptions of a simple design effect may not always be met; alternative or more complicated approaches are required. Methods: We summarise a wide range of sample size methods available for cluster randomized trials. For those familiar with sample size calculations for individually randomized trials but with less experience in the clustered case, this manuscript provides formulae for a wide range of scenarios with associated explanation and recommendations. For those with more experience, comprehensive summaries are provided that allow quick identification of methods for a given design, outcome and analysis method. Results: We present first those methods applicable to the simplest two-arm, parallel group, completely randomized design followed by methods that incorporate deviations from this design such as: variability in cluster sizes; attrition; non-compliance; or the inclusion of baseline covariates or repeated measures. The paper concludes with methods for alternative designs. Conclusions: There is a large amount of methodology available for sample size calculations in CRTs. This paper gives the most comprehensive description of published methodology for sample size calculation and provides an important resource for those designing these trials. PMID:26174515

PTM Modeling of Dredged Suspended Sediment at Proposed Polaris Point and Ship Repair Facility CVN Berthing Sites - Apra Harbor, Guam

DTIC Science & Technology

2017-09-01

ADCP locations used for model calibration. ......................................................................... 12 Figure 4-3. Sample water...Example of fine sediment sample [Set d, Sample B30]. (B) Example of coarse sediment sample [Set d, sample B05...Turning Basin average sediment size distribution curve. ................................................... 21 Figure 5-5. Turning Basin average size

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments

PubMed Central

2013-01-01

Background Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. Results To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations. The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. Conclusions We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs. PMID:24160725

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

PubMed

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

Mass spectra features of biomass burning boiler and coal burning boiler emitted particles by single particle aerosol mass spectrometer.

PubMed

Xu, Jiao; Li, Mei; Shi, Guoliang; Wang, Haiting; Ma, Xian; Wu, Jianhui; Shi, Xurong; Feng, Yinchang

2017-11-15

In this study, single particle mass spectra signatures of both coal burning boiler and biomass burning boiler emitted particles were studied. Particle samples were suspended in clean Resuspension Chamber, and analyzed by ELPI and SPAMS simultaneously. The size distribution of BBB (biomass burning boiler sample) and CBB (coal burning boiler sample) are different, as BBB peaks at smaller size, and CBB peaks at larger size. Mass spectra signatures of two samples were studied by analyzing the average mass spectrum of each particle cluster extracted by ART-2a in different size ranges. In conclusion, BBB sample mostly consists of OC and EC containing particles, and a small fraction of K-rich particles in the size range of 0.2-0.5μm. In 0.5-1.0μm, BBB sample consists of EC, OC, K-rich and Al_Silicate containing particles; CBB sample consists of EC, ECOC containing particles, while Al_Silicate (including Al_Ca_Ti_Silicate, Al_Ti_Silicate, Al_Silicate) containing particles got higher fractions as size increase. The similarity of single particle mass spectrum signatures between two samples were studied by analyzing the dot product, results indicated that part of the single particle mass spectra of two samples in the same size range are similar, which bring challenge to the future source apportionment activity by using single particle aerosol mass spectrometer. Results of this study will provide physicochemical information of important sources which contribute to particle pollution, and will support source apportionment activities. Copyright © 2017. Published by Elsevier B.V.

Day and night variation in chemical composition and toxicological responses of size segregated urban air PM samples in a high air pollution situation

NASA Astrophysics Data System (ADS)

Jalava, P. I.; Wang, Q.; Kuuspalo, K.; Ruusunen, J.; Hao, L.; Fang, D.; Väisänen, O.; Ruuskanen, A.; Sippula, O.; Happo, M. S.; Uski, O.; Kasurinen, S.; Torvela, T.; Koponen, H.; Lehtinen, K. E. J.; Komppula, M.; Gu, C.; Jokiniemi, J.; Hirvonen, M.-R.

2015-11-01

Urban air particulate pollution is a known cause for adverse human health effects worldwide. China has encountered air quality problems in recent years due to rapid industrialization. Toxicological effects induced by particulate air pollution vary with particle sizes and season. However, it is not known how distinctively different photochemical activity and different emission sources during the day and the night affect the chemical composition of the PM size ranges and subsequently how it is reflected to the toxicological properties of the PM exposures. The particulate matter (PM) samples were collected in four different size ranges (PM10-2.5; PM2.5-1; PM1-0.2 and PM0.2) with a high volume cascade impactor. The PM samples were extracted with methanol, dried and thereafter used in the chemical and toxicological analyses. RAW264.7 macrophages were exposed to the particulate samples in four different doses for 24 h. Cytotoxicity, inflammatory parameters, cell cycle and genotoxicity were measured after exposure of the cells to particulate samples. Particles were characterized for their chemical composition, including ions, element and PAH compounds, and transmission electron microscopy (TEM) was used to take images of the PM samples. Chemical composition and the induced toxicological responses of the size segregated PM samples showed considerable size dependent differences as well as day to night variation. The PM10-2.5 and the PM0.2 samples had the highest inflammatory potency among the size ranges. Instead, almost all the PM samples were equally cytotoxic and only minor differences were seen in genotoxicity and cell cycle effects. Overall, the PM0.2 samples had the highest toxic potential among the different size ranges in many parameters. PAH compounds in the samples and were generally more abundant during the night than the day, indicating possible photo-oxidation of the PAH compounds due to solar radiation. This was reflected to different toxicity in the PM samples. Some of the day to night difference may have been caused also by differing wind directions transporting air masses from different emission sources during the day and the night. The present findings indicate the important role of the local particle sources and atmospheric processes on the health related toxicological properties of the PM. The varying toxicological responses evoked by the PM samples showed the importance of examining various particle sizes. Especially the detected considerable toxicological activity by PM0.2 size range suggests they're attributable to combustion sources, new particle formation and atmospheric processes.

Magnetic properties of Apollo 14 breccias and their correlation with metamorphism.

NASA Technical Reports Server (NTRS)

Gose, W. A.; Pearce, G. W.; Strangway, D. W.; Larson, E. E.

1972-01-01

The magnetic properties of Apollo 14 breccias can be explained in terms of the grain size distribution of the interstitial iron which is directly related to the metamorphic grade of the sample. In samples 14049 and 14313 iron grains less than 500 A in diameter are dominant as evidenced by a Richter-type magnetic aftereffect and hysteresis measurements. Both samples are of lowest metamorphic grade. The medium metamorphic-grade sample 14321 and the high-grade sample 14312 both show a logarithmic time-dependence of the magnetization indicative of a wide range of relaxation times and thus grain sizes, but sample 14321 contains a stable remanent magnetization whereas sample 14312 does not. This suggests that small multidomain particles (less than 1 micron) are most abundant in sample 14321 while sample 14312 is magnetically controlled by grains greater than 1 micron. The higher the metamorphic grade, the larger the grain size of the iron controlling the magnetic properties.

An audit of the statistics and the comparison with the parameter in the population

NASA Astrophysics Data System (ADS)

Bujang, Mohamad Adam; Sa'at, Nadiah; Joys, A. Reena; Ali, Mariana Mohamad

2015-10-01

The sufficient sample size that is needed to closely estimate the statistics for particular parameters are use to be an issue. Although sample size might had been calculated referring to objective of the study, however, it is difficult to confirm whether the statistics are closed with the parameter for a particular population. All these while, guideline that uses a p-value less than 0.05 is widely used as inferential evidence. Therefore, this study had audited results that were analyzed from various sub sample and statistical analyses and had compared the results with the parameters in three different populations. Eight types of statistical analysis and eight sub samples for each statistical analysis were analyzed. Results found that the statistics were consistent and were closed to the parameters when the sample study covered at least 15% to 35% of population. Larger sample size is needed to estimate parameter that involve with categorical variables compared with numerical variables. Sample sizes with 300 to 500 are sufficient to estimate the parameters for medium size of population.

Qualitative Meta-Analysis on the Hospital Task: Implications for Research

ERIC Educational Resources Information Center

Noll, Jennifer; Sharma, Sashi

2014-01-01

The "law of large numbers" indicates that as sample size increases, sample statistics become less variable and more closely estimate their corresponding population parameters. Different research studies investigating how people consider sample size when evaluating the reliability of a sample statistic have found a wide range of…

Sampling strategies for estimating brook trout effective population size

Treesearch

Andrew R. Whiteley; Jason A. Coombs; Mark Hudy; Zachary Robinson; Keith H. Nislow; Benjamin H. Letcher

2012-01-01

The influence of sampling strategy on estimates of effective population size (Ne) from single-sample genetic methods has not been rigorously examined, though these methods are increasingly used. For headwater salmonids, spatially close kin association among age-0 individuals suggests that sampling strategy (number of individuals and location from...

40 CFR 90.706 - Engine sample selection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... = emission test result for an individual engine. x = mean of emission test results of the actual sample. FEL... test with the last test result from the previous model year and then calculate the required sample size.... Test results used to calculate the variables in the following Sample Size Equation must be final...

The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings.

PubMed

Lorca-Puls, Diego L; Gajardo-Vidal, Andrea; White, Jitrachote; Seghier, Mohamed L; Leff, Alexander P; Green, David W; Crinion, Jenny T; Ludersdorfer, Philipp; Hope, Thomas M H; Bowman, Howard; Price, Cathy J

2018-07-01

This study investigated how sample size affects the reproducibility of findings from univariate voxel-based lesion-deficit analyses (e.g., voxel-based lesion-symptom mapping and voxel-based morphometry). Our effect of interest was the strength of the mapping between brain damage and speech articulation difficulties, as measured in terms of the proportion of variance explained. First, we identified a region of interest by searching on a voxel-by-voxel basis for brain areas where greater lesion load was associated with poorer speech articulation using a large sample of 360 right-handed English-speaking stroke survivors. We then randomly drew thousands of bootstrap samples from this data set that included either 30, 60, 90, 120, 180, or 360 patients. For each resample, we recorded effect size estimates and p values after conducting exactly the same lesion-deficit analysis within the previously identified region of interest and holding all procedures constant. The results show (1) how often small effect sizes in a heterogeneous population fail to be detected; (2) how effect size and its statistical significance varies with sample size; (3) how low-powered studies (due to small sample sizes) can greatly over-estimate as well as under-estimate effect sizes; and (4) how large sample sizes (N ≥ 90) can yield highly significant p values even when effect sizes are so small that they become trivial in practical terms. The implications of these findings for interpreting the results from univariate voxel-based lesion-deficit analyses are discussed. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Sampling stratospheric aerosols with impactors

NASA Technical Reports Server (NTRS)

Oberbeck, Verne R.

1989-01-01

Derivation of statistically significant size distributions from impactor samples of rarefield stratospheric aerosols imposes difficult sampling constraints on collector design. It is shown that it is necessary to design impactors of different size for each range of aerosol size collected so as to obtain acceptable levels of uncertainty with a reasonable amount of data reduction.

Effect of roll hot press temperature on crystallite size of PVDF film

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartono, Ambran, E-mail: ambranhartono@yahoo.com; Sanjaya, Edi; Djamal, Mitra

2014-03-24

Fabrication PVDF films have been made using Hot Roll Press. Preparation of samples carried out for nine different temperatures. This condition is carried out to see the effect of Roll Hot Press temperature on the size of the crystallite of PVDF films. To obtain the diffraction pattern of sample characterization is performed using X-Ray Diffraction. Furthermore, from the diffraction pattern is obtained, the calculation to determine the crystallite size of the sample by using the Scherrer equation. From the experimental results and the calculation of crystallite sizes obtained for the samples with temperature 130 °C up to 170 °C respectivelymore » increased from 7.2 nm up to 20.54 nm. These results show that increasing temperatures will also increase the size of the crystallite of the sample. This happens because with the increasing temperature causes the higher the degree of crystallization of PVDF film sample is formed, so that the crystallite size also increases. This condition indicates that the specific volume or size of the crystals depends on the magnitude of the temperature as it has been studied by Nakagawa.« less

Influence of sampling window size and orientation on parafoveal cone packing density

PubMed Central

Lombardo, Marco; Serrao, Sebastiano; Ducoli, Pietro; Lombardo, Giuseppe

2013-01-01

We assessed the agreement between sampling windows of different size and orientation on packing density estimates in images of the parafoveal cone mosaic acquired using a flood-illumination adaptive optics retinal camera. Horizontal and vertical oriented sampling windows of different size (320x160 µm, 160x80 µm and 80x40 µm) were selected in two retinal locations along the horizontal meridian in one eye of ten subjects. At each location, cone density tended to decline with decreasing sampling area. Although the differences in cone density estimates were not statistically significant, Bland-Altman plots showed that the agreement between cone density estimated within the different sampling window conditions was moderate. The percentage of the preferred packing arrangements of cones by Voronoi tiles was slightly affected by window size and orientation. The results illustrated the high importance of specifying the size and orientation of the sampling window used to derive cone metric estimates to facilitate comparison of different studies. PMID:24009995

Simulation analyses of space use: Home range estimates, variability, and sample size

USGS Publications Warehouse

Bekoff, Marc; Mech, L. David

1984-01-01

Simulations of space use by animals were run to determine the relationship among home range area estimates, variability, and sample size (number of locations). As sample size increased, home range size increased asymptotically, whereas variability decreased among mean home range area estimates generated by multiple simulations for the same sample size. Our results suggest that field workers should ascertain between 100 and 200 locations in order to estimate reliably home range area. In some cases, this suggested guideline is higher than values found in the few published studies in which the relationship between home range area and number of locations is addressed. Sampling differences for small species occupying relatively small home ranges indicate that fewer locations may be sufficient to allow for a reliable estimate of home range. Intraspecific variability in social status (group member, loner, resident, transient), age, sex, reproductive condition, and food resources also have to be considered, as do season, habitat, and differences in sampling and analytical methods. Comparative data still are needed.

The choice of sample size: a mixed Bayesian / frequentist approach.

PubMed

Pezeshk, Hamid; Nematollahi, Nader; Maroufy, Vahed; Gittins, John

2009-04-01

Sample size computations are largely based on frequentist or classical methods. In the Bayesian approach the prior information on the unknown parameters is taken into account. In this work we consider a fully Bayesian approach to the sample size determination problem which was introduced by Grundy et al. and developed by Lindley. This approach treats the problem as a decision problem and employs a utility function to find the optimal sample size of a trial. Furthermore, we assume that a regulatory authority, which is deciding on whether or not to grant a licence to a new treatment, uses a frequentist approach. We then find the optimal sample size for the trial by maximising the expected net benefit, which is the expected benefit of subsequent use of the new treatment minus the cost of the trial.

Sample size calculation for stepped wedge and other longitudinal cluster randomised trials.

PubMed

Hooper, Richard; Teerenstra, Steven; de Hoop, Esther; Eldridge, Sandra

2016-11-20

The sample size required for a cluster randomised trial is inflated compared with an individually randomised trial because outcomes of participants from the same cluster are correlated. Sample size calculations for longitudinal cluster randomised trials (including stepped wedge trials) need to take account of at least two levels of clustering: the clusters themselves and times within clusters. We derive formulae for sample size for repeated cross-section and closed cohort cluster randomised trials with normally distributed outcome measures, under a multilevel model allowing for variation between clusters and between times within clusters. Our formulae agree with those previously described for special cases such as crossover and analysis of covariance designs, although simulation suggests that the formulae could underestimate required sample size when the number of clusters is small. Whether using a formula or simulation, a sample size calculation requires estimates of nuisance parameters, which in our model include the intracluster correlation, cluster autocorrelation, and individual autocorrelation. A cluster autocorrelation less than 1 reflects a situation where individuals sampled from the same cluster at different times have less correlated outcomes than individuals sampled from the same cluster at the same time. Nuisance parameters could be estimated from time series obtained in similarly clustered settings with the same outcome measure, using analysis of variance to estimate variance components. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Treatment Trials for Neonatal Seizures: The Effect of Design on Sample Size

PubMed Central

Stevenson, Nathan J.; Boylan, Geraldine B.; Hellström-Westas, Lena; Vanhatalo, Sampsa

2016-01-01

Neonatal seizures are common in the neonatal intensive care unit. Clinicians treat these seizures with several anti-epileptic drugs (AEDs) to reduce seizures in a neonate. Current AEDs exhibit sub-optimal efficacy and several randomized control trials (RCT) of novel AEDs are planned. The aim of this study was to measure the influence of trial design on the required sample size of a RCT. We used seizure time courses from 41 term neonates with hypoxic ischaemic encephalopathy to build seizure treatment trial simulations. We used five outcome measures, three AED protocols, eight treatment delays from seizure onset (Td) and four levels of trial AED efficacy to simulate different RCTs. We performed power calculations for each RCT design and analysed the resultant sample size. We also assessed the rate of false positives, or placebo effect, in typical uncontrolled studies. We found that the false positive rate ranged from 5 to 85% of patients depending on RCT design. For controlled trials, the choice of outcome measure had the largest effect on sample size with median differences of 30.7 fold (IQR: 13.7–40.0) across a range of AED protocols, Td and trial AED efficacy (p<0.001). RCTs that compared the trial AED with positive controls required sample sizes with a median fold increase of 3.2 (IQR: 1.9–11.9; p<0.001). Delays in AED administration from seizure onset also increased the required sample size 2.1 fold (IQR: 1.7–2.9; p<0.001). Subgroup analysis showed that RCTs in neonates treated with hypothermia required a median fold increase in sample size of 2.6 (IQR: 2.4–3.0) compared to trials in normothermic neonates (p<0.001). These results show that RCT design has a profound influence on the required sample size. Trials that use a control group, appropriate outcome measure, and control for differences in Td between groups in analysis will be valid and minimise sample size. PMID:27824913

The Relationship between National-Level Carbon Dioxide Emissions and Population Size: An Assessment of Regional and Temporal Variation, 1960–2005

PubMed Central

Jorgenson, Andrew K.; Clark, Brett

2013-01-01

This study examines the regional and temporal differences in the statistical relationship between national-level carbon dioxide emissions and national-level population size. The authors analyze panel data from 1960 to 2005 for a diverse sample of nations, and employ descriptive statistics and rigorous panel regression modeling techniques. Initial descriptive analyses indicate that all regions experienced overall increases in carbon emissions and population size during the 45-year period of investigation, but with notable differences. For carbon emissions, the sample of countries in Asia experienced the largest percent increase, followed by countries in Latin America, Africa, and lastly the sample of relatively affluent countries in Europe, North America, and Oceania combined. For population size, the sample of countries in Africa experienced the largest percent increase, followed countries in Latin America, Asia, and the combined sample of countries in Europe, North America, and Oceania. Findings for two-way fixed effects panel regression elasticity models of national-level carbon emissions indicate that the estimated elasticity coefficient for population size is much smaller for nations in Africa than for nations in other regions of the world. Regarding potential temporal changes, from 1960 to 2005 the estimated elasticity coefficient for population size decreased by 25% for the sample of Africa countries, 14% for the sample of Asia countries, 6.5% for the sample of Latin America countries, but remained the same in size for the sample of countries in Europe, North America, and Oceania. Overall, while population size continues to be the primary driver of total national-level anthropogenic carbon dioxide emissions, the findings for this study highlight the need for future research and policies to recognize that the actual impacts of population size on national-level carbon emissions differ across both time and region. PMID:23437323

Sampling methods, dispersion patterns, and fixed precision sequential sampling plans for western flower thrips (Thysanoptera: Thripidae) and cotton fleahoppers (Hemiptera: Miridae) in cotton.

PubMed

Parajulee, M N; Shrestha, R B; Leser, J F

2006-04-01

A 2-yr field study was conducted to examine the effectiveness of two sampling methods (visual and plant washing techniques) for western flower thrips, Frankliniella occidentalis (Pergande), and five sampling methods (visual, beat bucket, drop cloth, sweep net, and vacuum) for cotton fleahopper, Pseudatomoscelis seriatus (Reuter), in Texas cotton, Gossypium hirsutum (L.), and to develop sequential sampling plans for each pest. The plant washing technique gave similar results to the visual method in detecting adult thrips, but the washing technique detected significantly higher number of thrips larvae compared with the visual sampling. Visual sampling detected the highest number of fleahoppers followed by beat bucket, drop cloth, vacuum, and sweep net sampling, with no significant difference in catch efficiency between vacuum and sweep net methods. However, based on fixed precision cost reliability, the sweep net sampling was the most cost-effective method followed by vacuum, beat bucket, drop cloth, and visual sampling. Taylor's Power Law analysis revealed that the field dispersion patterns of both thrips and fleahoppers were aggregated throughout the crop growing season. For thrips management decision based on visual sampling (0.25 precision), 15 plants were estimated to be the minimum sample size when the estimated population density was one thrips per plant, whereas the minimum sample size was nine plants when thrips density approached 10 thrips per plant. The minimum visual sample size for cotton fleahoppers was 16 plants when the density was one fleahopper per plant, but the sample size decreased rapidly with an increase in fleahopper density, requiring only four plants to be sampled when the density was 10 fleahoppers per plant. Sequential sampling plans were developed and validated with independent data for both thrips and cotton fleahoppers.

Further improvement of hydrostatic pressure sample injection for microchip electrophoresis.

PubMed

Luo, Yong; Zhang, Qingquan; Qin, Jianhua; Lin, Bingcheng

2007-12-01

Hydrostatic pressure sample injection method is able to minimize the number of electrodes needed for a microchip electrophoresis process; however, it neither can be applied for electrophoretic DNA sizing, nor can be implemented on the widely used single-cross microchip. This paper presents an injector design that makes the hydrostatic pressure sample injection method suitable for DNA sizing. By introducing an assistant channel into the normal double-cross injector, a rugged DNA sample plug suitable for sizing can be successfully formed within the cross area during the sample loading. This paper also demonstrates that the hydrostatic pressure sample injection can be performed in the single-cross microchip by controlling the radial position of the detection point in the separation channel. Rhodamine 123 and its derivative as model sample were successfully separated.

Estimation of sample size and testing power (part 5).

PubMed

Hu, Liang-ping; Bao, Xiao-lei; Guan, Xue; Zhou, Shi-guo

2012-02-01

Estimation of sample size and testing power is an important component of research design. This article introduced methods for sample size and testing power estimation of difference test for quantitative and qualitative data with the single-group design, the paired design or the crossover design. To be specific, this article introduced formulas for sample size and testing power estimation of difference test for quantitative and qualitative data with the above three designs, the realization based on the formulas and the POWER procedure of SAS software and elaborated it with examples, which will benefit researchers for implementing the repetition principle.

Effect of Mechanical Impact Energy on the Sorption and Diffusion of Moisture in Reinforced Polymer Composite Samples on Variation of Their Sizes

NASA Astrophysics Data System (ADS)

Startsev, V. O.; Il'ichev, A. V.

2018-05-01

The effect of mechanical impact energy on the sorption and diffusion of moisture in polymer composite samples on variation of their sizes was investigated. Square samples, with sides of 40, 60, 80, and 100 mm, made of a KMKU-2m-120.E0,1 carbon-fiber and KMKS-2m.120.T10 glass-fiber plastics with different resistances to calibrated impacts, were compared. Impact loading diagrams of the samples in relation to their sizes and impact energy were analyzed. It is shown that the moisture saturation and moisture diffusion coefficient of the impact-damaged materials can be modeled by Fick's second law with account of impact energy and sample sizes.

The attention-weighted sample-size model of visual short-term memory: Attention capture predicts resource allocation and memory load.

PubMed

Smith, Philip L; Lilburn, Simon D; Corbett, Elaine A; Sewell, David K; Kyllingsbæk, Søren

2016-09-01

We investigated the capacity of visual short-term memory (VSTM) in a phase discrimination task that required judgments about the configural relations between pairs of black and white features. Sewell et al. (2014) previously showed that VSTM capacity in an orientation discrimination task was well described by a sample-size model, which views VSTM as a resource comprised of a finite number of noisy stimulus samples. The model predicts the invariance of [Formula: see text] , the sum of squared sensitivities across items, for displays of different sizes. For phase discrimination, the set-size effect significantly exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items in the display captures attention and receives a disproportionate share of resources. The choice probabilities and response time distributions from the task were well described by a diffusion decision model in which the drift rates embodied the assumptions of the attention-weighted sample-size model. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Differentiating gold nanorod samples using particle size and shape distributions from transmission electron microscope images

NASA Astrophysics Data System (ADS)

Grulke, Eric A.; Wu, Xiaochun; Ji, Yinglu; Buhr, Egbert; Yamamoto, Kazuhiro; Song, Nam Woong; Stefaniak, Aleksandr B.; Schwegler-Berry, Diane; Burchett, Woodrow W.; Lambert, Joshua; Stromberg, Arnold J.

2018-04-01

Size and shape distributions of gold nanorod samples are critical to their physico-chemical properties, especially their longitudinal surface plasmon resonance. This interlaboratory comparison study developed methods for measuring and evaluating size and shape distributions for gold nanorod samples using transmission electron microscopy (TEM) images. The objective was to determine whether two different samples, which had different performance attributes in their application, were different with respect to their size and/or shape descriptor distributions. Touching particles in the captured images were identified using a ruggedness shape descriptor. Nanorods could be distinguished from nanocubes using an elongational shape descriptor. A non-parametric statistical test showed that cumulative distributions of an elongational shape descriptor, that is, the aspect ratio, were statistically different between the two samples for all laboratories. While the scale parameters of size and shape distributions were similar for both samples, the width parameters of size and shape distributions were statistically different. This protocol fulfills an important need for a standardized approach to measure gold nanorod size and shape distributions for applications in which quantitative measurements and comparisons are important. Furthermore, the validated protocol workflow can be automated, thus providing consistent and rapid measurements of nanorod size and shape distributions for researchers, regulatory agencies, and industry.

Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions.

PubMed

Fiedler, Klaus; Kareev, Yaakov; Avrahami, Judith; Beier, Susanne; Kutzner, Florian; Hütter, Mandy

2016-01-01

Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience.

Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference

PubMed Central

Karcher, Michael D.; Palacios, Julia A.; Bedford, Trevor; Suchard, Marc A.; Minin, Vladimir N.

2016-01-01

Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalescent model for the sampled individuals’ genealogy and then integrating over all possible genealogies via Monte Carlo or, less efficiently, by conditioning on one genealogy estimated from the sequence data. However, when analyzing sequences sampled serially through time, current methods implicitly assume either that sampling times are fixed deterministically by the data collection protocol or that their distribution does not depend on the size of the population. Through simulation, we first show that, when sampling times do probabilistically depend on effective population size, estimation methods may be systematically biased. To correct for this deficiency, we propose a new model that explicitly accounts for preferential sampling by modeling the sampling times as an inhomogeneous Poisson process dependent on effective population size. We demonstrate that in the presence of preferential sampling our new model not only reduces bias, but also improves estimation precision. Finally, we compare the performance of the currently used phylodynamic methods with our proposed model through clinically-relevant, seasonal human influenza examples. PMID:26938243

Confidence intervals for the population mean tailored to small sample sizes, with applications to survey sampling.

PubMed

Rosenblum, Michael A; Laan, Mark J van der

2009-01-07

The validity of standard confidence intervals constructed in survey sampling is based on the central limit theorem. For small sample sizes, the central limit theorem may give a poor approximation, resulting in confidence intervals that are misleading. We discuss this issue and propose methods for constructing confidence intervals for the population mean tailored to small sample sizes. We present a simple approach for constructing confidence intervals for the population mean based on tail bounds for the sample mean that are correct for all sample sizes. Bernstein's inequality provides one such tail bound. The resulting confidence intervals have guaranteed coverage probability under much weaker assumptions than are required for standard methods. A drawback of this approach, as we show, is that these confidence intervals are often quite wide. In response to this, we present a method for constructing much narrower confidence intervals, which are better suited for practical applications, and that are still more robust than confidence intervals based on standard methods, when dealing with small sample sizes. We show how to extend our approaches to much more general estimation problems than estimating the sample mean. We describe how these methods can be used to obtain more reliable confidence intervals in survey sampling. As a concrete example, we construct confidence intervals using our methods for the number of violent deaths between March 2003 and July 2006 in Iraq, based on data from the study "Mortality after the 2003 invasion of Iraq: A cross sectional cluster sample survey," by Burnham et al. (2006).

Improving the accuracy of sediment-associated constituent concentrations in whole storm water samples by wet-sieving

USGS Publications Warehouse

Selbig, W.R.; Bannerman, R.; Bowman, G.

2007-01-01

Sand-sized particles (>63 ??m) in whole storm water samples collected from urban runoff have the potential to produce data with substantial bias and/or poor precision both during sample splitting and laboratory analysis. New techniques were evaluated in an effort to overcome some of the limitations associated with sample splitting and analyzing whole storm water samples containing sand-sized particles. Wet-sieving separates sand-sized particles from a whole storm water sample. Once separated, both the sieved solids and the remaining aqueous (water suspension of particles less than 63 ??m) samples were analyzed for total recoverable metals using a modification of USEPA Method 200.7. The modified version digests the entire sample, rather than an aliquot, of the sample. Using a total recoverable acid digestion on the entire contents of the sieved solid and aqueous samples improved the accuracy of the derived sediment-associated constituent concentrations. Concentration values of sieved solid and aqueous samples can later be summed to determine an event mean concentration. ?? ASA, CSSA, SSSA.

Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling

PubMed Central

2006-01-01

Hidden populations, such as injection drug users and sex workers, are central to a number of public health problems. However, because of the nature of these groups, it is difficult to collect accurate information about them, and this difficulty complicates disease prevention efforts. A recently developed statistical approach called respondent-driven sampling improves our ability to study hidden populations by allowing researchers to make unbiased estimates of the prevalence of certain traits in these populations. Yet, not enough is known about the sample-to-sample variability of these prevalence estimates. In this paper, we present a bootstrap method for constructing confidence intervals around respondent-driven sampling estimates and demonstrate in simulations that it outperforms the naive method currently in use. We also use simulations and real data to estimate the design effects for respondent-driven sampling in a number of situations. We conclude with practical advice about the power calculations that are needed to determine the appropriate sample size for a study using respondent-driven sampling. In general, we recommend a sample size twice as large as would be needed under simple random sampling. PMID:16937083

Synthesis And Characterization Of Reduced Size Ferrite Reinforced Polymer Composites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Borah, Subasit; Bhattacharyya, Nidhi S.

2008-04-24

Small sized Co{sub 1-x}Ni{sub x}Fe{sub 2}O{sub 4} ferrite particles are synthesized by chemical route. The precursor materials are annealed at 400, 600 and 800 C. The crystallographic structure and phases of the samples are characterized by X-ray diffraction (XRD). The annealed ferrite samples crystallized into cubic spinel structure. Transmission Electron Microscopy (TEM) micrographs show that the average particle size of the samples are <20 nm. Particulate magneto-polymer composite materials are fabricated by reinforcing low density polyethylene (LDPE) matrix with the ferrite samples. The B-H loop study conducted at 10 kHz on the toroid shaped composite samples shows reduction in magneticmore » losses with decrease in size of the filler sample. Magnetic losses are detrimental for applications of ferrite at high powers. The reduction in magnetic loss shows a possible application of Co-Ni ferrites at high microwave power levels.« less

Degradation resistance of 3Y-TZP ceramics sintered using spark plasma sintering

NASA Astrophysics Data System (ADS)

Chintapalli, R.; Marro, F. G.; Valle, J. A.; Yan, H.; Reece, M. J.; Anglada, M.

2009-09-01

Commercially available tetragonal zirconia powder doped with 3 mol% of yttria has been sintered using spark plasma sintering (SPS) and has been investigated for its resistance to hydrothermal degradation. Samples were sintered at 1100, 1150, 1175 and 1600 °C at constant pressure of 100 MPa and soaking for 5 minutes, and the grain sizes obtained were 65, 90, 120 and 800 nm, respectively. Samples sintered conventionally with a grain size of 300 nm were also compared with samples sintered using SPS. Finely polished samples were subjected to artificial degradation at 131 °C for 60 hours in vapour in auto clave under a pressure of 2 bars. The XRD studies show no phase transformation in samples with low density and small grain size (<200 nm), but significant phase transformation is seen in dense samples with larger grain size (>300 nm). Results are discussed in terms of present theories of hydrothermal degradation.

Post-stratified estimation: with-in strata and total sample size recommendations

Treesearch

James A. Westfall; Paul L. Patterson; John W. Coulston

2011-01-01

Post-stratification is used to reduce the variance of estimates of the mean. Because the stratification is not fixed in advance, within-strata sample sizes can be quite small. The survey statistics literature provides some guidance on minimum within-strata sample sizes; however, the recommendations and justifications are inconsistent and apply broadly for many...

Using the Student's "t"-Test with Extremely Small Sample Sizes

ERIC Educational Resources Information Center

de Winter, J. C .F.

2013-01-01

Researchers occasionally have to work with an extremely small sample size, defined herein as "N" less than or equal to 5. Some methodologists have cautioned against using the "t"-test when the sample size is extremely small, whereas others have suggested that using the "t"-test is feasible in such a case. The present…

40 CFR 1042.310 - Engine selection for Category 1 and Category 2 engines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Category 2 engines. (a) Determine minimum sample sizes as follows: (1) For Category 1 engines, the minimum sample size is one engine or one percent of the projected U.S.-directed production volume for all your Category 1 engine families, whichever is greater. (2) For Category 2 engines, the minimum sample size is...

On Two-Stage Multiple Comparison Procedures When There Are Unequal Sample Sizes in the First Stage.

ERIC Educational Resources Information Center

Wilcox, Rand R.

1984-01-01

Two stage multiple-comparison procedures give an exact solution to problems of power and Type I errors, but require equal sample sizes in the first stage. This paper suggests a method of evaluating the experimentwise Type I error probability when the first stage has unequal sample sizes. (Author/BW)

Sample Size Requirements for Structural Equation Models: An Evaluation of Power, Bias, and Solution Propriety

ERIC Educational Resources Information Center

Wolf, Erika J.; Harrington, Kelly M.; Clark, Shaunna L.; Miller, Mark W.

2013-01-01

Determining sample size requirements for structural equation modeling (SEM) is a challenge often faced by investigators, peer reviewers, and grant writers. Recent years have seen a large increase in SEMs in the behavioral science literature, but consideration of sample size requirements for applied SEMs often relies on outdated rules-of-thumb.…

Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model

ERIC Educational Resources Information Center

Custer, Michael

2015-01-01

This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…

Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

PubMed

Petruzzellis, Francesco; Palandrani, Chiara; Savi, Tadeja; Alberti, Roberto; Nardini, Andrea; Bacaro, Giovanni

2017-12-01

The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits' variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITV BI ) and among populations (ITV POP ), relatively few studies have analyzed intraspecific variability within individuals (ITV WI ). Here, we provide an analysis of ITV WI of two foliar traits, namely specific leaf area (SLA) and osmotic potential (π), in a population of Quercus ilex L. We assessed the baseline ITV WI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITV WI , comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while π variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.

Observational studies of patients in the emergency department: a comparison of 4 sampling methods.

PubMed

Valley, Morgan A; Heard, Kennon J; Ginde, Adit A; Lezotte, Dennis C; Lowenstein, Steven R

2012-08-01

We evaluate the ability of 4 sampling methods to generate representative samples of the emergency department (ED) population. We analyzed the electronic records of 21,662 consecutive patient visits at an urban, academic ED. From this population, we simulated different models of study recruitment in the ED by using 2 sample sizes (n=200 and n=400) and 4 sampling methods: true random, random 4-hour time blocks by exact sample size, random 4-hour time blocks by a predetermined number of blocks, and convenience or "business hours." For each method and sample size, we obtained 1,000 samples from the population. Using χ(2) tests, we measured the number of statistically significant differences between the sample and the population for 8 variables (age, sex, race/ethnicity, language, triage acuity, arrival mode, disposition, and payer source). Then, for each variable, method, and sample size, we compared the proportion of the 1,000 samples that differed from the overall ED population to the expected proportion (5%). Only the true random samples represented the population with respect to sex, race/ethnicity, triage acuity, mode of arrival, language, and payer source in at least 95% of the samples. Patient samples obtained using random 4-hour time blocks and business hours sampling systematically differed from the overall ED patient population for several important demographic and clinical variables. However, the magnitude of these differences was not large. Common sampling strategies selected for ED-based studies may affect parameter estimates for several representative population variables. However, the potential for bias for these variables appears small. Copyright © 2012. Published by Mosby, Inc.

Variation in aluminum, iron, and particle concentrations in oxic ground-water samples collected by use of tangential-flow ultrafiltration with low-flow sampling

USGS Publications Warehouse

Szabo, Z.; Oden, J.H.; Gibs, J.; Rice, D.E.; Ding, Y.; ,

2001-01-01

Particulates that move with ground water and those that are artificially mobilized during well purging could be incorporated into water samples during collection and could cause trace-element concentrations to vary in unfiltered samples, and possibly in filtered samples (typically 0.45-um (micron) pore size) as well, depending on the particle-size fractions present. Therefore, measured concentrations may not be representative of those in the aquifer. Ground water may contain particles of various sizes and shapes that are broadly classified as colloids, which do not settle from water, and particulates, which do. In order to investigate variations in trace-element concentrations in ground-water samples as a function of particle concentrations and particle-size fractions, the U.S. Geological Survey, in cooperation with the U.S. Air Force, collected samples from five wells completed in the unconfined, oxic Kirkwood-Cohansey aquifer system of the New Jersey Coastal Plain. Samples were collected by purging with a portable pump at low flow (0.2-0.5 liters per minute and minimal drawdown, ideally less than 0.5 foot). Unfiltered samples were collected in the following sequence: (1) within the first few minutes of pumping, (2) after initial turbidity declined and about one to two casing volumes of water had been purged, and (3) after turbidity values had stabilized at less than 1 to 5 Nephelometric Turbidity Units. Filtered samples were split concurrently through (1) a 0.45-um pore size capsule filter, (2) a 0.45-um pore size capsule filter and a 0.0029-um pore size tangential-flow filter in sequence, and (3), in selected cases, a 0.45-um and a 0.05-um pore size capsule filter in sequence. Filtered samples were collected concurrently with the unfiltered sample that was collected when turbidity values stabilized. Quality-assurance samples consisted of sequential duplicates (about 25 percent) and equipment blanks. Concentrations of particles were determined by light scattering. Variations in concentrations aluminum and iron (1 -74 and 1-199 ug/L (micrograms per liter), respectively), common indicators of the presence of particulate-borne trace elements, were greatest in sample sets from individual wells with the greatest variations in turbidity and particle concentration. Differences in trace-element concentrations in sequentially collected unfiltered samples with variable turbidity were 5 to 10 times as great as those in concurrently collected samples that were passed through various filters. These results indicate that turbidity must be both reduced and stabilized even when low-flow sample-collection techniques are used in order to obtain water samples that do not contain considerable particulate artifacts. Currently (2001) available techniques need to be refined to ensure that the measured trace-element concentrations are representative of those that are mobile in the aquifer water.

Causality in Statistical Power: Isomorphic Properties of Measurement, Research Design, Effect Size, and Sample Size.

PubMed

Heidel, R Eric

2016-01-01

Statistical power is the ability to detect a significant effect, given that the effect actually exists in a population. Like most statistical concepts, statistical power tends to induce cognitive dissonance in hepatology researchers. However, planning for statistical power by an a priori sample size calculation is of paramount importance when designing a research study. There are five specific empirical components that make up an a priori sample size calculation: the scale of measurement of the outcome, the research design, the magnitude of the effect size, the variance of the effect size, and the sample size. A framework grounded in the phenomenon of isomorphism, or interdependencies amongst different constructs with similar forms, will be presented to understand the isomorphic effects of decisions made on each of the five aforementioned components of statistical power.

A multi-stage drop-the-losers design for multi-arm clinical trials.

PubMed

Wason, James; Stallard, Nigel; Bowden, Jack; Jennison, Christopher

2017-02-01

Multi-arm multi-stage trials can improve the efficiency of the drug development process when multiple new treatments are available for testing. A group-sequential approach can be used in order to design multi-arm multi-stage trials, using an extension to Dunnett's multiple-testing procedure. The actual sample size used in such a trial is a random variable that has high variability. This can cause problems when applying for funding as the cost will also be generally highly variable. This motivates a type of design that provides the efficiency advantages of a group-sequential multi-arm multi-stage design, but has a fixed sample size. One such design is the two-stage drop-the-losers design, in which a number of experimental treatments, and a control treatment, are assessed at a prescheduled interim analysis. The best-performing experimental treatment and the control treatment then continue to a second stage. In this paper, we discuss extending this design to have more than two stages, which is shown to considerably reduce the sample size required. We also compare the resulting sample size requirements to the sample size distribution of analogous group-sequential multi-arm multi-stage designs. The sample size required for a multi-stage drop-the-losers design is usually higher than, but close to, the median sample size of a group-sequential multi-arm multi-stage trial. In many practical scenarios, the disadvantage of a slight loss in average efficiency would be overcome by the huge advantage of a fixed sample size. We assess the impact of delay between recruitment and assessment as well as unknown variance on the drop-the-losers designs.

Sample size determination for logistic regression on a logit-normal distribution.

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

Sample size adjustments for varying cluster sizes in cluster randomized trials with binary outcomes analyzed with second-order PQL mixed logistic regression.

PubMed

Candel, Math J J M; Van Breukelen, Gerard J P

2010-06-30

Adjustments of sample size formulas are given for varying cluster sizes in cluster randomized trials with a binary outcome when testing the treatment effect with mixed effects logistic regression using second-order penalized quasi-likelihood estimation (PQL). Starting from first-order marginal quasi-likelihood (MQL) estimation of the treatment effect, the asymptotic relative efficiency of unequal versus equal cluster sizes is derived. A Monte Carlo simulation study shows this asymptotic relative efficiency to be rather accurate for realistic sample sizes, when employing second-order PQL. An approximate, simpler formula is presented to estimate the efficiency loss due to varying cluster sizes when planning a trial. In many cases sampling 14 per cent more clusters is sufficient to repair the efficiency loss due to varying cluster sizes. Since current closed-form formulas for sample size calculation are based on first-order MQL, planning a trial also requires a conversion factor to obtain the variance of the second-order PQL estimator. In a second Monte Carlo study, this conversion factor turned out to be 1.25 at most. (c) 2010 John Wiley & Sons, Ltd.

A modified approach to estimating sample size for simple logistic regression with one continuous covariate.

PubMed

Novikov, I; Fund, N; Freedman, L S

2010-01-15

Different methods for the calculation of sample size for simple logistic regression (LR) with one normally distributed continuous covariate give different results. Sometimes the difference can be large. Furthermore, some methods require the user to specify the prevalence of cases when the covariate equals its population mean, rather than the more natural population prevalence. We focus on two commonly used methods and show through simulations that the power for a given sample size may differ substantially from the nominal value for one method, especially when the covariate effect is large, while the other method performs poorly if the user provides the population prevalence instead of the required parameter. We propose a modification of the method of Hsieh et al. that requires specification of the population prevalence and that employs Schouten's sample size formula for a t-test with unequal variances and group sizes. This approach appears to increase the accuracy of the sample size estimates for LR with one continuous covariate.

Sample sizes and model comparison metrics for species distribution models

Treesearch

B.B. Hanberry; H.S. He; D.C. Dey

2012-01-01

Species distribution models use small samples to produce continuous distribution maps. The question of how small a sample can be to produce an accurate model generally has been answered based on comparisons to maximum sample sizes of 200 observations or fewer. In addition, model comparisons often are made with the kappa statistic, which has become controversial....

Using known map category marginal frequencies to improve estimates of thematic map accuracy

NASA Technical Reports Server (NTRS)

Card, D. H.

1982-01-01

By means of two simple sampling plans suggested in the accuracy-assessment literature, it is shown how one can use knowledge of map-category relative sizes to improve estimates of various probabilities. The fact that maximum likelihood estimates of cell probabilities for the simple random sampling and map category-stratified sampling were identical has permitted a unified treatment of the contingency-table analysis. A rigorous analysis of the effect of sampling independently within map categories is made possible by results for the stratified case. It is noted that such matters as optimal sample size selection for the achievement of a desired level of precision in various estimators are irrelevant, since the estimators derived are valid irrespective of how sample sizes are chosen.

Automated system measuring triple oxygen and nitrogen isotope ratios in nitrate using the bacterial method and N2 O decomposition by microwave discharge.

PubMed

Hattori, Shohei; Savarino, Joel; Kamezaki, Kazuki; Ishino, Sakiko; Dyckmans, Jens; Fujinawa, Tamaki; Caillon, Nicolas; Barbero, Albane; Mukotaka, Arata; Toyoda, Sakae; Well, Reinhard; Yoshida, Naohiro

2016-12-30

Triple oxygen and nitrogen isotope ratios in nitrate are powerful tools for assessing atmospheric nitrate formation pathways and their contribution to ecosystems. N 2 O decomposition using microwave-induced plasma (MIP) has been used only for measurements of oxygen isotopes to date, but it is also possible to measure nitrogen isotopes during the same analytical run. The main improvements to a previous system are (i) an automated distribution system of nitrate to the bacterial medium, (ii) N 2 O separation by gas chromatography before N 2 O decomposition using the MIP, (iii) use of a corundum tube for microwave discharge, and (iv) development of an automated system for isotopic measurements. Three nitrate standards with sample sizes of 60, 80, 100, and 120 nmol were measured to investigate the sample size dependence of the isotope measurements. The δ 17 O, δ 18 O, and Δ 17 O values increased with increasing sample size, although the δ 15 N value showed no significant size dependency. Different calibration slopes and intercepts were obtained with different sample amounts. The slopes and intercepts for the regression lines in different sample amounts were dependent on sample size, indicating that the extent of oxygen exchange is also dependent on sample size. The sample-size-dependent slopes and intercepts were fitted using natural log (ln) regression curves, and the slopes and intercepts can be estimated to apply to any sample size corrections. When using 100 nmol samples, the standard deviations of residuals from the regression lines for this system were 0.5‰, 0.3‰, and 0.1‰, respectively, for the δ 18 O, Δ 17 O, and δ 15 N values, results that are not inferior to those from other systems using gold tube or gold wire. An automated system was developed to measure triple oxygen and nitrogen isotopes in nitrate using N 2 O decomposition by MIP. This system enables us to measure both triple oxygen and nitrogen isotopes in nitrate with comparable precision and sample throughput (23 min per sample on average), and minimal manual treatment. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Capturing heterogeneity: The role of a study area's extent for estimating mean throughfall

NASA Astrophysics Data System (ADS)

Zimmermann, Alexander; Voss, Sebastian; Metzger, Johanna Clara; Hildebrandt, Anke; Zimmermann, Beate

2016-11-01

The selection of an appropriate spatial extent of a sampling plot is one among several important decisions involved in planning a throughfall sampling scheme. In fact, the choice of the extent may determine whether or not a study can adequately characterize the hydrological fluxes of the studied ecosystem. Previous attempts to optimize throughfall sampling schemes focused on the selection of an appropriate sample size, support, and sampling design, while comparatively little attention has been given to the role of the extent. In this contribution, we investigated the influence of the extent on the representativeness of mean throughfall estimates for three forest ecosystems of varying stand structure. Our study is based on virtual sampling of simulated throughfall fields. We derived these fields from throughfall data sampled in a simply structured forest (young tropical forest) and two heterogeneous forests (old tropical forest, unmanaged mixed European beech forest). We then sampled the simulated throughfall fields with three common extents and various sample sizes for a range of events and for accumulated data. Our findings suggest that the size of the study area should be carefully adapted to the complexity of the system under study and to the required temporal resolution of the throughfall data (i.e. event-based versus accumulated). Generally, event-based sampling in complex structured forests (conditions that favor comparatively long autocorrelations in throughfall) requires the largest extents. For event-based sampling, the choice of an appropriate extent can be as important as using an adequate sample size.

Scanning fiber angle-resolved low coherence interferometry

PubMed Central

Zhu, Yizheng; Terry, Neil G.; Wax, Adam

2010-01-01

We present a fiber-optic probe for Fourier-domain angle-resolved low coherence interferometry for the determination of depth-resolved scatterer size. The probe employs a scanning single-mode fiber to collect the angular scattering distribution of the sample, which is analyzed using the Mie theory to obtain the average size of the scatterers. Depth sectioning is achieved with low coherence Mach–Zehnder interferometry. In the sample arm of the interferometer, a fixed fiber illuminates the sample through an imaging lens and a collection fiber samples the backscattered angular distribution by scanning across the Fourier plane image of the sample. We characterize the optical performance of the probe and demonstrate the ability to execute depth-resolved sizing with subwavelength accuracy by using a double-layer phantom containing two sizes of polystyrene microspheres. PMID:19838271

Tests of Independence in Contingency Tables with Small Samples: A Comparison of Statistical Power.

ERIC Educational Resources Information Center

Parshall, Cynthia G.; Kromrey, Jeffrey D.

1996-01-01

Power and Type I error rates were estimated for contingency tables with small sample sizes for the following four types of tests: (1) Pearson's chi-square; (2) chi-square with Yates's continuity correction; (3) the likelihood ratio test; and (4) Fisher's Exact Test. Various marginal distributions, sample sizes, and effect sizes were examined. (SLD)

45 CFR Appendix C to Part 1356 - Calculating Sample Size for NYTD Follow-Up Populations

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 4 2013-10-01 2013-10-01 false Calculating Sample Size for NYTD Follow-Up Populations C Appendix C to Part 1356 Public Welfare Regulations Relating to Public Welfare (Continued) OFFICE... REQUIREMENTS APPLICABLE TO TITLE IV-E Pt. 1356, App. C Appendix C to Part 1356—Calculating Sample Size for NYTD...

Sample size considerations when groups are the appropriate unit of analyses

PubMed Central

Sadler, Georgia Robins; Ko, Celine Marie; Alisangco, Jennifer; Rosbrook, Bradley P.; Miller, Eric; Fullerton, Judith

2007-01-01

This paper discusses issues to be considered by nurse researchers when groups should be used as a unit of randomization. Advantages and disadvantages are presented, with statistical calculations needed to determine effective sample size. Examples of these concepts are presented using data from the Black Cosmetologists Promoting Health Program. Different hypothetical scenarios and their impact on sample size are presented. Given the complexity of calculating sample size when using groups as a unit of randomization, it’s advantageous for researchers to work closely with statisticians when designing and implementing studies that anticipate the use of groups as the unit of randomization. PMID:17693219

Minimizing the Maximum Expected Sample Size in Two-Stage Phase II Clinical Trials with Continuous Outcomes

PubMed Central

Wason, James M. S.; Mander, Adrian P.

2012-01-01

Two-stage designs are commonly used for Phase II trials. Optimal two-stage designs have the lowest expected sample size for a specific treatment effect, for example, the null value, but can perform poorly if the true treatment effect differs. Here we introduce a design for continuous treatment responses that minimizes the maximum expected sample size across all possible treatment effects. The proposed design performs well for a wider range of treatment effects and so is useful for Phase II trials. We compare the design to a previously used optimal design and show it has superior expected sample size properties. PMID:22651118

Recommended protocols for sampling macrofungi

Treesearch

Gregory M. Mueller; John Paul Schmit; Sabine M. Hubndorf Leif Ryvarden; Thomas E. O' Dell; D. Jean Lodge; Patrick R. Leacock; Milagro Mata; Loengrin Umania; Qiuxin (Florence) Wu; Daniel L. Czederpiltz

2004-01-01

This chapter discusses several issues regarding reommended protocols for sampling macrofungi: Opportunistic sampling of macrofungi, sampling conspicuous macrofungi using fixed-size, sampling small Ascomycetes using microplots, and sampling a fixed number of downed logs.

Damage Accumulation in Silica Glass Nanofibers.

PubMed

Bonfanti, Silvia; Ferrero, Ezequiel E; Sellerio, Alessandro L; Guerra, Roberto; Zapperi, Stefano

2018-06-06

The origin of the brittle-to-ductile transition, experimentally observed in amorphous silica nanofibers as the sample size is reduced, is still debated. Here we investigate the issue by extensive molecular dynamics simulations at low and room temperatures for a broad range of sample sizes, with open and periodic boundary conditions. Our results show that small sample-size enhanced ductility is primarily due to diffuse damage accumulation, that for larger samples leads to brittle catastrophic failure. Surface effects such as boundary fluidization contribute to ductility at room temperature by promoting necking, but are not the main driver of the transition. Our results suggest that the experimentally observed size-induced ductility of silica nanofibers is a manifestation of finite-size criticality, as expected in general for quasi-brittle disordered networks.

Threshold-dependent sample sizes for selenium assessment with stream fish tissue

USGS Publications Warehouse

Hitt, Nathaniel P.; Smith, David R.

2015-01-01

Natural resource managers are developing assessments of selenium (Se) contamination in freshwater ecosystems based on fish tissue concentrations. We evaluated the effects of sample size (i.e., number of fish per site) on the probability of correctly detecting mean whole-body Se values above a range of potential management thresholds. We modeled Se concentrations as gamma distributions with shape and scale parameters fitting an empirical mean-to-variance relationship in data from southwestern West Virginia, USA (63 collections, 382 individuals). We used parametric bootstrapping techniques to calculate statistical power as the probability of detecting true mean concentrations up to 3 mg Se/kg above management thresholds ranging from 4 to 8 mg Se/kg. Sample sizes required to achieve 80% power varied as a function of management thresholds and Type I error tolerance (α). Higher thresholds required more samples than lower thresholds because populations were more heterogeneous at higher mean Se levels. For instance, to assess a management threshold of 4 mg Se/kg, a sample of eight fish could detect an increase of approximately 1 mg Se/kg with 80% power (given α = 0.05), but this sample size would be unable to detect such an increase from a management threshold of 8 mg Se/kg with more than a coin-flip probability. Increasing α decreased sample size requirements to detect above-threshold mean Se concentrations with 80% power. For instance, at an α-level of 0.05, an 8-fish sample could detect an increase of approximately 2 units above a threshold of 8 mg Se/kg with 80% power, but when α was relaxed to 0.2, this sample size was more sensitive to increasing mean Se concentrations, allowing detection of an increase of approximately 1.2 units with equivalent power. Combining individuals into 2- and 4-fish composite samples for laboratory analysis did not decrease power because the reduced number of laboratory samples was compensated for by increased precision of composites for estimating mean conditions. However, low sample sizes (<5 fish) did not achieve 80% power to detect near-threshold values (i.e., <1 mg Se/kg) under any scenario we evaluated. This analysis can assist the sampling design and interpretation of Se assessments from fish tissue by accounting for natural variation in stream fish populations.

Towards Monitoring Biodiversity in Amazonian Forests: How Regular Samples Capture Meso-Scale Altitudinal Variation in 25 km2 Plots

PubMed Central

Norris, Darren; Fortin, Marie-Josée; Magnusson, William E.

2014-01-01

Background Ecological monitoring and sampling optima are context and location specific. Novel applications (e.g. biodiversity monitoring for environmental service payments) call for renewed efforts to establish reliable and robust monitoring in biodiversity rich areas. As there is little information on the distribution of biodiversity across the Amazon basin, we used altitude as a proxy for biological variables to test whether meso-scale variation can be adequately represented by different sample sizes in a standardized, regular-coverage sampling arrangement. Methodology/Principal Findings We used Shuttle-Radar-Topography-Mission digital elevation values to evaluate if the regular sampling arrangement in standard RAPELD (rapid assessments (“RAP”) over the long-term (LTER [“PELD” in Portuguese])) grids captured patters in meso-scale spatial variation. The adequacy of different sample sizes (n = 4 to 120) were examined within 32,325 km2/3,232,500 ha (1293×25 km2 sample areas) distributed across the legal Brazilian Amazon. Kolmogorov-Smirnov-tests, correlation and root-mean-square-error were used to measure sample representativeness, similarity and accuracy respectively. Trends and thresholds of these responses in relation to sample size and standard-deviation were modeled using Generalized-Additive-Models and conditional-inference-trees respectively. We found that a regular arrangement of 30 samples captured the distribution of altitude values within these areas. Sample size was more important than sample standard deviation for representativeness and similarity. In contrast, accuracy was more strongly influenced by sample standard deviation. Additionally, analysis of spatially interpolated data showed that spatial patterns in altitude were also recovered within areas using a regular arrangement of 30 samples. Conclusions/Significance Our findings show that the logistically feasible sample used in the RAPELD system successfully recovers meso-scale altitudinal patterns. This suggests that the sample size and regular arrangement may also be generally appropriate for quantifying spatial patterns in biodiversity at similar scales across at least 90% (≈5 million km2) of the Brazilian Amazon. PMID:25170894

Sample size considerations for clinical research studies in nuclear cardiology.

PubMed

Chiuzan, Cody; West, Erin A; Duong, Jimmy; Cheung, Ken Y K; Einstein, Andrew J

2015-12-01

Sample size calculation is an important element of research design that investigators need to consider in the planning stage of the study. Funding agencies and research review panels request a power analysis, for example, to determine the minimum number of subjects needed for an experiment to be informative. Calculating the right sample size is crucial to gaining accurate information and ensures that research resources are used efficiently and ethically. The simple question "How many subjects do I need?" does not always have a simple answer. Before calculating the sample size requirements, a researcher must address several aspects, such as purpose of the research (descriptive or comparative), type of samples (one or more groups), and data being collected (continuous or categorical). In this article, we describe some of the most frequent methods for calculating the sample size with examples from nuclear cardiology research, including for t tests, analysis of variance (ANOVA), non-parametric tests, correlation, Chi-squared tests, and survival analysis. For the ease of implementation, several examples are also illustrated via user-friendly free statistical software.

Sample size for post-marketing safety studies based on historical controls.

PubMed

Wu, Yu-te; Makuch, Robert W

2010-08-01

As part of a drug's entire life cycle, post-marketing studies are an important part in the identification of rare, serious adverse events. Recently, the US Food and Drug Administration (FDA) has begun to implement new post-marketing safety mandates as a consequence of increased emphasis on safety. The purpose of this research is to provide exact sample size formula for the proposed hybrid design, based on a two-group cohort study with incorporation of historical external data. Exact sample size formula based on the Poisson distribution is developed, because the detection of rare events is our outcome of interest. Performance of exact method is compared to its approximate large-sample theory counterpart. The proposed hybrid design requires a smaller sample size compared to the standard, two-group prospective study design. In addition, the exact method reduces the number of subjects required in the treatment group by up to 30% compared to the approximate method for the study scenarios examined. The proposed hybrid design satisfies the advantages and rationale of the two-group design with smaller sample sizes generally required. 2010 John Wiley & Sons, Ltd.

Synthesis and characterization of nanocrystalline mesoporous zirconia using supercritical drying.

PubMed

Tyagi, Beena; Sidhpuria, Kalpesh; Shaik, Basha; Jasra, Raksh Vir

2006-06-01

Synthesis of nano-crystalline zirconia aerogel was done by sol-gel technique and supercritical drying using n-propanol solvent at and above supercritical temperature (235-280 degrees C) and pressure (48-52 bar) of n-propanol. Zirconia xerogel samples have also been prepared by conventional thermal drying method to compare with the super critically dried samples. Crystalline phase, crystallite size, surface area, pore volume, and pore size distribution were determined for all the samples in detail to understand the effect of gel drying methods on these properties. Supercritical drying of zirconia gel was observed to give thermally stable, nano-crystalline, tetragonal zirconia aerogels having high specific surface area and porosity with narrow and uniform pore size distribution as compared to thermally dried zirconia. With supercritical drying, zirconia samples show the formation of only mesopores whereas in thermally dried samples, substantial amount of micropores are observed along with mesopores. The samples prepared using supercritical drying yield nano-crystalline zirconia with smaller crystallite size (4-6 nm) as compared to higher crystallite size (13-20 nm) observed with thermally dried zirconia.

Modeling the transport of engineered nanoparticles in saturated porous media - an experimental setup

NASA Astrophysics Data System (ADS)

Braun, A.; Neukum, C.; Azzam, R.

2011-12-01

The accelerating production and application of engineered nanoparticles is causing concerns regarding their release and fate in the environment. For assessing the risk that is posed to drinking water resources it is important to understand the transport and retention mechanisms of engineered nanoparticles in soil and groundwater. In this study an experimental setup for analyzing the mobility of silver and titanium dioxide nanoparticles in saturated porous media is presented. Batch and column experiments with glass beads and two different soils as matrices are carried out under varied conditions to study the impact of electrolyte concentration and pore water velocities. The analysis of nanoparticles implies several challenges, such as the detection and characterization and the preparation of a well dispersed sample with defined properties, as nanoparticles tend to form agglomerates when suspended in an aqueous medium. The analytical part of the experiments is mainly undertaken with Flow Field-Flow Fractionation (FlFFF). This chromatography like technique separates a particulate sample according to size. It is coupled to a UV/Vis and a light scattering detector for analyzing concentration and size distribution of the sample. The advantage of this technique is the ability to analyze also complex environmental samples, such as the effluent of column experiments including soil components, and the gentle sample treatment. For optimization of the sample preparation and for getting a first idea of the aggregation behavior in soil solutions, in sedimentation experiments the effect of ionic strength, sample concentration and addition of a surfactant on particle or aggregate size and temporal dispersion stability was investigated. In general the samples are more stable the lower the concentration of particles is. For TiO2 nanoparticles, the addition of a surfactant yielded the most stable samples with smallest aggregate sizes. Furthermore the suspension stability is increasing with electrolyte concentration. Depending on the dispersing medium the results show that TiO2 nanoparticles tend to form aggregates between 100-200 nm in diameter while the primary particle size is given as 21 nm by the manufacturer. Aggregate sizes are increasing with time. The particle size distribution of the silver nanoparticle samples is quite uniform in each medium. The fresh samples show aggregate sizes between 40 and 45 nm while the primary particle size is 15 nm according to the manufacturer. Aggregate size is only slightly increasing with time during the sedimentation experiments. These results are used as a reference when analyzing the effluent of column experiments.

Characteristics of randomised trials on diseases in the digestive system registered in ClinicalTrials.gov: a retrospective analysis.

PubMed

Wildt, Signe; Krag, Aleksander; Gluud, Liselotte

2011-01-01

Objectives To evaluate the adequacy of reporting of protocols for randomised trials on diseases of the digestive system registered in http://ClinicalTrials.gov and the consistency between primary outcomes, secondary outcomes and sample size specified in http://ClinicalTrials.gov and published trials. Methods Randomised phase III trials on adult patients with gastrointestinal diseases registered before January 2009 in http://ClinicalTrials.gov were eligible for inclusion. From http://ClinicalTrials.gov all data elements in the database required by the International Committee of Medical Journal Editors (ICMJE) member journals were extracted. The subsequent publications for registered trials were identified. For published trials, data concerning publication date, primary and secondary endpoint, sample size, and whether the journal adhered to ICMJE principles were extracted. Differences between primary and secondary outcomes, sample size and sample size calculations data in http://ClinicalTrials.gov and in the published paper were registered. Results 105 trials were evaluated. 66 trials (63%) were published. 30% of trials were registered incorrectly after their completion date. Several data elements of the required ICMJE data list were not filled in, with missing data in 22% and 11%, respectively, of cases concerning the primary outcome measure and sample size. In 26% of the published papers, data on sample size calculations were missing and discrepancies between sample size reporting in http://ClinicalTrials.gov and published trials existed. Conclusion The quality of registration of randomised controlled trials still needs improvement.

Parameter Estimation with Small Sample Size: A Higher-Order IRT Model Approach

ERIC Educational Resources Information Center

de la Torre, Jimmy; Hong, Yuan

2010-01-01

Sample size ranks as one of the most important factors that affect the item calibration task. However, due to practical concerns (e.g., item exposure) items are typically calibrated with much smaller samples than what is desired. To address the need for a more flexible framework that can be used in small sample item calibration, this article…

Sampling and data handling methods for inhalable particulate sampling. Final report nov 78-dec 80

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, W.B.; Cushing, K.M.; Johnson, J.W.

1982-05-01

The report reviews the objectives of a research program on sampling and measuring particles in the inhalable particulate (IP) size range in emissions from stationary sources, and describes methods and equipment required. A computer technique was developed to analyze data on particle-size distributions of samples taken with cascade impactors from industrial process streams. Research in sampling systems for IP matter included concepts for maintaining isokinetic sampling conditions, necessary for representative sampling of the larger particles, while flowrates in the particle-sizing device were constant. Laboratory studies were conducted to develop suitable IP sampling systems with overall cut diameters of 15 micrometersmore » and conforming to a specified collection efficiency curve. Collection efficiencies were similarly measured for a horizontal elutriator. Design parameters were calculated for horizontal elutriators to be used with impactors, the EPA SASS train, and the EPA FAS train. Two cyclone systems were designed and evaluated. Tests on an Andersen Size Selective Inlet, a 15-micrometer precollector for high-volume samplers, showed its performance to be with the proposed limits for IP samplers. A stack sampling system was designed in which the aerosol is diluted in flow patterns and with mixing times simulating those in stack plumes.« less

Maximum inflation of the type 1 error rate when sample size and allocation rate are adapted in a pre-planned interim look.

PubMed

Graf, Alexandra C; Bauer, Peter

2011-06-30

We calculate the maximum type 1 error rate of the pre-planned conventional fixed sample size test for comparing the means of independent normal distributions (with common known variance) which can be yielded when sample size and allocation rate to the treatment arms can be modified in an interim analysis. Thereby it is assumed that the experimenter fully exploits knowledge of the unblinded interim estimates of the treatment effects in order to maximize the conditional type 1 error rate. The 'worst-case' strategies require knowledge of the unknown common treatment effect under the null hypothesis. Although this is a rather hypothetical scenario it may be approached in practice when using a standard control treatment for which precise estimates are available from historical data. The maximum inflation of the type 1 error rate is substantially larger than derived by Proschan and Hunsberger (Biometrics 1995; 51:1315-1324) for design modifications applying balanced samples before and after the interim analysis. Corresponding upper limits for the maximum type 1 error rate are calculated for a number of situations arising from practical considerations (e.g. restricting the maximum sample size, not allowing sample size to decrease, allowing only increase in the sample size in the experimental treatment). The application is discussed for a motivating example. Copyright © 2011 John Wiley & Sons, Ltd.

The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations

NASA Astrophysics Data System (ADS)

Wake, David A.; Bundy, Kevin; Diamond-Stanic, Aleksandar M.; Yan, Renbin; Blanton, Michael R.; Bershady, Matthew A.; Sánchez-Gallego, José R.; Drory, Niv; Jones, Amy; Kauffmann, Guinevere; Law, David R.; Li, Cheng; MacDonald, Nicholas; Masters, Karen; Thomas, Daniel; Tinker, Jeremy; Weijmans, Anne-Marie; Brownstein, Joel R.

2017-09-01

We describe the sample design for the SDSS-IV MaNGA survey and present the final properties of the main samples along with important considerations for using these samples for science. Our target selection criteria were developed while simultaneously optimizing the size distribution of the MaNGA integral field units (IFUs), the IFU allocation strategy, and the target density to produce a survey defined in terms of maximizing signal-to-noise ratio, spatial resolution, and sample size. Our selection strategy makes use of redshift limits that only depend on I-band absolute magnitude (M I ), or, for a small subset of our sample, M I and color (NUV - I). Such a strategy ensures that all galaxies span the same range in angular size irrespective of luminosity and are therefore covered evenly by the adopted range of IFU sizes. We define three samples: the Primary and Secondary samples are selected to have a flat number density with respect to M I and are targeted to have spectroscopic coverage to 1.5 and 2.5 effective radii (R e ), respectively. The Color-Enhanced supplement increases the number of galaxies in the low-density regions of color-magnitude space by extending the redshift limits of the Primary sample in the appropriate color bins. The samples cover the stellar mass range 5× {10}8≤slant {M}* ≤slant 3× {10}11 {M}⊙ {h}-2 and are sampled at median physical resolutions of 1.37 and 2.5 kpc for the Primary and Secondary samples, respectively. We provide weights that will statistically correct for our luminosity and color-dependent selection function and IFU allocation strategy, thus correcting the observed sample to a volume-limited sample.

Metallographic Characterization of Wrought Depleted Uranium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forsyth, Robert Thomas; Hill, Mary Ann

Metallographic characterization was performed on wrought depleted uranium (DU) samples taken from the longitudinal and transverse orientations from specific locations on two specimens. Characterization of the samples included general microstructure, inclusion analysis, grain size analysis, and microhardness testing. Comparisons of the characterization results were made to determine any differences based on specimen, sample orientation, or sample location. In addition, the characterization results for the wrought DU samples were also compared with data obtained from the metallographic characterization of cast DU samples previously characterized. No differences were observed in microstructure, inclusion size, morphology, and distribution, or grain size in regard tomore » specimen, location, or orientation for the wrought depleted uranium samples. However, a small difference was observed in average hardness with regard to orientation at the same locations within the same specimen. The longitudinal samples were slightly harder than the transverse samples from the same location of the same specimen. This was true for both wrought DU specimens. Comparing the wrought DU sample data with the previously characterized cast DU sample data, distinct differences in microstructure, inclusion size, morphology and distribution, grain size, and microhardness were observed. As expected, the microstructure of the wrought DU samples consisted of small recrystallized grains which were uniform, randomly oriented, and equiaxed with minimal twinning observed in only a few grains. In contrast, the cast DU microstructure consisted of large irregularly shaped grains with extensive twinning observed in most grains. Inclusions in the wrought DU samples were elongated, broken and cracked and light and dark phases were observed in some inclusions. The mean inclusion area percentage for the wrought DU samples ranged from 0.08% to 0.34% and the average density from all wrought DU samples was 1.62E+04/cm 2. Inclusions in the cast DU samples were equiaxed and intact with light and dark phases observed in some inclusions. The mean inclusion area percentage for the cast DU samples ranged from 0.93% to 1.00% and the average density from all wrought DU samples was 2.83E+04/cm 2. The average mean grain area from all wrought DU samples was 141 μm 2 while the average mean grain area from all cast DU samples was 1.7 mm2. The average Knoop microhardness from all wrought DU samples was 215 HK and the average Knoop microhardness from all cast DU samples was 264 HK.« less

Laser Diffraction Techniques Replace Sieving for Lunar Soil Particle Size Distribution Data

NASA Technical Reports Server (NTRS)

Cooper, Bonnie L.; Gonzalez, C. P.; McKay, D. S.; Fruland, R. L.

2012-01-01

Sieving was used extensively until 1999 to determine the particle size distribution of lunar samples. This method is time-consuming, and requires more than a gram of material in order to obtain a result in which one may have confidence. This is demonstrated by the difference in geometric mean and median for samples measured by [1], in which a 14-gram sample produced a geometric mean of approx.52 micrometers, whereas two other samples of 1.5 grams resulted in gave means of approx.63 and approx.69 micrometers. Sample allocations for sieving are typically much smaller than a gram, and many of the sample allocations received by our lab are 0.5 to 0.25 grams in mass. Basu [2] has described how the finest fraction of the soil is easily lost in the sieving process, and this effect is compounded when sample sizes are small.

Allocating Sample Sizes to Reduce Budget for Fixed-Effect 2×2 Heterogeneous Analysis of Variance

ERIC Educational Resources Information Center

Luh, Wei-Ming; Guo, Jiin-Huarng

2016-01-01

This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a…

Approximate Sample Size Formulas for Testing Group Mean Differences when Variances Are Unequal in One-Way ANOVA

ERIC Educational Resources Information Center

Guo, Jiin-Huarng; Luh, Wei-Ming

2008-01-01

This study proposes an approach for determining appropriate sample size for Welch's F test when unequal variances are expected. Given a certain maximum deviation in population means and using the quantile of F and t distributions, there is no need to specify a noncentrality parameter and it is easy to estimate the approximate sample size needed…

Review of Sample Size for Structural Equation Models in Second Language Testing and Learning Research: A Monte Carlo Approach

ERIC Educational Resources Information Center

In'nami, Yo; Koizumi, Rie

2013-01-01

The importance of sample size, although widely discussed in the literature on structural equation modeling (SEM), has not been widely recognized among applied SEM researchers. To narrow this gap, we focus on second language testing and learning studies and examine the following: (a) Is the sample size sufficient in terms of precision and power of…

Determining Sample Size with a Given Range of Mean Effects in One-Way Heteroscedastic Analysis of Variance

ERIC Educational Resources Information Center

Shieh, Gwowen; Jan, Show-Li

2013-01-01

The authors examined 2 approaches for determining the required sample size of Welch's test for detecting equality of means when the greatest difference between any 2 group means is given. It is shown that the actual power obtained with the sample size of the suggested approach is consistently at least as great as the nominal power. However, the…

Sample size requirements for the design of reliability studies: precision consideration.

PubMed

Shieh, Gwowen

2014-09-01

In multilevel modeling, the intraclass correlation coefficient based on the one-way random-effects model is routinely employed to measure the reliability or degree of resemblance among group members. To facilitate the advocated practice of reporting confidence intervals in future reliability studies, this article presents exact sample size procedures for precise interval estimation of the intraclass correlation coefficient under various allocation and cost structures. Although the suggested approaches do not admit explicit sample size formulas and require special algorithms for carrying out iterative computations, they are more accurate than the closed-form formulas constructed from large-sample approximations with respect to the expected width and assurance probability criteria. This investigation notes the deficiency of existing methods and expands the sample size methodology for the design of reliability studies that have not previously been discussed in the literature.

Generating Random Samples of a Given Size Using Social Security Numbers.

ERIC Educational Resources Information Center

Erickson, Richard C.; Brauchle, Paul E.

1984-01-01

The purposes of this article are (1) to present a method by which social security numbers may be used to draw cluster samples of a predetermined size and (2) to describe procedures used to validate this method of drawing random samples. (JOW)

Role of Sample Processing Strategies at the European Union National Reference Laboratories (NRLs) Concerning the Analysis of Pesticide Residues.

PubMed

Hajeb, Parvaneh; Herrmann, Susan S; Poulsen, Mette E

2017-07-19

The guidance document SANTE 11945/2015 recommends that cereal samples be milled to a particle size preferably smaller than 1.0 mm and that extensive heating of the samples should be avoided. The aim of the present study was therefore to investigate the differences in milling procedures, obtained particle size distributions, and the resulting pesticide residue recovery when cereal samples were milled at the European Union National Reference Laboratories (NRLs) with their routine milling procedures. A total of 23 NRLs participated in the study. The oat and rye samples milled by each NRL were sent to the European Union Reference Laboratory on Cereals and Feedingstuff (EURL) for the determination of the particle size distribution and pesticide residue recovery. The results showed that the NRLs used several different brands and types of mills. Large variations in the particle size distributions and pesticide extraction efficiencies were observed even between samples milled by the same type of mill.

Estimating the size of hidden populations using respondent-driven sampling data: Case examples from Morocco

PubMed Central

Johnston, Lisa G; McLaughlin, Katherine R; Rhilani, Houssine El; Latifi, Amina; Toufik, Abdalla; Bennani, Aziza; Alami, Kamal; Elomari, Boutaina; Handcock, Mark S

2015-01-01

Background Respondent-driven sampling is used worldwide to estimate the population prevalence of characteristics such as HIV/AIDS and associated risk factors in hard-to-reach populations. Estimating the total size of these populations is of great interest to national and international organizations, however reliable measures of population size often do not exist. Methods Successive Sampling-Population Size Estimation (SS-PSE) along with network size imputation allows population size estimates to be made without relying on separate studies or additional data (as in network scale-up, multiplier and capture-recapture methods), which may be biased. Results Ten population size estimates were calculated for people who inject drugs, female sex workers, men who have sex with other men, and migrants from sub-Sahara Africa in six different cities in Morocco. SS-PSE estimates fell within or very close to the likely values provided by experts and the estimates from previous studies using other methods. Conclusions SS-PSE is an effective method for estimating the size of hard-to-reach populations that leverages important information within respondent-driven sampling studies. The addition of a network size imputation method helps to smooth network sizes allowing for more accurate results. However, caution should be used particularly when there is reason to believe that clustered subgroups may exist within the population of interest or when the sample size is small in relation to the population. PMID:26258908

Hierarchical modeling of cluster size in wildlife surveys

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

Experiments with central-limit properties of spatial samples from locally covariant random fields

USGS Publications Warehouse

Barringer, T.H.; Smith, T.E.

1992-01-01

When spatial samples are statistically dependent, the classical estimator of sample-mean standard deviation is well known to be inconsistent. For locally dependent samples, however, consistent estimators of sample-mean standard deviation can be constructed. The present paper investigates the sampling properties of one such estimator, designated as the tau estimator of sample-mean standard deviation. In particular, the asymptotic normality properties of standardized sample means based on tau estimators are studied in terms of computer experiments with simulated sample-mean distributions. The effects of both sample size and dependency levels among samples are examined for various value of tau (denoting the size of the spatial kernel for the estimator). The results suggest that even for small degrees of spatial dependency, the tau estimator exhibits significantly stronger normality properties than does the classical estimator of standardized sample means. ?? 1992.

Underwater microscope for measuring spatial and temporal changes in bed-sediment grain size

USGS Publications Warehouse

Rubin, David M.; Chezar, Henry; Harney, Jodi N.; Topping, David J.; Melis, Theodore S.; Sherwood, Christopher R.

2007-01-01

For more than a century, studies of sedimentology and sediment transport have measured bed-sediment grain size by collecting samples and transporting them back to the laboratory for grain-size analysis. This process is slow and expensive. Moreover, most sampling systems are not selective enough to sample only the surficial grains that interact with the flow; samples typically include sediment from at least a few centimeters beneath the bed surface. New hardware and software are available for in situ measurement of grain size. The new technology permits rapid measurement of surficial bed sediment. Here we describe several systems we have deployed by boat, by hand, and by tripod in rivers, oceans, and on beaches.

Underwater Microscope for Measuring Spatial and Temporal Changes in Bed-Sediment Grain Size

USGS Publications Warehouse

Rubin, David M.; Chezar, Henry; Harney, Jodi N.; Topping, David J.; Melis, Theodore S.; Sherwood, Christopher R.

2006-01-01

For more than a century, studies of sedimentology and sediment transport have measured bed-sediment grain size by collecting samples and transporting them back to the lab for grain-size analysis. This process is slow and expensive. Moreover, most sampling systems are not selective enough to sample only the surficial grains that interact with the flow; samples typically include sediment from at least a few centimeters beneath the bed surface. New hardware and software are available for in-situ measurement of grain size. The new technology permits rapid measurement of surficial bed sediment. Here we describe several systems we have deployed by boat, by hand, and by tripod in rivers, oceans, and on beaches.

A note on power and sample size calculations for the Kruskal-Wallis test for ordered categorical data.

PubMed

Fan, Chunpeng; Zhang, Donghui

2012-01-01

Although the Kruskal-Wallis test has been widely used to analyze ordered categorical data, power and sample size methods for this test have been investigated to a much lesser extent when the underlying multinomial distributions are unknown. This article generalizes the power and sample size procedures proposed by Fan et al. ( 2011 ) for continuous data to ordered categorical data, when estimates from a pilot study are used in the place of knowledge of the true underlying distribution. Simulations show that the proposed power and sample size formulas perform well. A myelin oligodendrocyte glycoprotein (MOG) induced experimental autoimmunce encephalomyelitis (EAE) mouse study is used to demonstrate the application of the methods.

10 CFR Appendix B to Subpart F of... - Sampling Plan For Enforcement Testing

Code of Federal Regulations, 2010 CFR

2010-01-01

... sample as follows: ER18MR98.010 where (x 1) is the measured energy efficiency, energy or water (in the...-tailed probability level and a sample size of n 1. Step 6(a). For an Energy Efficiency Standard, compare... an Energy Efficiency Standard, determine the second sample size (n 2) as follows: ER18MR98.015 where...

Variable percentage sampler

DOEpatents

Miller, Jr., William H.

1976-01-01

A remotely operable sampler is provided for obtaining variable percentage samples of nuclear fuel particles and the like for analyses. The sampler has a rotating cup for a sample collection chamber designed so that the effective size of the sample inlet opening to the cup varies with rotational speed. Samples of a desired size are withdrawn from a flowing stream of particles without a deterrent to the flow of remaining particles.

Analysis of $sup 239$Pu and $sup 241$Am in NAEG large-sized bovine samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Major, W.J.; Lee, K.D.; Wessman, R.A.

Methods are described for the analysis of environmental levels of $sup 239$Pu and $sup 241$Am in large-sized bovine samples. Special procedure modifications to overcome the complexities of sample preparation and analyses and special techniques employed to prepare and analyze different types of bovine samples, such as muscle, blood, liver, and bone are discussed. (CH)

Noninvasive genetics provides insights into the population size and genetic diversity of an Amur tiger population in China.

PubMed

Wang, Dan; Hu, Yibo; Ma, Tianxiao; Nie, Yonggang; Xie, Yan; Wei, Fuwen

2016-01-01

Understanding population size and genetic diversity is critical for effective conservation of endangered species. The Amur tiger (Panthera tigris altaica) is the largest felid and a flagship species for wildlife conservation. Due to habitat loss and human activities, available habitat and population size are continuously shrinking. However, little is known about the true population size and genetic diversity of wild tiger populations in China. In this study, we collected 55 fecal samples and 1 hair sample to investigate the population size and genetic diversity of wild Amur tigers in Hunchun National Nature Reserve, Jilin Province, China. From the samples, we determined that 23 fecal samples and 1 hair sample were from 7 Amur tigers: 2 males, 4 females and 1 individual of unknown sex. Interestingly, 2 fecal samples that were presumed to be from tigers were from Amur leopards, highlighting the significant advantages of noninvasive genetics over traditional methods in studying rare and elusive animals. Analyses from this sample suggested that the genetic diversity of wild Amur tigers is much lower than that of Bengal tigers, consistent with previous findings. Furthermore, the genetic diversity of this Hunchun population in China was lower than that of the adjoining subpopulation in southwest Primorye Russia, likely due to sampling bias. Considering the small population size and relatively low genetic diversity, it is urgent to protect this endangered local subpopulation in China. © 2015 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

An imbalance in cluster sizes does not lead to notable loss of power in cross-sectional, stepped-wedge cluster randomised trials with a continuous outcome.

PubMed

Kristunas, Caroline A; Smith, Karen L; Gray, Laura J

2017-03-07

The current methodology for sample size calculations for stepped-wedge cluster randomised trials (SW-CRTs) is based on the assumption of equal cluster sizes. However, as is often the case in cluster randomised trials (CRTs), the clusters in SW-CRTs are likely to vary in size, which in other designs of CRT leads to a reduction in power. The effect of an imbalance in cluster size on the power of SW-CRTs has not previously been reported, nor what an appropriate adjustment to the sample size calculation should be to allow for any imbalance. We aimed to assess the impact of an imbalance in cluster size on the power of a cross-sectional SW-CRT and recommend a method for calculating the sample size of a SW-CRT when there is an imbalance in cluster size. The effect of varying degrees of imbalance in cluster size on the power of SW-CRTs was investigated using simulations. The sample size was calculated using both the standard method and two proposed adjusted design effects (DEs), based on those suggested for CRTs with unequal cluster sizes. The data were analysed using generalised estimating equations with an exchangeable correlation matrix and robust standard errors. An imbalance in cluster size was not found to have a notable effect on the power of SW-CRTs. The two proposed adjusted DEs resulted in trials that were generally considerably over-powered. We recommend that the standard method of sample size calculation for SW-CRTs be used, provided that the assumptions of the method hold. However, it would be beneficial to investigate, through simulation, what effect the maximum likely amount of inequality in cluster sizes would be on the power of the trial and whether any inflation of the sample size would be required.

Composition and Morphology of Major Particle Types from Airborne Measurements during ICE-T and PRADACS Field Studies

NASA Astrophysics Data System (ADS)

Venero, I. M.; Mayol-Bracero, O. L.; Anderson, J. R.

2012-12-01

As part of the Puerto Rican African Dust and Cloud Study (PRADACS) and the Ice in Clouds Experiment - Tropical (ICE-T), we sampled giant airborne particles to study their elemental composition, morphology, and size distributions. Samples were collected in July 2011 during field measurements performed by NCAR's C-130 aircraft based on St Croix, U.S Virgin Island. The results presented here correspond to the measurements done during research flight #8 (RF8). Aerosol particles with Dp > 1 um were sampled with the Giant Nuclei Impactor and particles with Dp < 1 um were collected with the Wyoming Inlet. Collected particles were later analyzed using an automated scanning electron microscope (SEM) and manual observation by field emission SEM. We identified the chemical composition and morphology of major particle types in filter samples collected at different altitudes (e.g., 300 ft, 1000 ft, and 4500ft). Results from the flight upwind of Puerto Rico show that particles in the giant nuclei size range are dominated by sea salt. Samples collected at altitudes 300 ft and 1000 ft showed the highest number of sea salt particles and the samples collected at higher altitudes (> 4000 ft) showed the highest concentrations of clay material. HYSPLIT back trajectories for all samples showed that the low altitude samples initiated in the free troposphere in the Atlantic Ocean, which may account for the high sea salt content and that the source of the high altitude samples was closer to the Saharan - Sahel desert region and, therefore, these samples possibly had the influence of African dust. Size distribution results for quartz and unreacted sea-salt aerosols collected on the Giant Nuclei Impactor showed that sample RF08 - 12:05 UTM (300 ft) had the largest size value (mean = 2.936 μm) than all the other samples. Additional information was also obtained from the Wyoming Inlet present at the C - 130 aircraft which showed that size distribution results for all particles were smaller in size. The different mineral components of the dust have different size distributions so that a fractionation process could occur during transport. Also, the presence of supermicron sea salt at altitude is important for cloud processes.

(I Can't Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research.

PubMed

van Rijnsoever, Frank J

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: "random chance," which is based on probability sampling, "minimal information," which yields at least one new code per sampling step, and "maximum information," which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario.

Influence of pore size distributions on decomposition of maize leaf residue: evidence from X-ray computed micro-tomography

NASA Astrophysics Data System (ADS)

Negassa, Wakene; Guber, Andrey; Kravchenko, Alexandra; Rivers, Mark

2014-05-01

Soil's potential to sequester carbon (C) depends not only on quality and quantity of organic inputs to soil but also on the residence time of the applied organic inputs within the soil. Soil pore structure is one of the main factors that influence residence time of soil organic matter by controlling gas exchange, soil moisture and microbial activities, thereby soil C sequestration capacity. Previous attempts to investigate the fate of organic inputs added to soil did not allow examining their decomposition in situ; the drawback that can now be remediated by application of X-ray computed micro-tomography (µ-CT). The non-destructive and non-invasive nature of µ-CT gives an opportunity to investigate the effect of soil pore size distributions on decomposition of plant residues at a new quantitative level. The objective of this study is to examine the influence of pore size distributions on the decomposition of plant residue added to soil. Samples with contrasting pore size distributions were created using aggregate fractions of five different sizes (<0.05, 0.05-0.1, 0.10-05, 0.5-1.0 and 1.0-2.0 mm). Weighted average pore diameters ranged from 10 µm (<0.05 mm fraction) to 104 µm (1-2 mm fraction), while maximum pore diameter were in a range from 29 µm (<0.05 mm fraction) to 568 µm (1-2 mm fraction) in the created soil samples. Dried pieces of maize leaves 2.5 mg in size (equivalent to 1.71 mg C g-1 soil) were added to half of the studied samples. Samples with and without maize leaves were incubated for 120 days. CO2 emission from the samples was measured at regular time intervals. In order to ensure that the observed differences are due to differences in pore structure and not due to differences in inherent properties of the studied aggregate fractions, we repeated the whole experiment using soil from the same aggregate size fractions but ground to <0.05 mm size. Five to six replicated samples were used for intact and ground samples of all sizes with and without leaves. Two replications of the intact aggregate fractions of all sizes with leaves were subjected to µ-CT scanning before and after incubation, whereas all the remaining replications of both intact and ground aggregate fractions of <0.05, 0.05-0.1, and 1.0-2.0 mm sizes with leaves were scanned with µ-CT after the incubation. The µ-CT image showed that approximately 80% of the leaves in the intact samples of large aggregate fractions (0.5-1.0 and 1.0-2.0 mm) was decomposed during the incubation, while only 50-60% of the leaves were decomposed in the intact samples of smaller sized fractions. Even lower percent of leaves (40-50%) was decomposed in the ground samples, with very similar leaf decomposition observed in all ground samples regardless of the aggregate fraction size. Consistent with µ-CT results, the proportion of decomposed leaf estimated with the conventional mass loss method was 48% and 60% for the <0.05 mm and 1.0-2.0 mm soil size fractions of intact aggregates, and 40-50% in ground samples, respectively. The results of the incubation experiment demonstrated that, while greater C mineralization was observed in samples of all size fractions amended with leaf, the effect of leaf presence was most pronounced in the smaller aggregate fractions (0.05-0.1 mm and 0.05 mm) of intact aggregates. The results of the present study unequivocally demonstrate that differences in pore size distributions have a major effect on the decomposition of plant residues added to soil. Moreover, in presence of plant residues, differences in pore size distributions appear to also influence the rates of decomposition of the intrinsic soil organic material.

Size and modal analyses of fines and ultrafines from some Apollo 17 samples

NASA Technical Reports Server (NTRS)

Greene, G. M.; King, D. T., Jr.; Banholzer, G. S., Jr.; King, E. A.

1975-01-01

Scanning electron and optical microscopy techniques have been used to determine the grain-size frequency distributions and morphology-based modal analyses of fine and ultrafine fractions of some Apollo 17 regolith samples. There are significant and large differences between the grain-size frequency distributions of the less than 10-micron size fraction of Apollo 17 samples, but there are no clear relations to the local geologic setting from which individual samples have been collected. This may be due to effective lateral mixing of regolith particles in this size range by micrometeoroid impacts. None of the properties of the frequency distributions support the idea of selective transport of any fine grain-size fraction, as has been proposed by other workers. All of the particle types found in the coarser size fractions also occur in the less than 10-micron particles. In the size range from 105 to 10 microns there is a strong tendency for the percentage of regularly shaped glass to increase as the graphic mean grain size of the less than 1-mm size fraction decreases, both probably being controlled by exposure age.

A standardized sampling protocol for channel catfish in prairie streams

USGS Publications Warehouse

Vokoun, Jason C.; Rabeni, Charles F.

2001-01-01

Three alternative gears—an AC electrofishing raft, bankpoles, and a 15-hoop-net set—were used in a standardized manner to sample channel catfish Ictalurus punctatus in three prairie streams of varying size in three seasons. We compared these gears as to time required per sample, size selectivity, mean catch per unit effort (CPUE) among months, mean CPUE within months, effect of fluctuating stream stage, and sensitivity to population size. According to these comparisons, the 15-hoop-net set used during stable water levels in October had the most desirable characteristics. Using our catch data, we estimated the precision of CPUE and size structure by varying sample sizes for the 15-hoop-net set. We recommend that 11–15 repetitions of the 15-hoop-net set be used for most management activities. This standardized basic unit of effort will increase the precision of estimates and allow better comparisons among samples as well as increased confidence in management decisions.

Sample size for estimating mean and coefficient of variation in species of crotalarias.

PubMed

Toebe, Marcos; Machado, Letícia N; Tartaglia, Francieli L; Carvalho, Juliana O DE; Bandeira, Cirineu T; Cargnelutti Filho, Alberto

2018-04-16

The objective of this study was to determine the sample size necessary to estimate the mean and coefficient of variation in four species of crotalarias (C. juncea, C. spectabilis, C. breviflora and C. ochroleuca). An experiment was carried out for each species during the season 2014/15. At harvest, 1,000 pods of each species were randomly collected. In each pod were measured: mass of pod with and without seeds, length, width and height of pods, number and mass of seeds per pod, and mass of hundred seeds. Measures of central tendency, variability and distribution were calculated, and the normality was verified. The sample size necessary to estimate the mean and coefficient of variation with amplitudes of the confidence interval of 95% (ACI95%) of 2%, 4%, ..., 20% was determined by resampling with replacement. The sample size varies among species and characters, being necessary a larger sample size to estimate the mean in relation of the necessary for the coefficient of variation.

A Bayesian approach for incorporating economic factors in sample size design for clinical trials of individual drugs and portfolios of drugs.

PubMed

Patel, Nitin R; Ankolekar, Suresh

2007-11-30

Classical approaches to clinical trial design ignore economic factors that determine economic viability of a new drug. We address the choice of sample size in Phase III trials as a decision theory problem using a hybrid approach that takes a Bayesian view from the perspective of a drug company and a classical Neyman-Pearson view from the perspective of regulatory authorities. We incorporate relevant economic factors in the analysis to determine the optimal sample size to maximize the expected profit for the company. We extend the analysis to account for risk by using a 'satisficing' objective function that maximizes the chance of meeting a management-specified target level of profit. We extend the models for single drugs to a portfolio of clinical trials and optimize the sample sizes to maximize the expected profit subject to budget constraints. Further, we address the portfolio risk and optimize the sample sizes to maximize the probability of achieving a given target of expected profit.

Ranked set sampling: cost and optimal set size.

PubMed

Nahhas, Ramzi W; Wolfe, Douglas A; Chen, Haiying

2002-12-01

McIntyre (1952, Australian Journal of Agricultural Research 3, 385-390) introduced ranked set sampling (RSS) as a method for improving estimation of a population mean in settings where sampling and ranking of units from the population are inexpensive when compared with actual measurement of the units. Two of the major factors in the usefulness of RSS are the set size and the relative costs of the various operations of sampling, ranking, and measurement. In this article, we consider ranking error models and cost models that enable us to assess the effect of different cost structures on the optimal set size for RSS. For reasonable cost structures, we find that the optimal RSS set sizes are generally larger than had been anticipated previously. These results will provide a useful tool for determining whether RSS is likely to lead to an improvement over simple random sampling in a given setting and, if so, what RSS set size is best to use in this case.

A general approach for sample size calculation for the three-arm 'gold standard' non-inferiority design.

PubMed

Stucke, Kathrin; Kieser, Meinhard

2012-12-10

In the three-arm 'gold standard' non-inferiority design, an experimental treatment, an active reference, and a placebo are compared. This design is becoming increasingly popular, and it is, whenever feasible, recommended for use by regulatory guidelines. We provide a general method to calculate the required sample size for clinical trials performed in this design. As special cases, the situations of continuous, binary, and Poisson distributed outcomes are explored. Taking into account the correlation structure of the involved test statistics, the proposed approach leads to considerable savings in sample size as compared with application of ad hoc methods for all three scale levels. Furthermore, optimal sample size allocation ratios are determined that result in markedly smaller total sample sizes as compared with equal assignment. As optimal allocation makes the active treatment groups larger than the placebo group, implementation of the proposed approach is also desirable from an ethical viewpoint. Copyright © 2012 John Wiley & Sons, Ltd.

Porosity of the Marcellus Shale: A contrast matching small-angle neutron scattering study

USGS Publications Warehouse

Bahadur, Jitendra; Ruppert, Leslie F.; Pipich, Vitaliy; Sakurovs, Richard; Melnichenko, Yuri B.

2018-01-01

Neutron scattering techniques were used to determine the effect of mineral matter on the accessibility of water and toluene to pores in the Devonian Marcellus Shale. Three Marcellus Shale samples, representing quartz-rich, clay-rich, and carbonate-rich facies, were examined using contrast matching small-angle neutron scattering (CM-SANS) at ambient pressure and temperature. Contrast matching compositions of H2O, D2O and toluene, deuterated toluene were used to probe open and closed pores of these three shale samples. Results show that although the mean pore radius was approximately the same for all three samples, the fractal dimension of the quartz-rich sample was higher than for the clay-rich and carbonate-rich samples, indicating different pore size distributions among the samples. The number density of pores was highest in the clay-rich sample and lowest in the quartz-rich sample. Contrast matching with water and toluene mixtures shows that the accessibility of pores to water and toluene also varied among the samples. In general, water accessed approximately 70–80% of the larger pores (>80 nm radius) in all three samples. At smaller pore sizes (~5–80 nm radius), the fraction of accessible pores decreases. The lowest accessibility to both fluids is at pore throat size of ~25 nm radii with the quartz-rich sample exhibiting lower accessibility than the clay- and carbonate-rich samples. The mechanism for this behaviour is unclear, but because the mineralogy of the three samples varies, it is likely that the inaccessible pores in this size range are associated with organics and not a specific mineral within the samples. At even smaller pore sizes (~<2.5 nm radius), in all samples, the fraction of accessible pores to water increases again to approximately 70–80%. Accessibility to toluene generally follows that of water; however, in the smallest pores (~<2.5 nm radius), accessibility to toluene decreases, especially in the clay-rich sample which contains about 30% more closed pores than the quartz- and carbonate-rich samples. Results from this study show that mineralogy of producing intervals within a shale reservoir can affect accessibility of pores to water and toluene and these mineralogic differences may affect hydrocarbon storage and production and hydraulic fracturing characteristics

Extraction of citral oil from lemongrass (Cymbopogon Citratus) by steam-water distillation technique

NASA Astrophysics Data System (ADS)

Alam, P. N.; Husin, H.; Asnawi, T. M.; Adisalamun

2018-04-01

In Indonesia, production of citral oil from lemon grass (Cymbopogon Cytratus) is done by a traditional technique whereby a low yield results. To improve the yield, an appropriate extraction technology is required. In this research, a steam-water distillation technique was applied to extract the essential oil from the lemongrass. The effects of sample particle size and bed volume on yield and quality of citral oil produced were investigated. The drying and refining time of 2 hours were used as fixed variables. This research results that minimum citral oil yield of 0.53% was obtained on sample particle size of 3 cm and bed volume of 80%, whereas the maximum yield of 1.95% on sample particle size of 15 cm and bed volume of 40%. The lowest specific gravity of 0.80 and the highest specific gravity of 0.905 were obtained on sample particle size of 8 cm with bed volume of 80% and particle size of 12 cm with bed volume of 70%, respectively. The lowest refractive index of 1.480 and the highest refractive index of 1.495 were obtained on sample particle size of 8 cm with bed volume of 70% and sample particle size of 15 cm with bed volume of 40%, respectively. The solubility of the produced citral oil in alcohol was 70% in ratio of 1:1, and the citral oil concentration obtained was around 79%.

An analysis of Apollo lunar soil samples 12070,889, 12030,187, and 12070,891: Basaltic diversity at the Apollo 12 landing site and implications for classification of small-sized lunar samples

NASA Astrophysics Data System (ADS)

Alexander, Louise; Snape, Joshua F.; Joy, Katherine H.; Downes, Hilary; Crawford, Ian A.

2016-09-01

Lunar mare basalts provide insights into the compositional diversity of the Moon's interior. Basalt fragments from the lunar regolith can potentially sample lava flows from regions of the Moon not previously visited, thus, increasing our understanding of lunar geological evolution. As part of a study of basaltic diversity at the Apollo 12 landing site, detailed petrological and geochemical data are provided here for 13 basaltic chips. In addition to bulk chemistry, we have analyzed the major, minor, and trace element chemistry of mineral phases which highlight differences between basalt groups. Where samples contain olivine, the equilibrium parent melt magnesium number (Mg#; atomic Mg/[Mg + Fe]) can be calculated to estimate parent melt composition. Ilmenite and plagioclase chemistry can also determine differences between basalt groups. We conclude that samples of approximately 1-2 mm in size can be categorized provided that appropriate mineral phases (olivine, plagioclase, and ilmenite) are present. Where samples are fine-grained (grain size <0.3 mm), a "paired samples t-test" can provide a statistical comparison between a particular sample and known lunar basalts. Of the fragments analyzed here, three are found to belong to each of the previously identified olivine and ilmenite basalt suites, four to the pigeonite basalt suite, one is an olivine cumulate, and two could not be categorized because of their coarse grain sizes and lack of appropriate mineral phases. Our approach introduces methods that can be used to investigate small sample sizes (i.e., fines) from future sample return missions to investigate lava flow diversity and petrological significance.

Performance and separation occurrence of binary probit regression estimator using maximum likelihood method and Firths approach under different sample size

NASA Astrophysics Data System (ADS)

Lusiana, Evellin Dewi

2017-12-01

The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.

Sample Size Estimation for Alzheimer's Disease Trials from Japanese ADNI Serial Magnetic Resonance Imaging.

PubMed

Fujishima, Motonobu; Kawaguchi, Atsushi; Maikusa, Norihide; Kuwano, Ryozo; Iwatsubo, Takeshi; Matsuda, Hiroshi

2017-01-01

Little is known about the sample sizes required for clinical trials of Alzheimer's disease (AD)-modifying treatments using atrophy measures from serial brain magnetic resonance imaging (MRI) in the Japanese population. The primary objective of the present study was to estimate how large a sample size would be needed for future clinical trials for AD-modifying treatments in Japan using atrophy measures of the brain as a surrogate biomarker. Sample sizes were estimated from the rates of change of the whole brain and hippocampus by the k-means normalized boundary shift integral (KN-BSI) and cognitive measures using the data of 537 Japanese Alzheimer's Neuroimaging Initiative (J-ADNI) participants with a linear mixed-effects model. We also examined the potential use of ApoE status as a trial enrichment strategy. The hippocampal atrophy rate required smaller sample sizes than cognitive measures of AD and mild cognitive impairment (MCI). Inclusion of ApoE status reduced sample sizes for AD and MCI patients in the atrophy measures. These results show the potential use of longitudinal hippocampal atrophy measurement using automated image analysis as a progression biomarker and ApoE status as a trial enrichment strategy in a clinical trial of AD-modifying treatment in Japanese people.

Particle size analysis of sediments, soils and related particulate materials for forensic purposes using laser granulometry.

PubMed

Pye, Kenneth; Blott, Simon J

2004-08-11

Particle size is a fundamental property of any sediment, soil or dust deposit which can provide important clues to nature and provenance. For forensic work, the particle size distribution of sometimes very small samples requires precise determination using a rapid and reliable method with a high resolution. The Coulter trade mark LS230 laser granulometer offers rapid and accurate sizing of particles in the range 0.04-2000 microm for a variety of sample types, including soils, unconsolidated sediments, dusts, powders and other particulate materials. Reliable results are possible for sample weights of just 50 mg. Discrimination between samples is performed on the basis of the shape of the particle size curves and statistical measures of the size distributions. In routine forensic work laser granulometry data can rarely be used in isolation and should be considered in combination with results from other techniques to reach an overall conclusion.

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review

PubMed Central

Morris, Tom; Gray, Laura

2017-01-01

Objectives To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Setting Any, not limited to healthcare settings. Participants Any taking part in an SW-CRT published up to March 2016. Primary and secondary outcome measures The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Results Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22–0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Conclusions Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. PMID:29146637

An opportunity cost approach to sample size calculation in cost-effectiveness analysis.

PubMed

Gafni, A; Walter, S D; Birch, S; Sendi, P

2008-01-01

The inclusion of economic evaluations as part of clinical trials has led to concerns about the adequacy of trial sample size to support such analysis. The analytical tool of cost-effectiveness analysis is the incremental cost-effectiveness ratio (ICER), which is compared with a threshold value (lambda) as a method to determine the efficiency of a health-care intervention. Accordingly, many of the methods suggested to calculating the sample size requirements for the economic component of clinical trials are based on the properties of the ICER. However, use of the ICER and a threshold value as a basis for determining efficiency has been shown to be inconsistent with the economic concept of opportunity cost. As a result, the validity of the ICER-based approaches to sample size calculations can be challenged. Alternative methods for determining improvements in efficiency have been presented in the literature that does not depend upon ICER values. In this paper, we develop an opportunity cost approach to calculating sample size for economic evaluations alongside clinical trials, and illustrate the approach using a numerical example. We compare the sample size requirement of the opportunity cost method with the ICER threshold method. In general, either method may yield the larger required sample size. However, the opportunity cost approach, although simple to use, has additional data requirements. We believe that the additional data requirements represent a small price to pay for being able to perform an analysis consistent with both concept of opportunity cost and the problem faced by decision makers. Copyright (c) 2007 John Wiley & Sons, Ltd.

Blinded and unblinded internal pilot study designs for clinical trials with count data.

PubMed

Schneider, Simon; Schmidli, Heinz; Friede, Tim

2013-07-01

Internal pilot studies are a popular design feature to address uncertainties in the sample size calculations caused by vague information on nuisance parameters. Despite their popularity, only very recently blinded sample size reestimation procedures for trials with count data were proposed and their properties systematically investigated. Although blinded procedures are favored by regulatory authorities, practical application is somewhat limited by fears that blinded procedures are prone to bias if the treatment effect was misspecified in the planning. Here, we compare unblinded and blinded procedures with respect to bias, error rates, and sample size distribution. We find that both procedures maintain the desired power and that the unblinded procedure is slightly liberal whereas the actual significance level of the blinded procedure is close to the nominal level. Furthermore, we show that in situations where uncertainty about the assumed treatment effect exists, the blinded estimator of the control event rate is biased in contrast to the unblinded estimator, which results in differences in mean sample sizes in favor of the unblinded procedure. However, these differences are rather small compared to the deviations of the mean sample sizes from the sample size required to detect the true, but unknown effect. We demonstrate that the variation of the sample size resulting from the blinded procedure is in many practically relevant situations considerably smaller than the one of the unblinded procedures. The methods are extended to overdispersed counts using a quasi-likelihood approach and are illustrated by trials in relapsing multiple sclerosis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sample size requirements for indirect association studies of gene-environment interactions (G x E).

PubMed

Hein, Rebecca; Beckmann, Lars; Chang-Claude, Jenny

2008-04-01

Association studies accounting for gene-environment interactions (G x E) may be useful for detecting genetic effects. Although current technology enables very dense marker spacing in genetic association studies, the true disease variants may not be genotyped. Thus, causal genes are searched for by indirect association using genetic markers in linkage disequilibrium (LD) with the true disease variants. Sample sizes needed to detect G x E effects in indirect case-control association studies depend on the true genetic main effects, disease allele frequencies, whether marker and disease allele frequencies match, LD between loci, main effects and prevalence of environmental exposures, and the magnitude of interactions. We explored variables influencing sample sizes needed to detect G x E, compared these sample sizes with those required to detect genetic marginal effects, and provide an algorithm for power and sample size estimations. Required sample sizes may be heavily inflated if LD between marker and disease loci decreases. More than 10,000 case-control pairs may be required to detect G x E. However, given weak true genetic main effects, moderate prevalence of environmental exposures, as well as strong interactions, G x E effects may be detected with smaller sample sizes than those needed for the detection of genetic marginal effects. Moreover, in this scenario, rare disease variants may only be detectable when G x E is included in the analyses. Thus, the analysis of G x E appears to be an attractive option for the detection of weak genetic main effects of rare variants that may not be detectable in the analysis of genetic marginal effects only.

Monitoring landscape metrics by point sampling: accuracy in estimating Shannon's diversity and edge density.

PubMed

Ramezani, Habib; Holm, Sören; Allard, Anna; Ståhl, Göran

2010-05-01

Environmental monitoring of landscapes is of increasing interest. To quantify landscape patterns, a number of metrics are used, of which Shannon's diversity, edge length, and density are studied here. As an alternative to complete mapping, point sampling was applied to estimate the metrics for already mapped landscapes selected from the National Inventory of Landscapes in Sweden (NILS). Monte-Carlo simulation was applied to study the performance of different designs. Random and systematic samplings were applied for four sample sizes and five buffer widths. The latter feature was relevant for edge length, since length was estimated through the number of points falling in buffer areas around edges. In addition, two landscape complexities were tested by applying two classification schemes with seven or 20 land cover classes to the NILS data. As expected, the root mean square error (RMSE) of the estimators decreased with increasing sample size. The estimators of both metrics were slightly biased, but the bias of Shannon's diversity estimator was shown to decrease when sample size increased. In the edge length case, an increasing buffer width resulted in larger bias due to the increased impact of boundary conditions; this effect was shown to be independent of sample size. However, we also developed adjusted estimators that eliminate the bias of the edge length estimator. The rates of decrease of RMSE with increasing sample size and buffer width were quantified by a regression model. Finally, indicative cost-accuracy relationships were derived showing that point sampling could be a competitive alternative to complete wall-to-wall mapping.

Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.

PubMed

Youssef, Noha H; Elshahed, Mostafa S

2008-09-01

Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.

Influence of size-fractioning techniques on concentrations of selected trace metals in bottom materials from two streams in northeastern Ohio

USGS Publications Warehouse

Koltun, G.F.; Helsel, Dennis R.

1986-01-01

Identical stream-bottom material samples, when fractioned to the same size by different techniques, may contain significantly different trace-metal concentrations. Precision of techniques also may differ, which could affect the ability to discriminate between size-fractioned bottom-material samples having different metal concentrations. Bottom-material samples fractioned to less than 0.020 millimeters by means of three common techniques (air elutriation, sieving, and settling) were analyzed for six trace metals to determine whether the technique used to obtain the desired particle-size fraction affects the ability to discriminate between bottom materials having different trace-metal concentrations. In addition, this study attempts to assess whether median trace-metal concentrations in size-fractioned bottom materials of identical origin differ depending on the size-fractioning technique used. Finally, this study evaluates the efficiency of the three size-fractioning techniques in terms of time, expense, and effort involved. Bottom-material samples were collected at two sites in northeastern Ohio: One is located in an undeveloped forested basin, and the other is located in a basin having a mixture of industrial and surface-mining land uses. The sites were selected for their close physical proximity, similar contributing drainage areas, and the likelihood that trace-metal concentrations in the bottom materials would be significantly different. Statistically significant differences in the concentrations of trace metals were detected between bottom-material samples collected at the two sites when the samples had been size-fractioned by means of air elutriation or sieving. Statistical analyses of samples that had been size fractioned by settling in native water were not measurably different in any of the six trace metals analyzed. Results of multiple comparison tests suggest that differences related to size-fractioning technique were evident in median copper, lead, and iron concentrations. Technique-related differences in copper concentrations most likely resulted from contamination of air-elutriated samples by a feed tip on the elutriator apparatus. No technique-related differences were observed in chromium, manganese, or zinc concentrations. Although air elutriation was the most expensive sizefractioning technique investigated, samples fractioned by this technique appeared to provide a superior level of discrimination between metal concentrations present in the bottom materials of the two sites. Sieving was an adequate lower-cost but more laborintensive alternative.

Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry

PubMed Central

Trattner, Sigal; Cheng, Bin; Pieniazek, Radoslaw L.; Hoffmann, Udo; Douglas, Pamela S.; Einstein, Andrew J.

2014-01-01

Purpose: Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations. Methods: The statistical scheme involves solving equations which minimize the sample size required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen–pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner. Results: Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv. Conclusions: Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence. PMID:24694150

Systematic review finds major deficiencies in sample size methodology and reporting for stepped-wedge cluster randomised trials

PubMed Central

Martin, James; Taljaard, Monica; Girling, Alan; Hemming, Karla

2016-01-01

Background Stepped-wedge cluster randomised trials (SW-CRT) are increasingly being used in health policy and services research, but unless they are conducted and reported to the highest methodological standards, they are unlikely to be useful to decision-makers. Sample size calculations for these designs require allowance for clustering, time effects and repeated measures. Methods We carried out a methodological review of SW-CRTs up to October 2014. We assessed adherence to reporting each of the 9 sample size calculation items recommended in the 2012 extension of the CONSORT statement to cluster trials. Results We identified 32 completed trials and 28 independent protocols published between 1987 and 2014. Of these, 45 (75%) reported a sample size calculation, with a median of 5.0 (IQR 2.5–6.0) of the 9 CONSORT items reported. Of those that reported a sample size calculation, the majority, 33 (73%), allowed for clustering, but just 15 (33%) allowed for time effects. There was a small increase in the proportions reporting a sample size calculation (from 64% before to 84% after publication of the CONSORT extension, p=0.07). The type of design (cohort or cross-sectional) was not reported clearly in the majority of studies, but cohort designs seemed to be most prevalent. Sample size calculations in cohort designs were particularly poor with only 3 out of 24 (13%) of these studies allowing for repeated measures. Discussion The quality of reporting of sample size items in stepped-wedge trials is suboptimal. There is an urgent need for dissemination of the appropriate guidelines for reporting and methodological development to match the proliferation of the use of this design in practice. Time effects and repeated measures should be considered in all SW-CRT power calculations, and there should be clarity in reporting trials as cohort or cross-sectional designs. PMID:26846897

Samples in applied psychology: over a decade of research in review.

PubMed

Shen, Winny; Kiger, Thomas B; Davies, Stacy E; Rasch, Rena L; Simon, Kara M; Ones, Deniz S

2011-09-01

This study examines sample characteristics of articles published in Journal of Applied Psychology (JAP) from 1995 to 2008. At the individual level, the overall median sample size over the period examined was approximately 173, which is generally adequate for detecting the average magnitude of effects of primary interest to researchers who publish in JAP. Samples using higher units of analyses (e.g., teams, departments/work units, and organizations) had lower median sample sizes (Mdn ≈ 65), yet were arguably robust given typical multilevel design choices of JAP authors despite the practical constraints of collecting data at higher units of analysis. A substantial proportion of studies used student samples (~40%); surprisingly, median sample sizes for student samples were smaller than working adult samples. Samples were more commonly occupationally homogeneous (~70%) than occupationally heterogeneous. U.S. and English-speaking participants made up the vast majority of samples, whereas Middle Eastern, African, and Latin American samples were largely unrepresented. On the basis of study results, recommendations are provided for authors, editors, and readers, which converge on 3 themes: (a) appropriateness and match between sample characteristics and research questions, (b) careful consideration of statistical power, and (c) the increased popularity of quantitative synthesis. Implications are discussed in terms of theory building, generalizability of research findings, and statistical power to detect effects. PsycINFO Database Record (c) 2011 APA, all rights reserved

Phase II Trials for Heterogeneous Patient Populations with a Time-to-Event Endpoint.

PubMed

Jung, Sin-Ho

2017-07-01

In this paper, we consider a single-arm phase II trial with a time-to-event end-point. We assume that the study population has multiple subpopulations with different prognosis, but the study treatment is expected to be similarly efficacious across the subpopulations. We review a stratified one-sample log-rank test and present its sample size calculation method under some practical design settings. Our sample size method requires specification of the prevalence of subpopulations. We observe that the power of the resulting sample size is not very sensitive to misspecification of the prevalence.

Sample size calculations for comparative clinical trials with over-dispersed Poisson process data.

PubMed

Matsui, Shigeyuki

2005-05-15

This paper develops a new formula for sample size calculations for comparative clinical trials with Poisson or over-dispersed Poisson process data. The criteria for sample size calculations is developed on the basis of asymptotic approximations for a two-sample non-parametric test to compare the empirical event rate function between treatment groups. This formula can accommodate time heterogeneity, inter-patient heterogeneity in event rate, and also, time-varying treatment effects. An application of the formula to a trial for chronic granulomatous disease is provided. Copyright 2004 John Wiley & Sons, Ltd.

Measures of precision for dissimilarity-based multivariate analysis of ecological communities

PubMed Central

Anderson, Marti J; Santana-Garcon, Julia

2015-01-01

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity-based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity-based standard error (MultSE) as a useful quantity for assessing sample-size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided. PMID:25438826

How large a training set is needed to develop a classifier for microarray data?

PubMed

Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

2008-01-01

A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

Generalized SAMPLE SIZE Determination Formulas for Investigating Contextual Effects by a Three-Level Random Intercept Model.

PubMed

Usami, Satoshi

2017-03-01

Behavioral and psychological researchers have shown strong interests in investigating contextual effects (i.e., the influences of combinations of individual- and group-level predictors on individual-level outcomes). The present research provides generalized formulas for determining the sample size needed in investigating contextual effects according to the desired level of statistical power as well as width of confidence interval. These formulas are derived within a three-level random intercept model that includes one predictor/contextual variable at each level to simultaneously cover various kinds of contextual effects that researchers can show interest. The relative influences of indices included in the formulas on the standard errors of contextual effects estimates are investigated with the aim of further simplifying sample size determination procedures. In addition, simulation studies are performed to investigate finite sample behavior of calculated statistical power, showing that estimated sample sizes based on derived formulas can be both positively and negatively biased due to complex effects of unreliability of contextual variables, multicollinearity, and violation of assumption regarding the known variances. Thus, it is advisable to compare estimated sample sizes under various specifications of indices and to evaluate its potential bias, as illustrated in the example.

Point Counts of Birds in Bottomland Hardwood Forests of the Mississippi Alluvial Valley: Duration, Minimum Sample Size, and Points Versus Visits

Treesearch

Winston Paul Smith; Daniel J. Twedt; David A. Wiedenfeld; Paul B. Hamel; Robert P. Ford; Robert J. Cooper

1993-01-01

To compare efficacy of point count sampling in bottomland hardwood forests, duration of point count, number of point counts, number of visits to each point during a breeding season, and minimum sample size are examined.

Standard Deviation for Small Samples

ERIC Educational Resources Information Center

Joarder, Anwar H.; Latif, Raja M.

2006-01-01

Neater representations for variance are given for small sample sizes, especially for 3 and 4. With these representations, variance can be calculated without a calculator if sample sizes are small and observations are integers, and an upper bound for the standard deviation is immediate. Accessible proofs of lower and upper bounds are presented for…

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

40 CFR 204.51 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... tests. (m) Test sample means the collection of compressors from the same category or configuration which is randomly drawn from the batch sample and which will receive emissions tests. (n) Batch size means... category or configuration in a batch. (o) Test sample size means the number of compressors of the same...

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

Chaibub Neto, Elias

2015-01-01

In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Sampling system for wheat (Triticum aestivum L) area estimation using digital LANDSAT MSS data and aerial photographs. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Moreira, M. A.; Chen, S. C.; Batista, G. T.

1984-01-01

A procedure to estimate wheat (Triticum aestivum L) area using sampling technique based on aerial photographs and digital LANDSAT MSS data is developed. Aerial photographs covering 720 square km are visually analyzed. To estimate wheat area, a regression approach is applied using different sample sizes and various sampling units. As the size of sampling unit decreased, the percentage of sampled area required to obtain similar estimation performance also decreased. The lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation is 13.90% using 10 square km as the sampling unit. Wheat area estimation using only aerial photographs is less precise and accurate than those obtained by regression estimation.

Thermal conductivity measurements of particulate materials: 3. Natural samples and mixtures of particle sizes

NASA Astrophysics Data System (ADS)

Presley, Marsha A.; Craddock, Robert A.

2006-09-01

A line-heat source apparatus was used to measure thermal conductivities of natural fluvial and eolian particulate sediments under low pressures of a carbon dioxide atmosphere. These measurements were compared to a previous compilation of the dependence of thermal conductivity on particle size to determine a thermal conductivity-derived particle size for each sample. Actual particle-size distributions were determined via physical separation through brass sieves. Comparison of the two analyses indicates that the thermal conductivity reflects the larger particles within the samples. In each sample at least 85-95% of the particles by weight are smaller than or equal to the thermal conductivity-derived particle size. At atmospheric pressures less than about 2-3 torr, samples that contain a large amount of small particles (<=125 μm or 4 Φ) exhibit lower thermal conductivities relative to those for the larger particles within the sample. Nonetheless, 90% of the sample by weight still consists of particles that are smaller than or equal to this lower thermal conductivity-derived particle size. These results allow further refinement in the interpretation of geomorphologic processes acting on the Martian surface. High-energy fluvial environments should produce poorer-sorted and coarser-grained deposits than lower energy eolian environments. Hence these results will provide additional information that may help identify coarser-grained fluvial deposits and may help differentiate whether channel dunes are original fluvial sediments that are at most reworked by wind or whether they represent a later overprint of sediment with a separate origin.

Single and simultaneous binary mergers in Wright-Fisher genealogies.

PubMed

Melfi, Andrew; Viswanath, Divakar

2018-05-01

The Kingman coalescent is a commonly used model in genetics, which is often justified with reference to the Wright-Fisher (WF) model. Current proofs of convergence of WF and other models to the Kingman coalescent assume a constant sample size. However, sample sizes have become quite large in human genetics. Therefore, we develop a convergence theory that allows the sample size to increase with population size. If the haploid population size is N and the sample size is N 1∕3-ϵ , ϵ>0, we prove that Wright-Fisher genealogies involve at most a single binary merger in each generation with probability converging to 1 in the limit of large N. Single binary merger or no merger in each generation of the genealogy implies that the Kingman partition distribution is obtained exactly. If the sample size is N 1∕2-ϵ , Wright-Fisher genealogies may involve simultaneous binary mergers in a single generation but do not involve triple mergers in the large N limit. The asymptotic theory is verified using numerical calculations. Variable population sizes are handled algorithmically. It is found that even distant bottlenecks can increase the probability of triple mergers as well as simultaneous binary mergers in WF genealogies. Copyright © 2018 Elsevier Inc. All rights reserved.

Approximate sample sizes required to estimate length distributions

USGS Publications Warehouse

Miranda, L.E.

2007-01-01

The sample sizes required to estimate fish length were determined by bootstrapping from reference length distributions. Depending on population characteristics and species-specific maximum lengths, 1-cm length-frequency histograms required 375-1,200 fish to estimate within 10% with 80% confidence, 2.5-cm histograms required 150-425 fish, proportional stock density required 75-140 fish, and mean length required 75-160 fish. In general, smaller species, smaller populations, populations with higher mortality, and simpler length statistics required fewer samples. Indices that require low sample sizes may be suitable for monitoring population status, and when large changes in length are evident, additional sampling effort may be allocated to more precisely define length status with more informative estimators. ?? Copyright by the American Fisheries Society 2007.

Sampling the structure and chemical order in assemblies of ferromagnetic nanoparticles by nuclear magnetic resonance

PubMed Central

Liu, Yuefeng; Luo, Jingjie; Shin, Yooleemi; Moldovan, Simona; Ersen, Ovidiu; Hébraud, Anne; Schlatter, Guy; Pham-Huu, Cuong; Meny, Christian

2016-01-01

Assemblies of nanoparticles are studied in many research fields from physics to medicine. However, as it is often difficult to produce mono-dispersed particles, investigating the key parameters enhancing their efficiency is blurred by wide size distributions. Indeed, near-field methods analyse a part of the sample that might not be representative of the full size distribution and macroscopic methods give average information including all particle sizes. Here, we introduce temperature differential ferromagnetic nuclear resonance spectra that allow sampling the crystallographic structure, the chemical composition and the chemical order of non-interacting ferromagnetic nanoparticles for specific size ranges within their size distribution. The method is applied to cobalt nanoparticles for catalysis and allows extracting the size effect from the crystallographic structure effect on their catalytic activity. It also allows sampling of the chemical composition and chemical order within the size distribution of alloyed nanoparticles and can thus be useful in many research fields. PMID:27156575

Analysis of Duplicated Multiple-Samples Rank Data Using the Mack-Skillings Test.

PubMed

Carabante, Kennet Mariano; Alonso-Marenco, Jose Ramon; Chokumnoyporn, Napapan; Sriwattana, Sujinda; Prinyawiwatkul, Witoon

2016-07-01

Appropriate analysis for duplicated multiple-samples rank data is needed. This study compared analysis of duplicated rank preference data using the Friedman versus Mack-Skillings tests. Panelists (n = 125) ranked twice 2 orange juice sets: different-samples set (100%, 70%, vs. 40% juice) and similar-samples set (100%, 95%, vs. 90%). These 2 sample sets were designed to get contrasting differences in preference. For each sample set, rank sum data were obtained from (1) averaged rank data of each panelist from the 2 replications (n = 125), (2) rank data of all panelists from each of the 2 separate replications (n = 125 each), (3) jointed rank data of all panelists from the 2 replications (n = 125), and (4) rank data of all panelists pooled from the 2 replications (n = 250); rank data (1), (2), and (4) were separately analyzed by the Friedman test, although those from (3) by the Mack-Skillings test. The effect of sample sizes (n = 10 to 125) was evaluated. For the similar-samples set, higher variations in rank data from the 2 replications were observed; therefore, results of the main effects were more inconsistent among methods and sample sizes. Regardless of analysis methods, the larger the sample size, the higher the χ(2) value, the lower the P-value (testing H0 : all samples are not different). Analyzing rank data (2) separately by replication yielded inconsistent conclusions across sample sizes, hence this method is not recommended. The Mack-Skillings test was more sensitive than the Friedman test. Furthermore, it takes into account within-panelist variations and is more appropriate for analyzing duplicated rank data. © 2016 Institute of Food Technologists®

Rock sampling. [apparatus for controlling particle size

NASA Technical Reports Server (NTRS)

Blum, P. (Inventor)

1971-01-01

An apparatus for sampling rock and other brittle materials and for controlling resultant particle sizes is described. The device includes grinding means for cutting grooves in the rock surface and to provide a grouping of thin, shallow, parallel ridges and cutter means to reduce these ridges to a powder specimen. Collection means is provided for the powder. The invention relates to rock grinding and particularly to the sampling of rock specimens with good size control.

Revisiting sample size: are big trials the answer?

PubMed

Lurati Buse, Giovanna A L; Botto, Fernando; Devereaux, P J

2012-07-18

The superiority of the evidence generated in randomized controlled trials over observational data is not only conditional to randomization. Randomized controlled trials require proper design and implementation to provide a reliable effect estimate. Adequate random sequence generation, allocation implementation, analyses based on the intention-to-treat principle, and sufficient power are crucial to the quality of a randomized controlled trial. Power, or the probability of the trial to detect a difference when a real difference between treatments exists, strongly depends on sample size. The quality of orthopaedic randomized controlled trials is frequently threatened by a limited sample size. This paper reviews basic concepts and pitfalls in sample-size estimation and focuses on the importance of large trials in the generation of valid evidence.

A novel sample size formula for the weighted log-rank test under the proportional hazards cure model.

PubMed

Xiong, Xiaoping; Wu, Jianrong

2017-01-01

The treatment of cancer has progressed dramatically in recent decades, such that it is no longer uncommon to see a cure or log-term survival in a significant proportion of patients with various types of cancer. To adequately account for the cure fraction when designing clinical trials, the cure models should be used. In this article, a sample size formula for the weighted log-rank test is derived under the fixed alternative hypothesis for the proportional hazards cure models. Simulation showed that the proposed sample size formula provides an accurate estimation of sample size for designing clinical trials under the proportional hazards cure models. Copyright © 2016 John Wiley & Sons, Ltd.

Sampling designs for contaminant temporal trend analyses using sedentary species exemplified by the snails Bellamya aeruginosa and Viviparus viviparus.

PubMed

Yin, Ge; Danielsson, Sara; Dahlberg, Anna-Karin; Zhou, Yihui; Qiu, Yanling; Nyberg, Elisabeth; Bignert, Anders

2017-10-01

Environmental monitoring typically assumes samples and sampling activities to be representative of the population being studied. Given a limited budget, an appropriate sampling strategy is essential to support detecting temporal trends of contaminants. In the present study, based on real chemical analysis data on polybrominated diphenyl ethers in snails collected from five subsites in Tianmu Lake, computer simulation is performed to evaluate three sampling strategies by the estimation of required sample size, to reach a detection of an annual change of 5% with a statistical power of 80% and 90% with a significant level of 5%. The results showed that sampling from an arbitrarily selected sampling spot is the worst strategy, requiring much more individual analyses to achieve the above mentioned criteria compared with the other two approaches. A fixed sampling site requires the lowest sample size but may not be representative for the intended study object e.g. a lake and is also sensitive to changes of that particular sampling site. In contrast, sampling at multiple sites along the shore each year, and using pooled samples when the cost to collect and prepare individual specimens are much lower than the cost for chemical analysis, would be the most robust and cost efficient strategy in the long run. Using statistical power as criterion, the results demonstrated quantitatively the consequences of various sampling strategies, and could guide users with respect of required sample sizes depending on sampling design for long term monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effect on the grain size of single-mode microwave sintered NiCuZn ferrite and zinc titanate dielectric resonator ceramics.

PubMed

Sirugudu, Roopas Kiran; Vemuri, Rama Krishna Murthy; Venkatachalam, Subramanian; Gopalakrishnan, Anisha; Budaraju, Srinivasa Murty

2011-01-01

Microwave sintering of materials significantly depends on dielectric, magnetic and conductive Losses. Samples with high dielectric and magnetic loss such as ferrites could be sintered easily. But low dielectric loss material such as dielectric resonators (paraelectrics) finds difficulty in generation of heat during microwave interaction. Microwave sintering of materials of these two classes helps in understanding the variation in dielectric and magnetic characteristics with respect to the change in grain size. High-energy ball milled Ni0.6Cu0.2Zn0.2Fe1.98O4-delta and ZnTiO3 are sintered in conventional and microwave methods and characterized for respective dielectric and magnetic characteristics. The grain size variation with higher copper content is also observed with conventional and microwave sintering. The grain size in microwave sintered Ni0.6Cu0.2Zn0.2Fe1.98O4-delta is found to be much small and uniform in comparison with conventional sintered sample. However, the grain size of microwave sintered sample is almost equal to that of conventional sintered sample of Ni0.3Cu0.5Zn0.2Fe1.98O4-delta. In contrast to these high dielectric and magnetic loss ferrites, the paraelectric materials are observed to sinter in presence of microwaves. Although microwave sintered zinc titanate sample showed finer and uniform grains with respect to conventional samples, the dielectric characteristics of microwave sintered sample are found to be less than that of conventional sample. Low dielectric constant is attributed to the low density. Smaller grain size is found to be responsible for low quality factor and the presence of small percentage of TiO2 is observed to achieve the temperature stable resonant frequency.

Three-year-olds obey the sample size principle of induction: the influence of evidence presentation and sample size disparity on young children's generalizations.

PubMed

Lawson, Chris A

2014-07-01

Three experiments with 81 3-year-olds (M=3.62years) examined the conditions that enable young children to use the sample size principle (SSP) of induction-the inductive rule that facilitates generalizations from large rather than small samples of evidence. In Experiment 1, children exhibited the SSP when exemplars were presented sequentially but not when exemplars were presented simultaneously. Results from Experiment 3 suggest that the advantage of sequential presentation is not due to the additional time to process the available input from the two samples but instead may be linked to better memory for specific individuals in the large sample. In addition, findings from Experiments 1 and 2 suggest that adherence to the SSP is mediated by the disparity between presented samples. Overall, these results reveal that the SSP appears early in development and is guided by basic cognitive processes triggered during the acquisition of input. Copyright © 2013 Elsevier Inc. All rights reserved.

Are catchment-wide erosion rates really "Catchment-Wide"? Effects of grain size on erosion rates determined from 10Be

NASA Astrophysics Data System (ADS)

Reitz, M. A.; Seeber, L.; Schaefer, J. M.; Ferguson, E. K.

2012-12-01

Early studies pioneering the method for catchment wide erosion rates by measuring 10Be in alluvial sediment were taken at river mouths and used the sand size grain fraction from the riverbeds in order to average upstream erosion rates and measure erosion patterns. Finer particles (<0.0625 mm) were excluded to reduce the possibility of a wind-blown component of sediment and coarser particles (>2 mm) were excluded to better approximate erosion from the entire upstream catchment area (coarse grains are generally found near the source). Now that the sensitivity of 10Be measurements is rapidly increasing, we can precisely measure erosion rates from rivers eroding active tectonic regions. These active regions create higher energy drainage systems that erode faster and carry coarser sediment. In these settings, does the sand-sized fraction fully capture the average erosion of the upstream drainage area? Or does a different grain size fraction provide a more accurate measure of upstream erosion? During a study of the Neto River in Calabria, southern Italy, we took 8 samples along the length of the river, focusing on collecting samples just below confluences with major tributaries, in order to use the high-resolution erosion rate data to constrain tectonic motion. The samples we measured were sieved to either a 0.125 mm - 0.710 mm fraction or the 0.125 mm - 4 mm fraction (depending on how much of the former was available). After measuring these 8 samples for 10Be and determining erosion rates, we used the approach by Granger et al. [1996] to calculate the subcatchment erosion rates between each sample point. In the subcatchments of the river where we used grain sizes up to 4 mm, we measured very low 10Be concentrations (corresponding to high erosion rates) and calculated nonsensical subcatchment erosion rates (i.e. negative rates). We, therefore, hypothesize that the coarser grain sizes we included are preferentially sampling a smaller upstream area, and not the entire upstream catchment, which is assumed when measurements are based solely on the sand sized fraction. To test this hypothesis, we used samples with a variety of grain sizes from the Shillong Plateau. We sieved 5 samples into three grain size fractions: 0.125 mm - 710 mm, 710 mm - 4 mm, and >4 mm and measured 10Be concentrations in each fraction. Although there is some variation in the grain size fraction that yields the highest erosion rate, generally, the coarser grain size fractions have higher erosion rates. More significant are the results when calculating the subcatchment erosion rates, which suggest that even medium sized grains (710 mm - 4 mm) are sampling an area smaller than the entire upstream area; this finding is consistent with the nonsensical results from the Neto River study. This result has numerous implications for the interpretations of 10Be erosion rates: most importantly, an alluvial sample may not be averaging the entire upstream area, even when using the sand size fraction - resulting erosion rates more pertinent for that sample point rather than the entire catchment.

A microfluidic platform for precision small-volume sample processing and its use to size separate biological particles with an acoustic microdevice [Precision size separation of biological particles in small-volume samples by an acoustic microfluidic system

DOE PAGES

Fong, Erika J.; Huang, Chao; Hamilton, Julie; ...

2015-11-23

Here, a major advantage of microfluidic devices is the ability to manipulate small sample volumes, thus reducing reagent waste and preserving precious sample. However, to achieve robust sample manipulation it is necessary to address device integration with the macroscale environment. To realize repeatable, sensitive particle separation with microfluidic devices, this protocol presents a complete automated and integrated microfluidic platform that enables precise processing of 0.15–1.5 ml samples using microfluidic devices. Important aspects of this system include modular device layout and robust fixtures resulting in reliable and flexible world to chip connections, and fully-automated fluid handling which accomplishes closed-loop sample collection,more » system cleaning and priming steps to ensure repeatable operation. Different microfluidic devices can be used interchangeably with this architecture. Here we incorporate an acoustofluidic device, detail its characterization, performance optimization, and demonstrate its use for size-separation of biological samples. By using real-time feedback during separation experiments, sample collection is optimized to conserve and concentrate sample. Although requiring the integration of multiple pieces of equipment, advantages of this architecture include the ability to process unknown samples with no additional system optimization, ease of device replacement, and precise, robust sample processing.« less

Size Effect on the Mechanical Properties of CF Winding Composite

NASA Astrophysics Data System (ADS)

Cui, Yuqing; Yin, Zhongwei

2017-12-01

Mechanical properties of filament winding composites are usually tested by NOL ring samples. Few people have studied the size effect of winding composite samples on the testing result of mechanical property. In this research, winding composite thickness, diameter, and geometry of NOL ring samples were prepared to investigate the size effect on the mechanical strength of carbon fiber (CF) winding composite. The CF T700, T1000, M40, and M50 were adopted for the winding composite, while the matrix was epoxy resin. Test results show that the tensile strength and ILSS of composites decreases monotonically with an increase of thickness from 1 mm to 4 mm. The mechanical strength of composite samples increases monotonically with the increase in diameter from 100 mm to 189 mm. The mechanical strength of composite samples with two flat sides are higher than those of cyclic annular samples.

Automated sampling assessment for molecular simulations using the effective sample size

PubMed Central

Zhang, Xin; Bhatt, Divesh; Zuckerman, Daniel M.

2010-01-01

To quantify the progress in the development of algorithms and forcefields used in molecular simulations, a general method for the assessment of the sampling quality is needed. Statistical mechanics principles suggest the populations of physical states characterize equilibrium sampling in a fundamental way. We therefore develop an approach for analyzing the variances in state populations, which quantifies the degree of sampling in terms of the effective sample size (ESS). The ESS estimates the number of statistically independent configurations contained in a simulated ensemble. The method is applicable to both traditional dynamics simulations as well as more modern (e.g., multi–canonical) approaches. Our procedure is tested in a variety of systems from toy models to atomistic protein simulations. We also introduce a simple automated procedure to obtain approximate physical states from dynamic trajectories: this allows sample–size estimation in systems for which physical states are not known in advance. PMID:21221418

Sampling Theory and Confidence Intervals for Effect Sizes: Using ESCI To Illustrate "Bouncing"; Confidence Intervals.

ERIC Educational Resources Information Center

Du, Yunfei

This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…

77 FR 2697 - Proposed Information Collection; Comment Request; Annual Services Report

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-19

... and from a sample of small- and medium-sized businesses selected using a stratified sampling procedure... be canvassed when the sample is re-drawn, while nearly all of the small- and medium-sized firms from...); Educational Services (NAICS 61); Health Care and Social Assistance (NAICS 62); Arts, Entertainment, and...

40 CFR 94.505 - Sample selection for testing.

Code of Federal Regulations, 2010 CFR

2010-07-01

... engine family. The required sample size is zero if a manufacturer's projected annual production for all Category 1 engine families is less than 100. (ii) The required sample size for a Category 2 engine family... manufacturer will begin to select engines from each Category 1 and Category 2 engine family for production line...

Norm Block Sample Sizes: A Review of 17 Individually Administered Intelligence Tests

ERIC Educational Resources Information Center

Norfolk, Philip A.; Farmer, Ryan L.; Floyd, Randy G.; Woods, Isaac L.; Hawkins, Haley K.; Irby, Sarah M.

2015-01-01

The representativeness, recency, and size of norm samples strongly influence the accuracy of inferences drawn from their scores. Inadequate norm samples may lead to inflated or deflated scores for individuals and poorer prediction of developmental and academic outcomes. The purpose of this study was to apply Kranzler and Floyd's method for…

Technology Tips: Sample Too Small? Probably Not!

ERIC Educational Resources Information Center

Strayer, Jeremy F.

2013-01-01

Statistical studies are referenced in the news every day, so frequently that people are sometimes skeptical of reported results. Often, no matter how large a sample size researchers use in their studies, people believe that the sample size is too small to make broad generalizations. The tasks presented in this article use simulations of repeated…

Determining the sample size for co-dominant molecular marker-assisted linkage detection for a monogenic qualitative trait by controlling the type-I and type-II errors in a segregating F2 population.

PubMed

Hühn, M; Piepho, H P

2003-03-01

Tests for linkage are usually performed using the lod score method. A critical question in linkage analyses is the choice of sample size. The appropriate sample size depends on the desired type-I error and power of the test. This paper investigates the exact type-I error and power of the lod score method in a segregating F(2) population with co-dominant markers and a qualitative monogenic dominant-recessive trait. For illustration, a disease-resistance trait is considered, where the susceptible allele is recessive. A procedure is suggested for finding the appropriate sample size. It is shown that recessive plants have about twice the information content of dominant plants, so the former should be preferred for linkage detection. In some cases the exact alpha-values for a given nominal alpha may be rather small due to the discrete nature of the sampling distribution in small samples. We show that a gain in power is possible by using exact methods.

EPICS Controlled Collimator for Controlling Beam Sizes in HIPPO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Napolitano, Arthur Soriano; Vogel, Sven C.

2017-08-03

Controlling the beam spot size and shape in a diffraction experiment determines the probed sample volume. The HIPPO - High-Pressure-Preferred Orientation– neutron time-offlight diffractometer is located at the Lujan Neutron Scattering Center in Los Alamos National Laboratories. HIPPO characterizes microstructural parameters, such as phase composition, strains, grain size, or texture, of bulk (cm-sized) samples. In the current setup, the beam spot has a 10 mm diameter. Using a collimator, consisting of two pairs of neutron absorbing boron-nitride slabs, horizontal and vertical dimensions of a rectangular beam spot can be defined. Using the HIPPO robotic sample changer for sample motion, themore » collimator would enable scanning of e.g. cylindrical samples along the cylinder axis by probing slices of such samples. The project presented here describes implementation of such a collimator, in particular the motion control software. We utilized the EPICS (Experimental Physics Interface and Control System) software interface to integrate the collimator control into the HIPPO instrument control system. Using EPICS, commands are sent to commercial stepper motors that move the beam windows.« less

Determination of sample size for higher volatile data using new framework of Box-Jenkins model with GARCH: A case study on gold price

NASA Astrophysics Data System (ADS)

Roslindar Yaziz, Siti; Zakaria, Roslinazairimah; Hura Ahmad, Maizah

2017-09-01

The model of Box-Jenkins - GARCH has been shown to be a promising tool for forecasting higher volatile time series. In this study, the framework of determining the optimal sample size using Box-Jenkins model with GARCH is proposed for practical application in analysing and forecasting higher volatile data. The proposed framework is employed to daily world gold price series from year 1971 to 2013. The data is divided into 12 different sample sizes (from 30 to 10200). Each sample is tested using different combination of the hybrid Box-Jenkins - GARCH model. Our study shows that the optimal sample size to forecast gold price using the framework of the hybrid model is 1250 data of 5-year sample. Hence, the empirical results of model selection criteria and 1-step-ahead forecasting evaluations suggest that the latest 12.25% (5-year data) of 10200 data is sufficient enough to be employed in the model of Box-Jenkins - GARCH with similar forecasting performance as by using 41-year data.

[A comparison of convenience sampling and purposive sampling].

PubMed

Suen, Lee-Jen Wu; Huang, Hui-Man; Lee, Hao-Hsien

2014-06-01

Convenience sampling and purposive sampling are two different sampling methods. This article first explains sampling terms such as target population, accessible population, simple random sampling, intended sample, actual sample, and statistical power analysis. These terms are then used to explain the difference between "convenience sampling" and purposive sampling." Convenience sampling is a non-probabilistic sampling technique applicable to qualitative or quantitative studies, although it is most frequently used in quantitative studies. In convenience samples, subjects more readily accessible to the researcher are more likely to be included. Thus, in quantitative studies, opportunity to participate is not equal for all qualified individuals in the target population and study results are not necessarily generalizable to this population. As in all quantitative studies, increasing the sample size increases the statistical power of the convenience sample. In contrast, purposive sampling is typically used in qualitative studies. Researchers who use this technique carefully select subjects based on study purpose with the expectation that each participant will provide unique and rich information of value to the study. As a result, members of the accessible population are not interchangeable and sample size is determined by data saturation not by statistical power analysis.

(I Can’t Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research

PubMed Central

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: “random chance,” which is based on probability sampling, “minimal information,” which yields at least one new code per sampling step, and “maximum information,” which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario. PMID:28746358

The effective elastic properties of human trabecular bone may be approximated using micro-finite element analyses of embedded volume elements.

PubMed

Daszkiewicz, Karol; Maquer, Ghislain; Zysset, Philippe K

2017-06-01

Boundary conditions (BCs) and sample size affect the measured elastic properties of cancellous bone. Samples too small to be representative appear stiffer under kinematic uniform BCs (KUBCs) than under periodicity-compatible mixed uniform BCs (PMUBCs). To avoid those effects, we propose to determine the effective properties of trabecular bone using an embedded configuration. Cubic samples of various sizes (2.63, 5.29, 7.96, 10.58 and 15.87 mm) were cropped from [Formula: see text] scans of femoral heads and vertebral bodies. They were converted into [Formula: see text] models and their stiffness tensor was established via six uniaxial and shear load cases. PMUBCs- and KUBCs-based tensors were determined for each sample. "In situ" stiffness tensors were also evaluated for the embedded configuration, i.e. when the loads were transmitted to the samples via a layer of trabecular bone. The Zysset-Curnier model accounting for bone volume fraction and fabric anisotropy was fitted to those stiffness tensors, and model parameters [Formula: see text] (Poisson's ratio) [Formula: see text] and [Formula: see text] (elastic and shear moduli) were compared between sizes. BCs and sample size had little impact on [Formula: see text]. However, KUBCs- and PMUBCs-based [Formula: see text] and [Formula: see text], respectively, decreased and increased with growing size, though convergence was not reached even for our largest samples. Both BCs produced upper and lower bounds for the in situ values that were almost constant across samples dimensions, thus appearing as an approximation of the effective properties. PMUBCs seem also appropriate for mimicking the trabecular core, but they still underestimate its elastic properties (especially in shear) even for nearly orthotropic samples.

Rule-of-thumb adjustment of sample sizes to accommodate dropouts in a two-stage analysis of repeated measurements.

PubMed

Overall, John E; Tonidandel, Scott; Starbuck, Robert R

2006-01-01

Recent contributions to the statistical literature have provided elegant model-based solutions to the problem of estimating sample sizes for testing the significance of differences in mean rates of change across repeated measures in controlled longitudinal studies with differentially correlated error and missing data due to dropouts. However, the mathematical complexity and model specificity of these solutions make them generally inaccessible to most applied researchers who actually design and undertake treatment evaluation research in psychiatry. In contrast, this article relies on a simple two-stage analysis in which dropout-weighted slope coefficients fitted to the available repeated measurements for each subject separately serve as the dependent variable for a familiar ANCOVA test of significance for differences in mean rates of change. This article is about how a sample of size that is estimated or calculated to provide desired power for testing that hypothesis without considering dropouts can be adjusted appropriately to take dropouts into account. Empirical results support the conclusion that, whatever reasonable level of power would be provided by a given sample size in the absence of dropouts, essentially the same power can be realized in the presence of dropouts simply by adding to the original dropout-free sample size the number of subjects who would be expected to drop from a sample of that original size under conditions of the proposed study.

Using sieving and pretreatment to separate plastics during end-of-life vehicle recycling.

PubMed

Stagner, Jacqueline A; Sagan, Barsha; Tam, Edwin Kl

2013-09-01

Plastics continue to be a challenge for recovering materials at the end-of-life for vehicles. However, it may be possible to improve the recovery of plastics by exploiting material characteristics, such as shape, or by altering their behavior, such as through temperature changes, in relation to recovery processes and handling. Samples of a 2009 Dodge Challenger front fascia were shredded in a laboratory-scale hammer mill shredder. A 2 × 2 factorial design study was performed to determine the effect of sample shape (flat versus curved) and sample temperature (room temperature versus cryogenic temperature) on the size of the particles exiting from the shredder. It was determined that sample shape does not affect the particle size; however, sample temperature does affect the particle size. At cryogenic temperatures, the distribution of particle sizes is much narrower than at room temperature. Having a more uniform particle size could make recovery of plastic particles, such as these more efficient during the recycling of end-of-life vehicles. Samples of Chrysler minivan headlights were also shredded at room temperature and at cryogenic temperatures. The size of the particles of the two different plastics in the headlights is statistically different both at room temperature and at cryogenic temperature, and the particles are distributed narrowly. The research suggests that incremental changes in end-of-life vehicle processing could be effective in aiding materials recovery.

Size Matters: FTIR Spectral Analysis of Apollo Regolith Samples Exhibits Grain Size Dependence.

NASA Astrophysics Data System (ADS)

Martin, Dayl; Joy, Katherine; Pernet-Fisher, John; Wogelius, Roy; Morlok, Andreas; Hiesinger, Harald

2017-04-01

The Mercury Thermal Infrared Spectrometer (MERTIS) on the upcoming BepiColombo mission is designed to analyse the surface of Mercury in thermal infrared wavelengths (7-14 μm) to investigate the physical properties of the surface materials [1]. Laboratory analyses of analogue materials are useful for investigating how various sample properties alter the resulting infrared spectrum. Laboratory FTIR analysis of Apollo fine (<1mm) soil samples 14259,672, 15401,147, and 67481,96 have provided an insight into how grain size, composition, maturity (i.e., exposure to space weathering processes), and proportion of glassy material affect their average infrared spectra. Each of these samples was analysed as a bulk sample and five size fractions: <25, 25-63, 63-125, 125-250, and <250 μm. Sample 14259,672 is a highly mature highlands regolith with a large proportion of agglutinates [2]. The high agglutinate content (>60%) causes a 'flattening' of the spectrum, with reduced reflectance in the Reststrahlen Band region (RB) as much as 30% in comparison to samples that are dominated by a high proportion of crystalline material. Apollo 15401,147 is an immature regolith with a high proportion of volcanic glass pyroclastic beads [2]. The high mafic mineral content results in a systematic shift in the Christiansen Feature (CF - the point of lowest reflectance) to longer wavelength: 8.6 μm. The glass beads dominate the spectrum, displaying a broad peak around the main Si-O stretch band (at 10.8 μm). As such, individual mineral components of this sample cannot be resolved from the average spectrum alone. Apollo 67481,96 is a sub-mature regolith composed dominantly of anorthite plagioclase [2]. The CF position of the average spectrum is shifted to shorter wavelengths (8.2 μm) due to the higher proportion of felsic minerals. Its average spectrum is dominated by anorthite reflectance bands at 8.7, 9.1, 9.8, and 10.8 μm. The average reflectance is greater than the other samples due to a lower proportion of glassy material. In each soil, the smallest fractions (0-25 and 25-63 μm) have CF positions 0.1-0.4 μm higher than the larger grain sizes. Also, the bulk-sample spectra mostly closely resemble the 0-25 μm sieved size fraction spectrum, indicating that this size fraction of each sample dominates the bulk spectrum regardless of other physical properties. This has implications for surface analyses of other Solar System bodies where some mineral phases or components could be concentrated in a particular size fraction. For example, the anorthite grains in 67481,96 are dominantly >25 μm in size and therefore may not contribute proportionally to the bulk average spectrum (compared to the <25 μm fraction). The resulting bulk spectrum of 67481,96 has a CF position 0.2 μm higher than all size fractions >25 microns and therefore does not represent a true average composition of the sample. Further investigation of how grain size and composition alters the average spectrum is required to fully understand infrared spectra of planetary surfaces. [1] - Hiesinger H., Helbert J., and MERTIS Co-I Team. (2010). The Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) for the BepiColombo Mission. Planetary and Space Science. 58, 144-165. [2] - NASA Lunar Sample Compendium. https://curator.jsc.nasa.gov/lunar/lsc/

Technical note: Alternatives to reduce adipose tissue sampling bias.

PubMed

Cruz, G D; Wang, Y; Fadel, J G

2014-10-01

Understanding the mechanisms by which nutritional and pharmaceutical factors can manipulate adipose tissue growth and development in production animals has direct and indirect effects in the profitability of an enterprise. Adipocyte cellularity (number and size) is a key biological response that is commonly measured in animal science research. The variability and sampling of adipocyte cellularity within a muscle has been addressed in previous studies, but no attempt to critically investigate these issues has been proposed in the literature. The present study evaluated 2 sampling techniques (random and systematic) in an attempt to minimize sampling bias and to determine the minimum number of samples from 1 to 15 needed to represent the overall adipose tissue in the muscle. Both sampling procedures were applied on adipose tissue samples dissected from 30 longissimus muscles from cattle finished either on grass or grain. Briefly, adipose tissue samples were fixed with osmium tetroxide, and size and number of adipocytes were determined by a Coulter Counter. These results were then fit in a finite mixture model to obtain distribution parameters of each sample. To evaluate the benefits of increasing number of samples and the advantage of the new sampling technique, the concept of acceptance ratio was used; simply stated, the higher the acceptance ratio, the better the representation of the overall population. As expected, a great improvement on the estimation of the overall adipocyte cellularity parameters was observed using both sampling techniques when sample size number increased from 1 to 15 samples, considering both techniques' acceptance ratio increased from approximately 3 to 25%. When comparing sampling techniques, the systematic procedure slightly improved parameters estimation. The results suggest that more detailed research using other sampling techniques may provide better estimates for minimum sampling.

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please visit http://public.tgen.org/tamu/ofs/ e-dougherty@ee.tamu.edu.

Sample size requirements for estimating effective dose from computed tomography using solid-state metal-oxide-semiconductor field-effect transistor dosimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trattner, Sigal; Cheng, Bin; Pieniazek, Radoslaw L.

2014-04-15

Purpose: Effective dose (ED) is a widely used metric for comparing ionizing radiation burden between different imaging modalities, scanners, and scan protocols. In computed tomography (CT), ED can be estimated by performing scans on an anthropomorphic phantom in which metal-oxide-semiconductor field-effect transistor (MOSFET) solid-state dosimeters have been placed to enable organ dose measurements. Here a statistical framework is established to determine the sample size (number of scans) needed for estimating ED to a desired precision and confidence, for a particular scanner and scan protocol, subject to practical limitations. Methods: The statistical scheme involves solving equations which minimize the sample sizemore » required for estimating ED to desired precision and confidence. It is subject to a constrained variation of the estimated ED and solved using the Lagrange multiplier method. The scheme incorporates measurement variation introduced both by MOSFET calibration, and by variation in MOSFET readings between repeated CT scans. Sample size requirements are illustrated on cardiac, chest, and abdomen–pelvis CT scans performed on a 320-row scanner and chest CT performed on a 16-row scanner. Results: Sample sizes for estimating ED vary considerably between scanners and protocols. Sample size increases as the required precision or confidence is higher and also as the anticipated ED is lower. For example, for a helical chest protocol, for 95% confidence and 5% precision for the ED, 30 measurements are required on the 320-row scanner and 11 on the 16-row scanner when the anticipated ED is 4 mSv; these sample sizes are 5 and 2, respectively, when the anticipated ED is 10 mSv. Conclusions: Applying the suggested scheme, it was found that even at modest sample sizes, it is feasible to estimate ED with high precision and a high degree of confidence. As CT technology develops enabling ED to be lowered, more MOSFET measurements are needed to estimate ED with the same precision and confidence.« less

Small Sample Sizes Yield Biased Allometric Equations in Temperate Forests

PubMed Central

Duncanson, L.; Rourke, O.; Dubayah, R.

2015-01-01

Accurate quantification of forest carbon stocks is required for constraining the global carbon cycle and its impacts on climate. The accuracies of forest biomass maps are inherently dependent on the accuracy of the field biomass estimates used to calibrate models, which are generated with allometric equations. Here, we provide a quantitative assessment of the sensitivity of allometric parameters to sample size in temperate forests, focusing on the allometric relationship between tree height and crown radius. We use LiDAR remote sensing to isolate between 10,000 to more than 1,000,000 tree height and crown radius measurements per site in six U.S. forests. We find that fitted allometric parameters are highly sensitive to sample size, producing systematic overestimates of height. We extend our analysis to biomass through the application of empirical relationships from the literature, and show that given the small sample sizes used in common allometric equations for biomass, the average site-level biomass bias is ~+70% with a standard deviation of 71%, ranging from −4% to +193%. These findings underscore the importance of increasing the sample sizes used for allometric equation generation. PMID:26598233

[Sample size calculation in clinical post-marketing evaluation of traditional Chinese medicine].

PubMed

Fu, Yingkun; Xie, Yanming

2011-10-01

In recent years, as the Chinese government and people pay more attention on the post-marketing research of Chinese Medicine, part of traditional Chinese medicine breed has or is about to begin after the listing of post-marketing evaluation study. In the post-marketing evaluation design, sample size calculation plays a decisive role. It not only ensures the accuracy and reliability of post-marketing evaluation. but also assures that the intended trials will have a desired power for correctly detecting a clinically meaningful difference of different medicine under study if such a difference truly exists. Up to now, there is no systemic method of sample size calculation in view of the traditional Chinese medicine. In this paper, according to the basic method of sample size calculation and the characteristic of the traditional Chinese medicine clinical evaluation, the sample size calculation methods of the Chinese medicine efficacy and safety are discussed respectively. We hope the paper would be beneficial to medical researchers, and pharmaceutical scientists who are engaged in the areas of Chinese medicine research.

Estimation after classification using lot quality assurance sampling: corrections for curtailed sampling with application to evaluating polio vaccination campaigns.

PubMed

Olives, Casey; Valadez, Joseph J; Pagano, Marcello

2014-03-01

To assess the bias incurred when curtailment of Lot Quality Assurance Sampling (LQAS) is ignored, to present unbiased estimators, to consider the impact of cluster sampling by simulation and to apply our method to published polio immunization data from Nigeria. We present estimators of coverage when using two kinds of curtailed LQAS strategies: semicurtailed and curtailed. We study the proposed estimators with independent and clustered data using three field-tested LQAS designs for assessing polio vaccination coverage, with samples of size 60 and decision rules of 9, 21 and 33, and compare them to biased maximum likelihood estimators. Lastly, we present estimates of polio vaccination coverage from previously published data in 20 local government authorities (LGAs) from five Nigerian states. Simulations illustrate substantial bias if one ignores the curtailed sampling design. Proposed estimators show no bias. Clustering does not affect the bias of these estimators. Across simulations, standard errors show signs of inflation as clustering increases. Neither sampling strategy nor LQAS design influences estimates of polio vaccination coverage in 20 Nigerian LGAs. When coverage is low, semicurtailed LQAS strategies considerably reduces the sample size required to make a decision. Curtailed LQAS designs further reduce the sample size when coverage is high. Results presented dispel the misconception that curtailed LQAS data are unsuitable for estimation. These findings augment the utility of LQAS as a tool for monitoring vaccination efforts by demonstrating that unbiased estimation using curtailed designs is not only possible but these designs also reduce the sample size. © 2014 John Wiley & Sons Ltd.

Field test comparison of an autocorrelation technique for determining grain size using a digital 'beachball' camera versus traditional methods

USGS Publications Warehouse

Barnard, P.L.; Rubin, D.M.; Harney, J.; Mustain, N.

2007-01-01

This extensive field test of an autocorrelation technique for determining grain size from digital images was conducted using a digital bed-sediment camera, or 'beachball' camera. Using 205 sediment samples and >1200 images from a variety of beaches on the west coast of the US, grain size ranging from sand to granules was measured from field samples using both the autocorrelation technique developed by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160-165.] and traditional methods (i.e. settling tube analysis, sieving, and point counts). To test the accuracy of the digital-image grain size algorithm, we compared results with manual point counts of an extensive image data set in the Santa Barbara littoral cell. Grain sizes calculated using the autocorrelation algorithm were highly correlated with the point counts of the same images (r2 = 0.93; n = 79) and had an error of only 1%. Comparisons of calculated grain sizes and grain sizes measured from grab samples demonstrated that the autocorrelation technique works well on high-energy dissipative beaches with well-sorted sediment such as in the Pacific Northwest (r2 ??? 0.92; n = 115). On less dissipative, more poorly sorted beaches such as Ocean Beach in San Francisco, results were not as good (r2 ??? 0.70; n = 67; within 3% accuracy). Because the algorithm works well compared with point counts of the same image, the poorer correlation with grab samples must be a result of actual spatial and vertical variability of sediment in the field; closer agreement between grain size in the images and grain size of grab samples can be achieved by increasing the sampling volume of the images (taking more images, distributed over a volume comparable to that of a grab sample). In all field tests the autocorrelation method was able to predict the mean and median grain size with ???96% accuracy, which is more than adequate for the majority of sedimentological applications, especially considering that the autocorrelation technique is estimated to be at least 100 times faster than traditional methods.

Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains

NASA Astrophysics Data System (ADS)

Abercrombie, H. H.; Meier, C. L.; Spencer, J. J.

2013-12-01

Over the course of 30 years, the National Ecological Observatory Network (NEON) will measure plant biomass and productivity across the U.S. to enable an understanding of terrestrial carbon cycle responses to ecosystem change drivers. Over the next several years, prior to operational sampling at a site, NEON will complete construction and characterization phases during which a limited amount of sampling will be done at each site to inform sampling designs, and guide standardization of data collection across all sites. Sampling biomass in 60+ sites distributed among 20 different eco-climatic domains poses major logistical and budgetary challenges. Traditional biomass sampling methods such as clip harvesting and direct measurements of Leaf Area Index (LAI) involve collecting and processing plant samples, and are time and labor intensive. Possible alternatives include using indirect sampling methods for estimating LAI such as digital hemispherical photography (DHP) or using a LI-COR 2200 Plant Canopy Analyzer. These LAI estimations can then be used as a proxy for biomass. The biomass estimates calculated can then inform the clip harvest sampling design during NEON operations, optimizing both sample size and number so that standardized uncertainty limits can be achieved with a minimum amount of sampling effort. In 2011, LAI and clip harvest data were collected from co-located sampling points at the Central Plains Experimental Range located in northern Colorado, a short grass steppe ecosystem that is the NEON Domain 10 core site. LAI was measured with a LI-COR 2200 Plant Canopy Analyzer. The layout of the sampling design included four, 300 meter transects, with clip harvests plots spaced every 50m, and LAI sub-transects spaced every 10m. LAI was measured at four points along 6m sub-transects running perpendicular to the 300m transect. Clip harvest plots were co-located 4m from corresponding LAI transects, and had dimensions of 0.1m by 2m. We conducted regression analyses with LAI and clip harvest data to determine whether LAI can be used as a suitable proxy for aboveground standing biomass. We also compared optimal sample sizes derived from LAI data, and clip-harvest data from two different size clip harvest areas (0.1m by 1m vs. 0.1m by 2m). Sample sizes were calculated in order to estimate the mean to within a standardized level of uncertainty that will be used to guide sampling effort across all vegetation types (i.e. estimated within × 10% with 95% confidence). Finally, we employed a Semivariogram approach to determine optimal sample size and spacing.

Reproducibility of preclinical animal research improves with heterogeneity of study samples

PubMed Central

Vogt, Lucile; Sena, Emily S.; Würbel, Hanno

2018-01-01

Single-laboratory studies conducted under highly standardized conditions are the gold standard in preclinical animal research. Using simulations based on 440 preclinical studies across 13 different interventions in animal models of stroke, myocardial infarction, and breast cancer, we compared the accuracy of effect size estimates between single-laboratory and multi-laboratory study designs. Single-laboratory studies generally failed to predict effect size accurately, and larger sample sizes rendered effect size estimates even less accurate. By contrast, multi-laboratory designs including as few as 2 to 4 laboratories increased coverage probability by up to 42 percentage points without a need for larger sample sizes. These findings demonstrate that within-study standardization is a major cause of poor reproducibility. More representative study samples are required to improve the external validity and reproducibility of preclinical animal research and to prevent wasting animals and resources for inconclusive research. PMID:29470495

Regression modeling of particle size distributions in urban storm water: advancements through improved sample collection methods

USGS Publications Warehouse

Fienen, Michael N.; Selbig, William R.

2012-01-01

A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.

An empirical analysis of the quantitative effect of data when fitting quadratic and cubic polynomials

NASA Technical Reports Server (NTRS)

Canavos, G. C.

1974-01-01

A study is made of the extent to which the size of the sample affects the accuracy of a quadratic or a cubic polynomial approximation of an experimentally observed quantity, and the trend with regard to improvement in the accuracy of the approximation as a function of sample size is established. The task is made possible through a simulated analysis carried out by the Monte Carlo method in which data are simulated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to either quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sizes and diminishes drastically for moderate and large amounts of experimental data.

Simulation of Particle Size Effect on Dynamic Properties and Fracture of PTFE-W-Al Composites

NASA Astrophysics Data System (ADS)

Herbold, Eric; Cai, Jing; Benson, David; Nesterenko, Vitali

2007-06-01

Recent investigations of the dynamic compressive strength of cold isostatically pressed (CIP) composites of polytetrafluoroethylene (PTFE), tungsten and aluminum powders show significant differences depending on the size of metallic particles. PTFE and aluminum mixtures are known to be energetic under dynamic and thermal loading. The addition of tungsten increases density and overall strength of the sample. Multi-material Eulerian and arbitrary Lagrangian-Eulerian methods were used for the investigation due to the complexity of the microstructure, relatively large deformations and the ability to handle the formation of free surfaces in a natural manner. The calculations indicate that the observed dependence of sample strength on particle size is due to the formation of force chains under dynamic loading in samples with small particle sizes even at larger porosity in comparison with samples with large grain size and larger density.

A simple approach to power and sample size calculations in logistic regression and Cox regression models.

PubMed

Vaeth, Michael; Skovlund, Eva

2004-06-15

For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

Validation of fixed sample size plans for monitoring lepidopteran pests of Brassica oleracea crops in North Korea.

PubMed

Hamilton, A J; Waters, E K; Kim, H J; Pak, W S; Furlong, M J

2009-06-01

The combined action of two lepidoteran pests, Plutella xylostella L. (Plutellidae) and Pieris rapae L. (Pieridae),causes significant yield losses in cabbage (Brassica oleracea variety capitata) crops in the Democratic People's Republic of Korea. Integrated pest management (IPM) strategies for these cropping systems are in their infancy, and sampling plans have not yet been developed. We used statistical resampling to assess the performance of fixed sample size plans (ranging from 10 to 50 plants). First, the precision (D = SE/mean) of the plans in estimating the population mean was assessed. There was substantial variation in achieved D for all sample sizes, and sample sizes of at least 20 and 45 plants were required to achieve the acceptable precision level of D < or = 0.3 at least 50 and 75% of the time, respectively. Second, the performance of the plans in classifying the population density relative to an economic threshold (ET) was assessed. To account for the different damage potentials of the two species the ETs were defined in terms of standard insects (SIs), where 1 SI = 1 P. rapae = 5 P. xylostella larvae. The plans were implemented using different economic thresholds (ETs) for the three growth stages of the crop: precupping (1 SI/plant), cupping (0.5 SI/plant), and heading (4 SI/plant). Improvement in the classification certainty with increasing sample sizes could be seen through the increasing steepness of operating characteristic curves. Rather than prescribe a particular plan, we suggest that the results of these analyses be used to inform practitioners of the relative merits of the different sample sizes.

A comparative study of the physical properties of Cu-Zn ferrites annealed under different atmospheres and temperatures: Magnetic enhancement of Cu0.5Zn0.5Fe2O4 nanoparticles by a reducing atmosphere

NASA Astrophysics Data System (ADS)

Gholizadeh, Ahmad

2018-04-01

In the present work, the influence of different sintering atmospheres and temperatures on physical properties of the Cu0.5Zn0.5Fe2O4 nanoparticles including the redistribution of Zn2+ and Fe3+ ions, the oxidation of Fe atoms in the lattice, crystallite sizes, IR bands, saturation magnetization and magnetic core sizes have been investigated. The fitting of XRD patterns by using Fullprof program and also FT-IR measurement show the formation of a cubic structure with no presence of impurity phase for all the samples. The unit cell parameter of the samples sintered at the air- and inert-ambient atmospheres trend to decrease with sintering temperature, but for the samples sintered under carbon monoxide-ambient atmosphere increase. The magnetization curves versus the applied magnetic field, indicate different behaviour for the samples sintered at 700 °C with the respect to the samples sintered at 300 °C. Also, the saturation magnetization increases with the sintering temperature and reach a maximum 61.68 emu/g in the sample sintered under reducing atmosphere at 600 °C. The magnetic particle size distributions of samples have been calculated by fitting the M-H curves with the size distributed Langevin function. The results obtained from the XRD and FTIR measurements suggest that the magnetic core size has the dominant effect in variation of the saturation magnetization of the samples.

A novel, efficient method for estimating the prevalence of acute malnutrition in resource-constrained and crisis-affected settings: A simulation study.

PubMed

Frison, Severine; Kerac, Marko; Checchi, Francesco; Nicholas, Jennifer

2017-01-01

The assessment of the prevalence of acute malnutrition in children under five is widely used for the detection of emergencies, planning interventions, advocacy, and monitoring and evaluation. This study examined PROBIT Methods which convert parameters (mean and standard deviation (SD)) of a normally distributed variable to a cumulative probability below any cut-off to estimate acute malnutrition in children under five using Middle-Upper Arm Circumference (MUAC). We assessed the performance of: PROBIT Method I, with mean MUAC from the survey sample and MUAC SD from a database of previous surveys; and PROBIT Method II, with mean and SD of MUAC observed in the survey sample. Specifically, we generated sub-samples from 852 survey datasets, simulating 100 surveys for eight sample sizes. Overall the methods were tested on 681 600 simulated surveys. PROBIT methods relying on sample sizes as small as 50 had better performance than the classic method for estimating and classifying the prevalence of acute malnutrition. They had better precision in the estimation of acute malnutrition for all sample sizes and better coverage for smaller sample sizes, while having relatively little bias. They classified situations accurately for a threshold of 5% acute malnutrition. Both PROBIT methods had similar outcomes. PROBIT Methods have a clear advantage in the assessment of acute malnutrition prevalence based on MUAC, compared to the classic method. Their use would require much lower sample sizes, thus enable great time and resource savings and permit timely and/or locally relevant prevalence estimates of acute malnutrition for a swift and well-targeted response.

Sampling design and required sample size for evaluating contamination levels of 137Cs in Japanese fir needles in a mixed deciduous forest stand in Fukushima, Japan.

PubMed

Oba, Yurika; Yamada, Toshihiro

2017-05-01

We estimated the sample size (the number of samples) required to evaluate the concentration of radiocesium ( 137 Cs) in Japanese fir (Abies firma Sieb. & Zucc.), 5 years after the outbreak of the Fukushima Daiichi Nuclear Power Plant accident. We investigated the spatial structure of the contamination levels in this species growing in a mixed deciduous broadleaf and evergreen coniferous forest stand. We sampled 40 saplings with a tree height of 150 cm-250 cm in a Fukushima forest community. The results showed that: (1) there was no correlation between the 137 Cs concentration in needles and soil, and (2) the difference in the spatial distribution pattern of 137 Cs concentration between needles and soil suggest that the contribution of root uptake to 137 Cs in new needles of this species may be minor in the 5 years after the radionuclides were released into the atmosphere. The concentration of 137 Cs in needles showed a strong positive spatial autocorrelation in the distance class from 0 to 2.5 m, suggesting that the statistical analysis of data should consider spatial autocorrelation in the case of an assessment of the radioactive contamination of forest trees. According to our sample size analysis, a sample size of seven trees was required to determine the mean contamination level within an error in the means of no more than 10%. This required sample size may be feasible for most sites. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fabrication and Characterization of Surrogate Glasses Aimed to Validate Nuclear Forensic Techniques

DTIC Science & Technology

2017-12-01

sample is processed while submerged and produces fine sized particles the exposure levels and risk of contamination from the samples is also greatly...induced the partial collapses of the xerogel network strengthened the network while the sample sizes were reduced [22], [26]. As a result the wt...inhomogeneous, making it difficult to clearly determine which features were present in the sample before LDHP and which were caused by it. In this study

Effect of capping and particle size on Raman laser-induced degradation of {gamma}-Fe{sub 2}O{sub 3} nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Varadwaj, K.S.K.; Panigrahi, M.K.; Ghose, J.

2004-11-01

Diol capped {gamma}-Fe{sub 2}O{sub 3} nanoparticles are prepared from ferric nitrate by refluxing in 1,4-butanediol (9.5nm) and 1,5-pentanediol (15nm) and uncapped particles are prepared by refluxing in 1,2-propanediol followed by sintering the alkoxide formed. X-ray diffraction (XRD) shows that all the samples have the spinel phase. Raman spectroscopy shows that the samples prepared in 1,4-butanediol and 1,5-pentanediol and 1,2-propanediol (sintered at 573 and 673K) are {gamma}-Fe{sub 2}O{sub 3} and the 773K-sintered sample is Fe{sub 3}O{sub 4}. Raman laser studies carried out at various laser powers show that all the samples undergo laser-induced degradation to {alpha}-Fe{sub 2}O{sub 3} at higher lasermore » power. The capped samples are however, found more stable to degradation than the uncapped samples. The stability of {gamma}-Fe{sub 2}O{sub 3} sample with large particle size (15.4nm) is more than the sample with small particle size (10.2nm). Fe{sub 3}O{sub 4} having a particle size of 48nm is however less stable than the smaller {gamma}-Fe{sub 2}O{sub 3} nanoparticles.« less

Analyses of sweep-up, ejecta, and fallback material from the 4250 metric ton high explosive test ''MISTY PICTURE'

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wohletz, K.H.; Raymond, R. Jr.; Rawson, G.

1988-01-01

The MISTY PICTURE surface burst was detonated at the White Sands Missle range in May of 1987. The Los Alamos National Laboratory dust characterization program was expanded to help correlate and interrelate aspects of the overall MISTY PICTURE dust and ejecta characterization program. Pre-shot sampling of the test bed included composite samples from 15 to 75 m distance from Surface Ground Zero (SGZ) representing depths down to 2.5 m, interval samples from 15 to 25 m from SGZ representing depths down to 3m, and samples of surface material (top 0.5 cm) out to distances of 190 m from SGZ. Sweep-upmore » samples were collected in GREG/SNOB gages located within the DPR. All samples were dry-sieved between 8.0 mm and 0.045 mm (16 size fractures); selected samples were analyzed for fines by a contrifugal settling technique. The size distributions were analyzed using spectral decomposition based upon a sequential fragmentation model. Results suggest that the same particle size subpopulations are present in the ejecta, fallout, and sweep-up samples as are present in the pre-shot test bed. The particle size distribution in post-shot environments apparently can be modelled taking into account heterogeneities in the pre-shot test bed and dominant wind direction during and following the shot. 13 refs., 12 figs., 2 tabs.« less

Modeling ultrasound propagation through material of increasing geometrical complexity.

PubMed

Odabaee, Maryam; Odabaee, Mostafa; Pelekanos, Matthew; Leinenga, Gerhard; Götz, Jürgen

2018-06-01

Ultrasound is increasingly being recognized as a neuromodulatory and therapeutic tool, inducing a broad range of bio-effects in the tissue of experimental animals and humans. To achieve these effects in a predictable manner in the human brain, the thick cancellous skull presents a problem, causing attenuation. In order to overcome this challenge, as a first step, the acoustic properties of a set of simple bone-modeling resin samples that displayed an increasing geometrical complexity (increasing step sizes) were analyzed. Using two Non-Destructive Testing (NDT) transducers, we found that Wiener deconvolution predicted the Ultrasound Acoustic Response (UAR) and attenuation caused by the samples. However, whereas the UAR of samples with step sizes larger than the wavelength could be accurately estimated, the prediction was not accurate when the sample had a smaller step size. Furthermore, a Finite Element Analysis (FEA) performed in ANSYS determined that the scattering and refraction of sound waves was significantly higher in complex samples with smaller step sizes compared to simple samples with a larger step size. Together, this reveals an interaction of frequency and geometrical complexity in predicting the UAR and attenuation. These findings could in future be applied to poro-visco-elastic materials that better model the human skull. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Investigation of specimen size effects by in-situ microcompression of equal channel angular pressed copper

DOE Office of Scientific and Technical Information (OSTI.GOV)

Howard, C.; Frazer, D.; Lupinacci, A.

Here, micropillar compression testing was implemented on Equal Channel Angular Pressed copper samples ranging from 200 nm to 10 µm in side length in order to measure the mechanical properties yield strength, first load drop during plastic deformation at which there was a subsequent stress decrease with increasing strain, work hardening, and strain hardening exponent. Several micropillars containing multiple grains were investigated in a 200 nm grain sample. The effective pillar diameter to grain size ratios, D/d, were measured to be between 1.9 and 27.2. Specimens having D/d ratios between 0.2 and 5 were investigated in a second sample thatmore » was annealed at 200 °C for 2 h with an average grain size of 1.3 µm. No yield strength or elastic modulus size effects were observed in specimens in the 200 nm grain size sample. However work hardening increases with a decrease in critical ratios and first stress drops occur at much lower stresses for specimens with D/d ratios less than 5. For comparison, bulk tensile testing of both samples was performed, and the yield strength values of all micropillar compression tests for the 200 nm grained sample are in good agreement with the yield strength values of the tensile tests.« less

Investigation of specimen size effects by in-situ microcompression of equal channel angular pressed copper

DOE PAGES

Howard, C.; Frazer, D.; Lupinacci, A.; ...

2015-09-30

Here, micropillar compression testing was implemented on Equal Channel Angular Pressed copper samples ranging from 200 nm to 10 µm in side length in order to measure the mechanical properties yield strength, first load drop during plastic deformation at which there was a subsequent stress decrease with increasing strain, work hardening, and strain hardening exponent. Several micropillars containing multiple grains were investigated in a 200 nm grain sample. The effective pillar diameter to grain size ratios, D/d, were measured to be between 1.9 and 27.2. Specimens having D/d ratios between 0.2 and 5 were investigated in a second sample thatmore » was annealed at 200 °C for 2 h with an average grain size of 1.3 µm. No yield strength or elastic modulus size effects were observed in specimens in the 200 nm grain size sample. However work hardening increases with a decrease in critical ratios and first stress drops occur at much lower stresses for specimens with D/d ratios less than 5. For comparison, bulk tensile testing of both samples was performed, and the yield strength values of all micropillar compression tests for the 200 nm grained sample are in good agreement with the yield strength values of the tensile tests.« less

Estimating numbers of females with cubs-of-the-year in the Yellowstone grizzly bear population

USGS Publications Warehouse

Keating, K.A.; Schwartz, C.C.; Haroldson, M.A.; Moody, D.

2001-01-01

For grizzly bears (Ursus arctos horribilis) in the Greater Yellowstone Ecosystem (GYE), minimum population size and allowable numbers of human-caused mortalities have been calculated as a function of the number of unique females with cubs-of-the-year (FCUB) seen during a 3- year period. This approach underestimates the total number of FCUB, thereby biasing estimates of population size and sustainable mortality. Also, it does not permit calculation of valid confidence bounds. Many statistical methods can resolve or mitigate these problems, but there is no universal best method. Instead, relative performances of different methods can vary with population size, sample size, and degree of heterogeneity among sighting probabilities for individual animals. We compared 7 nonparametric estimators, using Monte Carlo techniques to assess performances over the range of sampling conditions deemed plausible for the Yellowstone population. Our goal was to estimate the number of FCUB present in the population each year. Our evaluation differed from previous comparisons of such estimators by including sample coverage methods and by treating individual sightings, rather than sample periods, as the sample unit. Consequently, our conclusions also differ from earlier studies. Recommendations regarding estimators and necessary sample sizes are presented, together with estimates of annual numbers of FCUB in the Yellowstone population with bootstrap confidence bounds.

Rapid detection of soils contaminated with heavy metals and oils by laser induced breakdown spectroscopy (LIBS).

PubMed

Kim, Gibaek; Kwak, Jihyun; Kim, Ki-Rak; Lee, Heesung; Kim, Kyoung-Woong; Yang, Hyeon; Park, Kihong

2013-12-15

A laser induced breakdown spectroscopy (LIBS) coupled with the chemometric method was applied to rapidly discriminate between soils contaminated with heavy metals or oils and clean soils. The effects of the water contents and grain sizes of soil samples on LIBS emissions were also investigated. The LIBS emission lines decreased by 59-75% when the water content increased from 1.2% to 7.8%, and soil samples with a grain size of 75 μm displayed higher LIBS emission lines with lower relative standard deviations than those with a 2mm grain size. The water content was found to have a more pronounced effect on the LIBS emission lines than the grain size. Pelletizing and sieving were conducted for all samples collected from abandoned mining areas and military camp to have similar water contents and grain sizes before being analyzed by the LIBS with the chemometric analysis. The data show that three types of soil samples were clearly discerned by using the first three principal components from the spectral data of soil samples. A blind test was conducted with a 100% correction rate for soil samples contaminated with heavy metals and oil residues. Copyright © 2013 Elsevier B.V. All rights reserved.

Atomistic origin of size effects in fatigue behavior of metallic glasses

NASA Astrophysics Data System (ADS)

Sha, Zhendong; Wong, Wei Hin; Pei, Qingxiang; Branicio, Paulo Sergio; Liu, Zishun; Wang, Tiejun; Guo, Tianfu; Gao, Huajian

2017-07-01

While many experiments and simulations on metallic glasses (MGs) have focused on their tensile ductility under monotonic loading, the fatigue mechanisms of MGs under cyclic loading still remain largely elusive. Here we perform molecular dynamics (MD) and finite element simulations of tension-compression fatigue tests in MGs to elucidate their fatigue mechanisms with focus on the sample size effect. Shear band (SB) thickening is found to be the inherent fatigue mechanism for nanoscale MGs. The difference in fatigue mechanisms between macroscopic and nanoscale MGs originates from whether the SB forms partially or fully through the cross-section of the specimen. Furthermore, a qualitative investigation of the sample size effect suggests that small sample size increases the fatigue life while large sample size promotes cyclic softening and necking. Our observations on the size-dependent fatigue behavior can be rationalized by the Gurson model and the concept of surface tension of the nanovoids. The present study sheds light on the fatigue mechanisms of MGs and can be useful in interpreting previous experimental results.

Size-segregated sugar composition of transported dust aerosols from Middle-East over Delhi during March 2012

NASA Astrophysics Data System (ADS)

Kumar, S.; Aggarwal, S. G.; Fu, P. Q.; Kang, M.; Sarangi, B.; Sinha, D.; Kotnala, R. K.

2017-06-01

During March 20-22, 2012 Delhi experienced a massive dust-storm which originated in Middle-East. Size segregated sampling of these dust aerosols was performed using a nine staged Andersen sampler (5 sets of samples were collected including before dust-storm (BDS)), dust-storm day 1 to 3 (DS1 to DS3) and after dust storm (ADS). Sugars (mono and disaccharides, sugar-alcohols and anhydro-sugars) were determined using GC-MS technique. It was observed that on the onset of dust-storm, total suspended particulate matter (TSPM, sum of all stages) concentration in DS1 sample increased by > 2.5 folds compared to that of BDS samples. Interestingly, fine particulate matter (sum of stages with cutoff size < 2.1 μm) loading in DS1 also increased by > 2.5 folds as compared to that of BDS samples. Sugars analyzed in DS1 coarse mode (sum of stages with cutoff size > 2.1 μm) samples showed a considerable increase ( 1.7-2.8 folds) compared to that of other samples. It was further observed that mono-saccharides, disaccharides and sugar-alcohols concentrations were enhanced in giant (> 9.0 μm) particles in DS1 samples as compared to other samples. On the other hand, anhydro-sugars comprised 13-27% of sugars in coarse mode particles and were mostly found in fine mode constituting 66-85% of sugars in all the sample types. Trehalose showed an enhanced ( 2-4 folds) concentration in DS1 aerosol samples in both coarse (62.80 ng/m3) and fine (8.57 ng/m3) mode. This increase in Trehalose content in both coarse and fine mode suggests their origin to the transported desert dust and supports their candidature as an organic tracer for desert dust entrainments. Further, levoglucosan to mannosan (L/M) ratios which have been used to predict the type of biomass burning influences on aerosols are found to be size dependent in these samples. These ratios are higher for fine mode particles, hence should be used with caution while interpreting the sources using this tool.

Accounting for treatment by center interaction in sample size determinations and the use of surrogate outcomes in the pessary for the prevention of preterm birth trial: a simulation study.

PubMed

Willan, Andrew R

2016-07-05

The Pessary for the Prevention of Preterm Birth Study (PS3) is an international, multicenter, randomized clinical trial designed to examine the effectiveness of the Arabin pessary in preventing preterm birth in pregnant women with a short cervix. During the design of the study two methodological issues regarding power and sample size were raised. Since treatment in the Standard Arm will vary between centers, it is anticipated that so too will the probability of preterm birth in that arm. This will likely result in a treatment by center interaction, and the issue of how this will affect the sample size requirements was raised. The sample size requirements to examine the effect of the pessary on the baby's clinical outcome was prohibitively high, so the second issue is how best to examine the effect on clinical outcome. The approaches taken to address these issues are presented. Simulation and sensitivity analysis were used to address the sample size issue. The probability of preterm birth in the Standard Arm was assumed to vary between centers following a Beta distribution with a mean of 0.3 and a coefficient of variation of 0.3. To address the second issue a Bayesian decision model is proposed that combines the information regarding the between-treatment difference in the probability of preterm birth from PS3 with the data from the Multiple Courses of Antenatal Corticosteroids for Preterm Birth Study that relate preterm birth and perinatal mortality/morbidity. The approach provides a between-treatment comparison with respect to the probability of a bad clinical outcome. The performance of the approach was assessed using simulation and sensitivity analysis. Accounting for a possible treatment by center interaction increased the sample size from 540 to 700 patients per arm for the base case. The sample size requirements increase with the coefficient of variation and decrease with the number of centers. Under the same assumptions used for determining the sample size requirements, the simulated mean probability that pessary reduces the risk of perinatal mortality/morbidity is 0.98. The simulated mean decreased with coefficient of variation and increased with the number of clinical sites. Employing simulation and sensitivity analysis is a useful approach for determining sample size requirements while accounting for the additional uncertainty due to a treatment by center interaction. Using a surrogate outcome in conjunction with a Bayesian decision model is an efficient way to compare important clinical outcomes in a randomized clinical trial in situations where the direct approach requires a prohibitively high sample size.

Evaluation of species richness estimators based on quantitative performance measures and sensitivity to patchiness and sample grain size

NASA Astrophysics Data System (ADS)

Willie, Jacob; Petre, Charles-Albert; Tagg, Nikki; Lens, Luc

2012-11-01

Data from forest herbaceous plants in a site of known species richness in Cameroon were used to test the performance of rarefaction and eight species richness estimators (ACE, ICE, Chao1, Chao2, Jack1, Jack2, Bootstrap and MM). Bias, accuracy, precision and sensitivity to patchiness and sample grain size were the evaluation criteria. An evaluation of the effects of sampling effort and patchiness on diversity estimation is also provided. Stems were identified and counted in linear series of 1-m2 contiguous square plots distributed in six habitat types. Initially, 500 plots were sampled in each habitat type. The sampling process was monitored using rarefaction and a set of richness estimator curves. Curves from the first dataset suggested adequate sampling in riparian forest only. Additional plots ranging from 523 to 2143 were subsequently added in the undersampled habitats until most of the curves stabilized. Jack1 and ICE, the non-parametric richness estimators, performed better, being more accurate and less sensitive to patchiness and sample grain size, and significantly reducing biases that could not be detected by rarefaction and other estimators. This study confirms the usefulness of non-parametric incidence-based estimators, and recommends Jack1 or ICE alongside rarefaction while describing taxon richness and comparing results across areas sampled using similar or different grain sizes. As patchiness varied across habitat types, accurate estimations of diversity did not require the same number of plots. The number of samples needed to fully capture diversity is not necessarily the same across habitats, and can only be known when taxon sampling curves have indicated adequate sampling. Differences in observed species richness between habitats were generally due to differences in patchiness, except between two habitats where they resulted from differences in abundance. We suggest that communities should first be sampled thoroughly using appropriate taxon sampling curves before explaining differences in diversity.

Small-Sample DIF Estimation Using SIBTEST, Cochran's Z, and Log-Linear Smoothing

ERIC Educational Resources Information Center

Lei, Pui-Wa; Li, Hongli

2013-01-01

Minimum sample sizes of about 200 to 250 per group are often recommended for differential item functioning (DIF) analyses. However, there are times when sample sizes for one or both groups of interest are smaller than 200 due to practical constraints. This study attempts to examine the performance of Simultaneous Item Bias Test (SIBTEST),…

40 CFR 761.355 - Third level of sample selection.

Code of Federal Regulations, 2012 CFR

2012-07-01

... of sample selection further reduces the size of the subsample to 100 grams which is suitable for the... procedures in § 761.353 of this part into 100 gram portions. (b) Use a random number generator or random number table to select one 100 gram size portion as a sample for a procedure used to simulate leachate...

40 CFR 761.355 - Third level of sample selection.

Code of Federal Regulations, 2011 CFR

2011-07-01

... of sample selection further reduces the size of the subsample to 100 grams which is suitable for the... procedures in § 761.353 of this part into 100 gram portions. (b) Use a random number generator or random number table to select one 100 gram size portion as a sample for a procedure used to simulate leachate...

40 CFR 761.355 - Third level of sample selection.

Code of Federal Regulations, 2013 CFR

2013-07-01

... of sample selection further reduces the size of the subsample to 100 grams which is suitable for the... procedures in § 761.353 of this part into 100 gram portions. (b) Use a random number generator or random number table to select one 100 gram size portion as a sample for a procedure used to simulate leachate...

40 CFR 761.355 - Third level of sample selection.

Code of Federal Regulations, 2010 CFR

2010-07-01

... of sample selection further reduces the size of the subsample to 100 grams which is suitable for the... procedures in § 761.353 of this part into 100 gram portions. (b) Use a random number generator or random number table to select one 100 gram size portion as a sample for a procedure used to simulate leachate...

40 CFR 761.355 - Third level of sample selection.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of sample selection further reduces the size of the subsample to 100 grams which is suitable for the... procedures in § 761.353 of this part into 100 gram portions. (b) Use a random number generator or random number table to select one 100 gram size portion as a sample for a procedure used to simulate leachate...

Conditional Optimal Design in Three- and Four-Level Experiments

ERIC Educational Resources Information Center

Hedges, Larry V.; Borenstein, Michael

2014-01-01

The precision of estimates of treatment effects in multilevel experiments depends on the sample sizes chosen at each level. It is often desirable to choose sample sizes at each level to obtain the smallest variance for a fixed total cost, that is, to obtain optimal sample allocation. This article extends previous results on optimal allocation to…

Effect of finite sample size on feature selection and classification: a simulation study.

PubMed

Way, Ted W; Sahiner, Berkman; Hadjiiski, Lubomir M; Chan, Heang-Ping

2010-02-01

The small number of samples available for training and testing is often the limiting factor in finding the most effective features and designing an optimal computer-aided diagnosis (CAD) system. Training on a limited set of samples introduces bias and variance in the performance of a CAD system relative to that trained with an infinite sample size. In this work, the authors conducted a simulation study to evaluate the performances of various combinations of classifiers and feature selection techniques and their dependence on the class distribution, dimensionality, and the training sample size. The understanding of these relationships will facilitate development of effective CAD systems under the constraint of limited available samples. Three feature selection techniques, the stepwise feature selection (SFS), sequential floating forward search (SFFS), and principal component analysis (PCA), and two commonly used classifiers, Fisher's linear discriminant analysis (LDA) and support vector machine (SVM), were investigated. Samples were drawn from multidimensional feature spaces of multivariate Gaussian distributions with equal or unequal covariance matrices and unequal means, and with equal covariance matrices and unequal means estimated from a clinical data set. Classifier performance was quantified by the area under the receiver operating characteristic curve Az. The mean Az values obtained by resubstitution and hold-out methods were evaluated for training sample sizes ranging from 15 to 100 per class. The number of simulated features available for selection was chosen to be 50, 100, and 200. It was found that the relative performance of the different combinations of classifier and feature selection method depends on the feature space distributions, the dimensionality, and the available training sample sizes. The LDA and SVM with radial kernel performed similarly for most of the conditions evaluated in this study, although the SVM classifier showed a slightly higher hold-out performance than LDA for some conditions and vice versa for other conditions. PCA was comparable to or better than SFS and SFFS for LDA at small samples sizes, but inferior for SVM with polynomial kernel. For the class distributions simulated from clinical data, PCA did not show advantages over the other two feature selection methods. Under this condition, the SVM with radial kernel performed better than the LDA when few training samples were available, while LDA performed better when a large number of training samples were available. None of the investigated feature selection-classifier combinations provided consistently superior performance under the studied conditions for different sample sizes and feature space distributions. In general, the SFFS method was comparable to the SFS method while PCA may have an advantage for Gaussian feature spaces with unequal covariance matrices. The performance of the SVM with radial kernel was better than, or comparable to, that of the SVM with polynomial kernel under most conditions studied.

The large sample size fallacy.

PubMed

Lantz, Björn

2013-06-01

Significance in the statistical sense has little to do with significance in the common practical sense. Statistical significance is a necessary but not a sufficient condition for practical significance. Hence, results that are extremely statistically significant may be highly nonsignificant in practice. The degree of practical significance is generally determined by the size of the observed effect, not the p-value. The results of studies based on large samples are often characterized by extreme statistical significance despite small or even trivial effect sizes. Interpreting such results as significant in practice without further analysis is referred to as the large sample size fallacy in this article. The aim of this article is to explore the relevance of the large sample size fallacy in contemporary nursing research. Relatively few nursing articles display explicit measures of observed effect sizes or include a qualitative discussion of observed effect sizes. Statistical significance is often treated as an end in itself. Effect sizes should generally be calculated and presented along with p-values for statistically significant results, and observed effect sizes should be discussed qualitatively through direct and explicit comparisons with the effects in related literature. © 2012 Nordic College of Caring Science.

Grays Harbor and Chehalis River Improvements to Navigation Environmental Studies. Grays Harbor Ocean Disposal Study. Literature Review and Preliminary Benthic Sampling,

DTIC Science & Technology

1980-05-01

transects extending approximately 16 kilometers from the mouth of Grays Harbor. Sub- samples were taken for grain size analysis and wood content. The...samples were thert was".d on a 1.0 mm screen to separate benthic organisms from non-living materials. Consideration of the grain size analysis ...Nutrients 17 B. Field Study 18 Methods 18 Grain Size Analysis 18 Wood Analysis 21 Wood Fragments 21 Sediment Types 21 Discussion 24 IV. BIOLOGICAL

Particle size of sediments collected from the bed of the Amazon River and its tributaries in May and June 1977

USGS Publications Warehouse

Nordin, Carl F.; Meade, R.H.; Curtis, W.F.; Bosio, N.J.; Delaney, B.M.

1979-01-01

One-hundred-eight samples of bed material were collected from the Amazon River and its major tributaries between Belem, Brazil , and Iquitos, Peru. Samples were taken with a standard BM-54 sampler or with pipe dredges from May 18 to June 5, 1977. Most of the samples have median diameters in the size range of fine to medium sand and contain small percentages of fine gravel. Complete size distributions are tabulated. (Woodard-USGS)

Particle size of sediments collected from the bed of the Amazon River and its tributaries in June and July 1976

USGS Publications Warehouse

Nordin, Carl F.; Meade, R.H.; Mahoney, H.A.; Delany, B.M.

1977-01-01

Sixty-five samples of bed material were collected from the Amazon River and its major tributaries between Belem, Brazil, and Iquitos, Peru. Samples were taken with a standard BM-54 sampler, a pipe dredge, or a Helley-Smith bedload sampler. Most of the samples have median diameters in the size range of fine to medium sand and contain small percentages of fine gravel. Complete size distributions are tabulated.

Sample Size Calculations for Precise Interval Estimation of the Eta-Squared Effect Size

ERIC Educational Resources Information Center

Shieh, Gwowen

2015-01-01

Analysis of variance is one of the most frequently used statistical analyses in the behavioral, educational, and social sciences, and special attention has been paid to the selection and use of an appropriate effect size measure of association in analysis of variance. This article presents the sample size procedures for precise interval estimation…

Measures of precision for dissimilarity-based multivariate analysis of ecological communities.

PubMed

Anderson, Marti J; Santana-Garcon, Julia

2015-01-01

Ecological studies require key decisions regarding the appropriate size and number of sampling units. No methods currently exist to measure precision for multivariate assemblage data when dissimilarity-based analyses are intended to follow. Here, we propose a pseudo multivariate dissimilarity-based standard error (MultSE) as a useful quantity for assessing sample-size adequacy in studies of ecological communities. Based on sums of squared dissimilarities, MultSE measures variability in the position of the centroid in the space of a chosen dissimilarity measure under repeated sampling for a given sample size. We describe a novel double resampling method to quantify uncertainty in MultSE values with increasing sample size. For more complex designs, values of MultSE can be calculated from the pseudo residual mean square of a permanova model, with the double resampling done within appropriate cells in the design. R code functions for implementing these techniques, along with ecological examples, are provided. © 2014 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

Aerosol mobility size spectrometer

DOEpatents

Wang, Jian; Kulkarni, Pramod

2007-11-20

A device for measuring aerosol size distribution within a sample containing aerosol particles. The device generally includes a spectrometer housing defining an interior chamber and a camera for recording aerosol size streams exiting the chamber. The housing includes an inlet for introducing a flow medium into the chamber in a flow direction, an aerosol injection port adjacent the inlet for introducing a charged aerosol sample into the chamber, a separation section for applying an electric field to the aerosol sample across the flow direction and an outlet opposite the inlet. In the separation section, the aerosol sample becomes entrained in the flow medium and the aerosol particles within the aerosol sample are separated by size into a plurality of aerosol flow streams under the influence of the electric field. The camera is disposed adjacent the housing outlet for optically detecting a relative position of at least one aerosol flow stream exiting the outlet and for optically detecting the number of aerosol particles within the at least one aerosol flow stream.

On sample size of the kruskal-wallis test with application to a mouse peritoneal cavity study.

PubMed

Fan, Chunpeng; Zhang, Donghui; Zhang, Cun-Hui

2011-03-01

As the nonparametric generalization of the one-way analysis of variance model, the Kruskal-Wallis test applies when the goal is to test the difference between multiple samples and the underlying population distributions are nonnormal or unknown. Although the Kruskal-Wallis test has been widely used for data analysis, power and sample size methods for this test have been investigated to a much lesser extent. This article proposes new power and sample size calculation methods for the Kruskal-Wallis test based on the pilot study in either a completely nonparametric model or a semiparametric location model. No assumption is made on the shape of the underlying population distributions. Simulation results show that, in terms of sample size calculation for the Kruskal-Wallis test, the proposed methods are more reliable and preferable to some more traditional methods. A mouse peritoneal cavity study is used to demonstrate the application of the methods. © 2010, The International Biometric Society.

Accuracy or precision: Implications of sample design and methodology on abundance estimation

USGS Publications Warehouse

Kowalewski, Lucas K.; Chizinski, Christopher J.; Powell, Larkin A.; Pope, Kevin L.; Pegg, Mark A.

2015-01-01

Sampling by spatially replicated counts (point-count) is an increasingly popular method of estimating population size of organisms. Challenges exist when sampling by point-count method, and it is often impractical to sample entire area of interest and impossible to detect every individual present. Ecologists encounter logistical limitations that force them to sample either few large-sample units or many small sample-units, introducing biases to sample counts. We generated a computer environment and simulated sampling scenarios to test the role of number of samples, sample unit area, number of organisms, and distribution of organisms in the estimation of population sizes using N-mixture models. Many sample units of small area provided estimates that were consistently closer to true abundance than sample scenarios with few sample units of large area. However, sample scenarios with few sample units of large area provided more precise abundance estimates than abundance estimates derived from sample scenarios with many sample units of small area. It is important to consider accuracy and precision of abundance estimates during the sample design process with study goals and objectives fully recognized, although and with consequence, consideration of accuracy and precision of abundance estimates is often an afterthought that occurs during the data analysis process.

Determining the Population Size of Pond Phytoplankton.

ERIC Educational Resources Information Center

Hummer, Paul J.

1980-01-01

Discusses methods for determining the population size of pond phytoplankton, including water sampling techniques, laboratory analysis of samples, and additional studies worthy of investigation in class or as individual projects. (CS)

Unequal cluster sizes in stepped-wedge cluster randomised trials: a systematic review.

PubMed

Kristunas, Caroline; Morris, Tom; Gray, Laura

2017-11-15

To investigate the extent to which cluster sizes vary in stepped-wedge cluster randomised trials (SW-CRT) and whether any variability is accounted for during the sample size calculation and analysis of these trials. Any, not limited to healthcare settings. Any taking part in an SW-CRT published up to March 2016. The primary outcome is the variability in cluster sizes, measured by the coefficient of variation (CV) in cluster size. Secondary outcomes include the difference between the cluster sizes assumed during the sample size calculation and those observed during the trial, any reported variability in cluster sizes and whether the methods of sample size calculation and methods of analysis accounted for any variability in cluster sizes. Of the 101 included SW-CRTs, 48% mentioned that the included clusters were known to vary in size, yet only 13% of these accounted for this during the calculation of the sample size. However, 69% of the trials did use a method of analysis appropriate for when clusters vary in size. Full trial reports were available for 53 trials. The CV was calculated for 23 of these: the median CV was 0.41 (IQR: 0.22-0.52). Actual cluster sizes could be compared with those assumed during the sample size calculation for 14 (26%) of the trial reports; the cluster sizes were between 29% and 480% of that which had been assumed. Cluster sizes often vary in SW-CRTs. Reporting of SW-CRTs also remains suboptimal. The effect of unequal cluster sizes on the statistical power of SW-CRTs needs further exploration and methods appropriate to studies with unequal cluster sizes need to be employed. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Bony pelvic canal size and shape in relation to body proportionality in humans.

PubMed

Kurki, Helen K

2013-05-01

Obstetric selection acts on the female pelvic canal to accommodate the human neonate and contributes to pelvic sexual dimorphism. There is a complex relationship between selection for obstetric sufficiency and for overall body size in humans. The relationship between selective pressures may differ among populations of different body sizes and proportions, as pelvic canal dimensions vary among populations. Size and shape of the pelvic canal in relation to body size and shape were examined using nine skeletal samples (total female n = 57; male n = 84) from diverse geographical regions. Pelvic, vertebral, and lower limb bone measurements were collected. Principal component analyses demonstrate pelvic canal size and shape differences among the samples. Male multivariate variance in pelvic shape is greater than female variance for North and South Africans. High-latitude samples have larger and broader bodies, and pelvic canals of larger size and, among females, relatively broader medio-lateral dimensions relative to low-latitude samples, which tend to display relatively expanded inlet antero-posterior (A-P) and posterior canal dimensions. Differences in canal shape exist among samples that are not associated with latitude or body size, suggesting independence of some canal shape characteristics from body size and shape. The South Africans are distinctive with very narrow bodies and small pelvic inlets relative to an elongated lower canal in A-P and posterior lengths. Variation in pelvic canal geometry among populations is consistent with a high degree of evolvability in the human pelvis. Copyright © 2013 Wiley Periodicals, Inc.

At convenience and systematic random sampling: effects on the prognostic value of nuclear area assessments in breast cancer patients.

PubMed

Jannink, I; Bennen, J N; Blaauw, J; van Diest, P J; Baak, J P

1995-01-01

This study compares the influence of two different nuclear sampling methods on the prognostic value of assessments of mean and standard deviation of nuclear area (MNA, SDNA) in 191 consecutive invasive breast cancer patients with long term follow up. The first sampling method used was 'at convenience' sampling (ACS); the second, systematic random sampling (SRS). Both sampling methods were tested with a sample size of 50 nuclei (ACS-50 and SRS-50). To determine whether, besides the sampling methods, sample size had impact on prognostic value as well, the SRS method was also tested using a sample size of 100 nuclei (SRS-100). SDNA values were systematically lower for ACS, obviously due to (unconsciously) not including small and large nuclei. Testing prognostic value of a series of cut off points, MNA and SDNA values assessed by the SRS method were prognostically significantly stronger than the values obtained by the ACS method. This was confirmed in Cox regression analysis. For the MNA, the Mantel-Cox p-values from SRS-50 and SRS-100 measurements were not significantly different. However, for the SDNA, SRS-100 yielded significantly lower p-values than SRS-50. In conclusion, compared with the 'at convenience' nuclear sampling method, systematic random sampling of nuclei is not only superior with respect to reproducibility of results, but also provides a better prognostic value in patients with invasive breast cancer.

Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river

USGS Publications Warehouse

Smith, D.R.; Rogala, J.T.; Gray, B.R.; Zigler, S.J.; Newton, T.J.

2011-01-01

Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.

Estimation of the bottleneck size in Florida panthers

USGS Publications Warehouse

Culver, M.; Hedrick, P.W.; Murphy, K.; O'Brien, S.; Hornocker, M.G.

2008-01-01

We have estimated the extent of genetic variation in museum (1890s) and contemporary (1980s) samples of Florida panthers Puma concolor coryi for both nuclear loci and mtDNA. The microsatellite heterozygosity in the contemporary sample was only 0.325 that in the museum samples although our sample size and number of loci are limited. Support for this estimate is provided by a sample of 84 microsatellite loci in contemporary Florida panthers and Idaho pumas Puma concolor hippolestes in which the contemporary Florida panther sample had only 0.442 the heterozygosity of Idaho pumas. The estimated diversities in mtDNA in the museum and contemporary samples were 0.600 and 0.000, respectively. Using a population genetics approach, we have estimated that to reduce either the microsatellite heterozygosity or the mtDNA diversity this much (in a period of c. 80years during the 20th century when the numbers were thought to be low) that a very small bottleneck size of c. 2 for several generations and a small effective population size in other generations is necessary. Using demographic data from Yellowstone pumas, we estimated the ratio of effective to census population size to be 0.315. Using this ratio, the census population size in the Florida panthers necessary to explain the loss of microsatellite variation was c .41 for the non-bottleneck generations and 6.2 for the two bottleneck generations. These low bottleneck population sizes and the concomitant reduced effectiveness of selection are probably responsible for the high frequency of several detrimental traits in Florida panthers, namely undescended testicles and poor sperm quality. The recent intensive monitoring both before and after the introduction of Texas pumas in 1995 will make the recovery and genetic restoration of Florida panthers a classic study of an endangered species. Our estimates of the bottleneck size responsible for the loss of genetic variation in the Florida panther completes an unknown aspect of this account. ?? 2008 The Authors. Journal compilation ?? 2008 The Zoological Society of London.

The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

PubMed

Page, G P; Amos, C I; Boerwinkle, E

1998-04-01

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

Ratio of Cut Surface Area to Leaf Sample Volume for Water Potential Measurements by Thermocouple Psychrometers

PubMed Central

Walker, Sue; Oosterhuis, Derrick M.; Wiebe, Herman H.

1984-01-01

Evaporative losses from the cut edge of leaf samples are of considerable importance in measurements of leaf water potential using thermocouple psychrometers. The ratio of cut surface area to leaf sample volume (area to volume ratio) has been used to give an estimate of possible effects of evaporative loss in relation to sample size. A wide range of sample sizes with different area to volume ratios has been used. Our results using Glycine max L. Merr. cv Bragg indicate that leaf samples with area to volume values less than 0.2 square millimeter per cubic millimeter give psychrometric leaf water potential measurements that compare favorably with pressure chamber measurements. PMID:16663578

Effect of sample area and sieve size on benthic macrofaunal community condition assessments in California enclosed bays and estuaries.

PubMed

Hammerstrom, Kamille K; Ranasinghe, J Ananda; Weisberg, Stephen B; Oliver, John S; Fairey, W Russell; Slattery, Peter N; Oakden, James M

2012-10-01

Benthic macrofauna are used extensively for environmental assessment, but the area sampled and sieve sizes used to capture animals often differ among studies. Here, we sampled 80 sites using 3 different sized sampling areas (0.1, 0.05, 0.0071 m(2)) and sieved those sediments through each of 2 screen sizes (0.5, 1 mm) to evaluate their effect on number of individuals, number of species, dominance, nonmetric multidimensional scaling (MDS) ordination, and benthic community condition indices that are used to assess sediment quality in California. Sample area had little effect on abundance but substantially affected numbers of species, which are not easily scaled to a standard area. Sieve size had a substantial effect on both measures, with the 1-mm screen capturing only 74% of the species and 68% of the individuals collected in the 0.5-mm screen. These differences, though, had little effect on the ability to differentiate samples along gradients in ordination space. Benthic indices generally ranked sample condition in the same order regardless of gear, although the absolute scoring of condition was affected by gear type. The largest differences in condition assessment were observed for the 0.0071-m(2) gear. Benthic indices based on numbers of species were more affected than those based on relative abundance, primarily because we were unable to scale species number to a common area as we did for abundance. Copyright © 2010 SETAC.

An alternative method for determining particle-size distribution of forest road aggregate and soil with large-sized particles

Treesearch

Hakjun Rhee; Randy B. Foltz; James L. Fridley; Finn Krogstad; Deborah S. Page-Dumroese

2014-01-01

Measurement of particle-size distribution (PSD) of soil with large-sized particles (e.g., 25.4 mm diameter) requires a large sample and numerous particle-size analyses (PSAs). A new method is needed that would reduce time, effort, and cost for PSAs of the soil and aggregate material with large-sized particles. We evaluated a nested method for sampling and PSA by...

Scaling ice microstructures from the laboratory to nature: cryo-EBSD on large samples.

NASA Astrophysics Data System (ADS)

Prior, David; Craw, Lisa; Kim, Daeyeong; Peyroux, Damian; Qi, Chao; Seidemann, Meike; Tooley, Lauren; Vaughan, Matthew; Wongpan, Pat

2017-04-01

Electron backscatter diffraction (EBSD) has extended significantly our ability to conduct detailed quantitative microstructural investigations of rocks, metals and ceramics. EBSD on ice was first developed in 2004. Techniques have improved significantly in the last decade and EBSD is now becoming more common in the microstructural analysis of ice. This is particularly true for laboratory-deformed ice where, in some cases, the fine grain sizes exclude the possibility of using a thin section of the ice. Having the orientations of all axes (rather than just the c-axis as in an optical method) yields important new information about ice microstructure. It is important to examine natural ice samples in the same way so that we can scale laboratory observations to nature. In the case of ice deformation, higher strain rates are used in the laboratory than those seen in nature. These are achieved by increasing stress and/or temperature and it is important to assess that the microstructures produced in the laboratory are comparable with those observed in nature. Natural ice samples are coarse grained. Glacier and ice sheet ice has a grain size from a few mm up to several cm. Sea and lake ice has grain sizes of a few cm to many metres. Thus extending EBSD analysis to larger sample sizes to include representative microstructures is needed. The chief impediments to working on large ice samples are sample exchange, limitations on stage motion and temperature control. Large ice samples cannot be transferred through a typical commercial cryo-transfer system that limits sample sizes. We transfer through a nitrogen glove box that encloses the main scanning electron microscope (SEM) door. The nitrogen atmosphere prevents the cold stage and the sample from becoming covered in frost. Having a long optimal working distance for EBSD (around 30mm for the Otago cryo-EBSD facility) , by moving the camera away from the pole piece, enables the stage to move without crashing into either the EBSD camera or the SEM pole piece (final lens). In theory a sample up to 100mm perpendicular to the tilt axis by 150mm parallel to the tilt axis can be analysed. In practice, the motion of our stage is restricted to maximum dimensions of 100 by 50mm by a conductive copper braid on our cold stage. Temperature control becomes harder as the samples become larger. If the samples become too warm then they will start to sublime and the quality of EBSD data will reduce. Large samples need to be relatively thin ( 5mm or less) so that conduction of heat to the cold stage is more effective at keeping the surface temperature low. In the Otago facility samples of up to 40mm by 40mm present little problem and can be analysed for several hours without significant sublimation. Larger samples need more care, e.g. fast sample transfer to keep the sample very cold. The largest samples we work on routinely are 40 by 60mm in size. We will show examples of EBSD data from glacial ice and sea ice from Antarctica and from large laboratory ice samples.

In Situ Sampling of Terrestrial Dust Devils and Implications for Mars

NASA Astrophysics Data System (ADS)

Raack, J.; Reiss, D.; Balme, M. R.; Taj-Eddine, K.; Ori, G. G.

2017-09-01

We report on first very detailed in situ samples of the relative dust load and the vertical grain size distribution of terrestrial dust devils sampled during two field campaigns in Morocco and their implications for Mars. Our measurements imply, i.e., a similar internal structure for sampled dust devils, despite their different strenghts and dimensions; an exponential decreasing of particle size with height; and that between 60 and 70% of all lifted particles can go into atmospheric suspension.

Size dependence of magnetorheological properties of cobalt ferrite ferrofluid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Radhika, B.; Sahoo, Rasmita; Srinath, S., E-mail: srinath@uohyd.ac.in

2015-06-24

Cobalt Ferrite nanoparticles were synthesized using co-precipitation method at reaction temperatures of 40°C and 80°C. X-Ray diffraction studies confirm cubic phase formation. The average crystallite sizes were found to be ∼30nm and ∼48nm for 40°C sample and 80°C sample respectively. Magnetic properties measured using vibrating sample magnetometer show higher coercivety and magnetization for sample prepared at 80°C. Magnetorheological properties of CoFe2O4 ferrofluids were measured and studied.

Forestry inventory based on multistage sampling with probability proportional to size

NASA Technical Reports Server (NTRS)

Lee, D. C. L.; Hernandez, P., Jr.; Shimabukuro, Y. E.

1983-01-01

A multistage sampling technique, with probability proportional to size, is developed for a forest volume inventory using remote sensing data. The LANDSAT data, Panchromatic aerial photographs, and field data are collected. Based on age and homogeneity, pine and eucalyptus classes are identified. Selection of tertiary sampling units is made through aerial photographs to minimize field work. The sampling errors for eucalyptus and pine ranged from 8.34 to 21.89 percent and from 7.18 to 8.60 percent, respectively.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach

PubMed Central

Boitard, Simon; Rodríguez, Willy; Jay, Flora; Mona, Stefano; Austerlitz, Frédéric

2016-01-01

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles. PMID:26943927

Setting health research priorities using the CHNRI method: VI. Quantitative properties of human collective opinion

PubMed Central

Yoshida, Sachiyo; Rudan, Igor; Cousens, Simon

2016-01-01

Introduction Crowdsourcing has become an increasingly important tool to address many problems – from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. Methods We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. Results The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14–16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank correlation coefficient = 0.95; IQR 0.94–0.96). Conclusions Our analyses suggest that the collective opinion of an expert group on a large number of research ideas, expressed through categorical variables (Yes/No/Not Sure/Don't know), stabilises relatively quickly in terms of identifying the ideas that have most support. In the exercise we found a high degree of reproducibility of the identified research priorities was achieved with as few as 45–55 experts. PMID:27350874

Setting health research priorities using the CHNRI method: VI. Quantitative properties of human collective opinion.

PubMed

Yoshida, Sachiyo; Rudan, Igor; Cousens, Simon

2016-06-01

Crowdsourcing has become an increasingly important tool to address many problems - from government elections in democracies, stock market prices, to modern online tools such as TripAdvisor or Internet Movie Database (IMDB). The CHNRI method (the acronym for the Child Health and Nutrition Research Initiative) for setting health research priorities has crowdsourcing as the major component, which it uses to generate, assess and prioritize between many competing health research ideas. We conducted a series of analyses using data from a group of 91 scorers to explore the quantitative properties of their collective opinion. We were interested in the stability of their collective opinion as the sample size increases from 15 to 90. From a pool of 91 scorers who took part in a previous CHNRI exercise, we used sampling with replacement to generate multiple random samples of different size. First, for each sample generated, we identified the top 20 ranked research ideas, among 205 that were proposed and scored, and calculated the concordance with the ranking generated by the 91 original scorers. Second, we used rank correlation coefficients to compare the ranks assigned to all 205 proposed research ideas when samples of different size are used. We also analysed the original pool of 91 scorers to to look for evidence of scoring variations based on scorers' characteristics. The sample sizes investigated ranged from 15 to 90. The concordance for the top 20 scored research ideas increased with sample sizes up to about 55 experts. At this point, the median level of concordance stabilized at 15/20 top ranked questions (75%), with the interquartile range also generally stable (14-16). There was little further increase in overlap when the sample size increased from 55 to 90. When analysing the ranking of all 205 ideas, the rank correlation coefficient increased as the sample size increased, with a median correlation of 0.95 reached at the sample size of 45 experts (median of the rank correlation coefficient = 0.95; IQR 0.94-0.96). Our analyses suggest that the collective opinion of an expert group on a large number of research ideas, expressed through categorical variables (Yes/No/Not Sure/Don't know), stabilises relatively quickly in terms of identifying the ideas that have most support. In the exercise we found a high degree of reproducibility of the identified research priorities was achieved with as few as 45-55 experts.

Size selective isocyanate aerosols personal air sampling using porous plastic foams

NASA Astrophysics Data System (ADS)

Khanh Huynh, Cong; Duc, Trinh Vu

2009-02-01

As part of a European project (SMT4-CT96-2137), various European institutions specialized in occupational hygiene (BGIA, HSL, IOM, INRS, IST, Ambiente e Lavoro) have established a program of scientific collaboration to develop one or more prototypes of European personal samplers for the collection of simultaneous three dust fractions: inhalable, thoracic and respirable. These samplers based on existing sampling heads (IOM, GSP and cassettes) use Polyurethane Plastic Foam (PUF) according to their porosity to support sampling and separator size of the particles. In this study, the authors present an original application of size selective personal air sampling using chemical impregnated PUF to perform isocyanate aerosols capturing and derivatizing in industrial spray-painting shops.

Water quality monitoring: A comparative case study of municipal and Curtin Sarawak's lake samples

NASA Astrophysics Data System (ADS)

Anand Kumar, A.; Jaison, J.; Prabakaran, K.; Nagarajan, R.; Chan, Y. S.

2016-03-01

In this study, particle size distribution and zeta potential of the suspended particles in municipal water and lake surface water of Curtin Sarawak's lake were compared and the samples were analysed using dynamic light scattering method. High concentration of suspended particles affects the water quality as well as suppresses the aquatic photosynthetic systems. A new approach has been carried out in the current work to determine the particle size distribution and zeta potential of the suspended particles present in the water samples. The results for the lake samples showed that the particle size ranges from 180nm to 1345nm and the zeta potential values ranges from -8.58 mV to -26.1 mV. High zeta potential value was observed in the surface water samples of Curtin Sarawak's lake compared to the municipal water. The zeta potential values represent that the suspended particles are stable and chances of agglomeration is lower in lake water samples. Moreover, the effects of physico-chemical parameters on zeta potential of the water samples were also discussed.

Application-Specific Graph Sampling for Frequent Subgraph Mining and Community Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purohit, Sumit; Choudhury, Sutanay; Holder, Lawrence B.

Graph mining is an important data analysis methodology, but struggles as the input graph size increases. The scalability and usability challenges posed by such large graphs make it imperative to sample the input graph and reduce its size. The critical challenge in sampling is to identify the appropriate algorithm to insure the resulting analysis does not suffer heavily from the data reduction. Predicting the expected performance degradation for a given graph and sampling algorithm is also useful. In this paper, we present different sampling approaches for graph mining applications such as Frequent Subgrpah Mining (FSM), and Community Detection (CD). Wemore » explore graph metrics such as PageRank, Triangles, and Diversity to sample a graph and conclude that for heterogeneous graphs Triangles and Diversity perform better than degree based metrics. We also present two new sampling variations for targeted graph mining applications. We present empirical results to show that knowledge of the target application, along with input graph properties can be used to select the best sampling algorithm. We also conclude that performance degradation is an abrupt, rather than gradual phenomena, as the sample size decreases. We present the empirical results to show that the performance degradation follows a logistic function.« less

Salmonella enteritidis surveillance by egg immunology: impact of the sampling scheme on the release of contaminated table eggs.

PubMed

Klinkenberg, Don; Thomas, Ekelijn; Artavia, Francisco F Calvo; Bouma, Annemarie

2011-08-01

Design of surveillance programs to detect infections could benefit from more insight into sampling schemes. We address the effect of sampling schemes for Salmonella Enteritidis surveillance in laying hens. Based on experimental estimates for the transmission rate in flocks, and the characteristics of an egg immunological test, we have simulated outbreaks with various sampling schemes, and with the current boot swab program with a 15-week sampling interval. Declaring a flock infected based on a single positive egg was not possible because test specificity was too low. Thus, a threshold number of positive eggs was defined to declare a flock infected, and, for small sample sizes, eggs from previous samplings had to be included in a cumulative sample to guarantee a minimum flock level specificity. Effectiveness of surveillance was measured by the proportion of outbreaks detected, and by the number of contaminated table eggs brought on the market. The boot swab program detected 90% of the outbreaks, with 75% fewer contaminated eggs compared to no surveillance, whereas the baseline egg program (30 eggs each 15 weeks) detected 86%, with 73% fewer contaminated eggs. We conclude that a larger sample size results in more detected outbreaks, whereas a smaller sampling interval decreases the number of contaminated eggs. Decreasing sample size and interval simultaneously reduces the number of contaminated eggs, but not indefinitely: the advantage of more frequent sampling is counterbalanced by the cumulative sample including less recently laid eggs. Apparently, optimizing surveillance has its limits when test specificity is taken into account. © 2011 Society for Risk Analysis.

Preparing rock powder specimens of controlled size distribution

NASA Technical Reports Server (NTRS)

Blum, P.

1968-01-01

Apparatus produces rock powder specimens of the size distribution needed in geological sampling. By cutting grooves in the surface of the rock sample and then by milling these shallow, parallel ridges, the powder specimen is produced. Particle size distribution is controlled by changing the height and width of ridges.

A cautionary note on Bayesian estimation of population size by removal sampling with diffuse priors.

PubMed

Bord, Séverine; Bioche, Christèle; Druilhet, Pierre

2018-05-01

We consider the problem of estimating a population size by removal sampling when the sampling rate is unknown. Bayesian methods are now widespread and allow to include prior knowledge in the analysis. However, we show that Bayes estimates based on default improper priors lead to improper posteriors or infinite estimates. Similarly, weakly informative priors give unstable estimators that are sensitive to the choice of hyperparameters. By examining the likelihood, we show that population size estimates can be stabilized by penalizing small values of the sampling rate or large value of the population size. Based on theoretical results and simulation studies, we propose some recommendations on the choice of the prior. Then, we applied our results to real datasets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of YBCO high temperature superconductor doped with silver nanoparticles and carbon nanotubes using Williamson-Hall and size-strain plot

NASA Astrophysics Data System (ADS)

Dadras, Sedigheh; Davoudiniya, Masoumeh

2018-05-01

This paper sets out to investigate and compare the effects of Ag nanoparticles and carbon nanotubes (CNTs) doping on the mechanical properties of Y1Ba2Cu3O7-δ (YBCO) high temperature superconductor. For this purpose, the pure and doped YBCO samples were synthesized by sol-gel method. The microstructural analysis of the samples is performed using X-ray diffraction (XRD). The crystalline size, lattice strain and stress of the pure and doped YBCO samples were estimated by modified forms of Williamson-Hall analysis (W-H), namely, uniform deformation model (UDM), uniform deformation stress model (UDSM) and the size-strain plot method (SSP). These results show that the crystalline size, lattice strain and stress of the YBCO samples declined by Ag nanoparticles and CNTs doping.

Cryogenic homogenization and sampling of heterogeneous multi-phase feedstock

DOEpatents

Doyle, Glenn Michael; Ideker, Virgene Linda; Siegwarth, James David

2002-01-01

An apparatus and process for producing a homogeneous analytical sample from a heterogenous feedstock by: providing the mixed feedstock, reducing the temperature of the feedstock to a temperature below a critical temperature, reducing the size of the feedstock components, blending the reduced size feedstock to form a homogeneous mixture; and obtaining a representative sample of the homogeneous mixture. The size reduction and blending steps are performed at temperatures below the critical temperature in order to retain organic compounds in the form of solvents, oils, or liquids that may be adsorbed onto or absorbed into the solid components of the mixture, while also improving the efficiency of the size reduction. Preferably, the critical temperature is less than 77 K (-196.degree. C.). Further, with the process of this invention the representative sample may be maintained below the critical temperature until being analyzed.

Simulation on Poisson and negative binomial models of count road accident modeling

NASA Astrophysics Data System (ADS)

Sapuan, M. S.; Razali, A. M.; Zamzuri, Z. H.; Ibrahim, K.

2016-11-01

Accident count data have often been shown to have overdispersion. On the other hand, the data might contain zero count (excess zeros). The simulation study was conducted to create a scenarios which an accident happen in T-junction with the assumption the dependent variables of generated data follows certain distribution namely Poisson and negative binomial distribution with different sample size of n=30 to n=500. The study objective was accomplished by fitting Poisson regression, negative binomial regression and Hurdle negative binomial model to the simulated data. The model validation was compared and the simulation result shows for each different sample size, not all model fit the data nicely even though the data generated from its own distribution especially when the sample size is larger. Furthermore, the larger sample size indicates that more zeros accident count in the dataset.

Simulation of Particle Size Effect on Dynamic Properties and Fracture of PTFE-W-Al Composites

NASA Astrophysics Data System (ADS)

Herbold, E. B.; Cai, J.; Benson, D. J.; Nesterenko, V. F.

2007-12-01

Recent investigations of the dynamic compressive strength of cold isostatically pressed composites of polytetrafluoroethylene (PTFE), tungsten (W) and aluminum (Al) powders show significant differences depending on the size of metallic particles. The addition of W increases the density and changes the overall strength of the sample depending on the size of W particles. To investigate relatively large deformations, multi-material Eulerian and arbitrary Lagrangian-Eulerian methods, which have the ability to efficiently handle the formation of free surfaces, were used. The calculations indicate that the increased sample strength with fine metallic particles is due to the dynamic formation of force chains. This phenomenon occurs for samples with a higher porosity of the PTFE matrix compared to samples with larger particle size of W and a higher density PTFE matrix.

Accounting for missing data in the estimation of contemporary genetic effective population size (N(e) ).

PubMed

Peel, D; Waples, R S; Macbeth, G M; Do, C; Ovenden, J R

2013-03-01

Theoretical models are often applied to population genetic data sets without fully considering the effect of missing data. Researchers can deal with missing data by removing individuals that have failed to yield genotypes and/or by removing loci that have failed to yield allelic determinations, but despite their best efforts, most data sets still contain some missing data. As a consequence, realized sample size differs among loci, and this poses a problem for unbiased methods that must explicitly account for random sampling error. One commonly used solution for the calculation of contemporary effective population size (N(e) ) is to calculate the effective sample size as an unweighted mean or harmonic mean across loci. This is not ideal because it fails to account for the fact that loci with different numbers of alleles have different information content. Here we consider this problem for genetic estimators of contemporary effective population size (N(e) ). To evaluate bias and precision of several statistical approaches for dealing with missing data, we simulated populations with known N(e) and various degrees of missing data. Across all scenarios, one method of correcting for missing data (fixed-inverse variance-weighted harmonic mean) consistently performed the best for both single-sample and two-sample (temporal) methods of estimating N(e) and outperformed some methods currently in widespread use. The approach adopted here may be a starting point to adjust other population genetics methods that include per-locus sample size components. © 2012 Blackwell Publishing Ltd.

Demonstration of Multi- and Single-Reader Sample Size Program for Diagnostic Studies software.

PubMed

Hillis, Stephen L; Schartz, Kevin M

2015-02-01

The recently released software Multi- and Single-Reader Sample Size Sample Size Program for Diagnostic Studies , written by Kevin Schartz and Stephen Hillis, performs sample size computations for diagnostic reader-performance studies. The program computes the sample size needed to detect a specified difference in a reader performance measure between two modalities, when using the analysis methods initially proposed by Dorfman, Berbaum, and Metz (DBM) and Obuchowski and Rockette (OR), and later unified and improved by Hillis and colleagues. A commonly used reader performance measure is the area under the receiver-operating-characteristic curve. The program can be used with typical common reader-performance measures which can be estimated parametrically or nonparametrically. The program has an easy-to-use step-by-step intuitive interface that walks the user through the entry of the needed information. Features of the software include the following: (1) choice of several study designs; (2) choice of inputs obtained from either OR or DBM analyses; (3) choice of three different inference situations: both readers and cases random, readers fixed and cases random, and readers random and cases fixed; (4) choice of two types of hypotheses: equivalence or noninferiority; (6) choice of two output formats: power for specified case and reader sample sizes, or a listing of case-reader combinations that provide a specified power; (7) choice of single or multi-reader analyses; and (8) functionality in Windows, Mac OS, and Linux.

Application of SAXS and SANS in evaluation of porosity, pore size distribution and surface area of coal

USGS Publications Warehouse

Radlinski, A.P.; Mastalerz, Maria; Hinde, A.L.; Hainbuchner, M.; Rauch, H.; Baron, M.; Lin, J.S.; Fan, L.; Thiyagarajan, P.

2004-01-01

This paper discusses the applicability of small angle X-ray scattering (SAXS) and small angle neutron scattering (SANS) techniques for determining the porosity, pore size distribution and internal specific surface area in coals. The method is noninvasive, fast, inexpensive and does not require complex sample preparation. It uses coal grains of about 0.8 mm size mounted in standard pellets as used for petrographic studies. Assuming spherical pore geometry, the scattering data are converted into the pore size distribution in the size range 1 nm (10 A??) to 20 ??m (200,000 A??) in diameter, accounting for both open and closed pores. FTIR as well as SAXS and SANS data for seven samples of oriented whole coals and corresponding pellets with vitrinite reflectance (Ro) values in the range 0.55% to 5.15% are presented and analyzed. Our results demonstrate that pellets adequately represent the average microstructure of coal samples. The scattering data have been used to calculate the maximum surface area available for methane adsorption. Total porosity as percentage of sample volume is calculated and compared with worldwide trends. By demonstrating the applicability of SAXS and SANS techniques to determine the porosity, pore size distribution and surface area in coals, we provide a new and efficient tool, which can be used for any type of coal sample, from a thin slice to a representative sample of a thick seam. ?? 2004 Elsevier B.V. All rights reserved.

Conceptual data sampling for breast cancer histology image classification.

PubMed

Rezk, Eman; Awan, Zainab; Islam, Fahad; Jaoua, Ali; Al Maadeed, Somaya; Zhang, Nan; Das, Gautam; Rajpoot, Nasir

2017-10-01

Data analytics have become increasingly complicated as the amount of data has increased. One technique that is used to enable data analytics in large datasets is data sampling, in which a portion of the data is selected to preserve the data characteristics for use in data analytics. In this paper, we introduce a novel data sampling technique that is rooted in formal concept analysis theory. This technique is used to create samples reliant on the data distribution across a set of binary patterns. The proposed sampling technique is applied in classifying the regions of breast cancer histology images as malignant or benign. The performance of our method is compared to other classical sampling methods. The results indicate that our method is efficient and generates an illustrative sample of small size. It is also competing with other sampling methods in terms of sample size and sample quality represented in classification accuracy and F1 measure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Repopulation of calibrations with samples from the target site: effect of the size of the calibration.

NASA Astrophysics Data System (ADS)

Guerrero, C.; Zornoza, R.; Gómez, I.; Mataix-Solera, J.; Navarro-Pedreño, J.; Mataix-Beneyto, J.; García-Orenes, F.

2009-04-01

Near infrared (NIR) reflectance spectroscopy offers important advantages because is a non-destructive technique, the pre-treatments needed in samples are minimal, and the spectrum of the sample is obtained in less than 1 minute without the needs of chemical reagents. For these reasons, NIR is a fast and cost-effective method. Moreover, NIR allows the analysis of several constituents or parameters simultaneously from the same spectrum once it is obtained. For this, a needed steep is the development of soil spectral libraries (set of samples analysed and scanned) and calibrations (using multivariate techniques). The calibrations should contain the variability of the target site soils in which the calibration is to be used. Many times this premise is not easy to fulfil, especially in libraries recently developed. A classical way to solve this problem is through the repopulation of libraries and the subsequent recalibration of the models. In this work we studied the changes in the accuracy of the predictions as a consequence of the successive addition of samples to repopulation. In general, calibrations with high number of samples and high diversity are desired. But we hypothesized that calibrations with lower quantities of samples (lower size) will absorb more easily the spectral characteristics of the target site. Thus, we suspect that the size of the calibration (model) that will be repopulated could be important. For this reason we also studied this effect in the accuracy of predictions of the repopulated models. In this study we used those spectra of our library which contained data of soil Kjeldahl Nitrogen (NKj) content (near to 1500 samples). First, those spectra from the target site were removed from the spectral library. Then, different quantities of samples of the library were selected (representing the 5, 10, 25, 50, 75 and 100% of the total library). These samples were used to develop calibrations with different sizes (%) of samples. We used partial least squares regression, and leave-one-out cross validation as methods of calibration. Two methods were used to select the different quantities (size of models) of samples: (1) Based on Characteristics of Spectra (BCS), and (2) Based on NKj Values of Samples (BVS). Both methods tried to select representative samples. Each of the calibrations (containing the 5, 10, 25, 50, 75 or 100% of the total samples of the library) was repopulated with samples from the target site and then recalibrated (by leave-one-out cross validation). This procedure was sequential. In each step, 2 samples from the target site were added to the models, and then recalibrated. This process was repeated successively 10 times, being 20 the total number of samples added. A local model was also created with the 20 samples used for repopulation. The repopulated, non-repopulated and local calibrations were used to predict the NKj content in those samples from the target site not included in repopulations. For the measurement of the accuracy of the predictions, the r2, RMSEP and slopes were calculated comparing predicted with analysed NKj values. This scheme was repeated for each of the four target sites studied. In general, scarce differences can be found between results obtained with BCS and BVS models. We observed that the repopulation of models increased the r2 of the predictions in sites 1 and 3. The repopulation caused scarce changes of the r2 of the predictions in sites 2 and 4, maybe due to the high initial values (using non-repopulated models r2 >0.90). As consequence of repopulation, the RMSEP decreased in all the sites except in site 2, where a very low RMESP was obtained before the repopulation (0.4 g×kg-1). The slopes trended to approximate to 1, but this value was reached only in site 4 and after the repopulation with 20 samples. In sites 3 and 4, accurate predictions were obtained using the local models. Predictions obtained with models using similar size of samples (similar %) were averaged with the aim to describe the main patterns. The r2 of predictions obtained with models of higher size were not more accurate than those obtained with models of lower size. After repopulation, the RMSEP of predictions using models with lower sizes (5, 10 and 25% of samples of the library) were lower than RMSEP obtained with higher sizes (75 and 100%), indicating that small models can easily integrate the variability of the soils from the target site. The results suggest that calibrations of small size could be repopulated and "converted" in local calibrations. According to this, we can focus most of the efforts in the obtainment of highly accurate analytical values in a reduced set of samples (including some samples from the target sites). The patterns observed here are in opposition with the idea of global models. These results could encourage the expansion of this technique, because very large data based seems not to be needed. Future studies with very different samples will help to confirm the robustness of the patterns observed. Authors acknowledge to "Bancaja-UMH" for the financial support of the project "NIRPROS".

Sample sizes to control error estimates in determining soil bulk density in California forest soils

Treesearch

Youzhi Han; Jianwei Zhang; Kim G. Mattson; Weidong Zhang; Thomas A. Weber

2016-01-01

Characterizing forest soil properties with high variability is challenging, sometimes requiring large numbers of soil samples. Soil bulk density is a standard variable needed along with element concentrations to calculate nutrient pools. This study aimed to determine the optimal sample size, the number of observation (n), for predicting the soil bulk density with a...

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining.

PubMed

Hero, Alfred O; Rajaratnam, Bala

2016-01-01

When can reliable inference be drawn in fue "Big Data" context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for "Big Data". Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

Evaluating sampling strategy for DNA barcoding study of coastal and inland halo-tolerant Poaceae and Chenopodiaceae: A case study for increased sample size

PubMed Central

Yao, Peng-Cheng; Gao, Hai-Yan; Wei, Ya-Nan; Zhang, Jian-Hang; Chen, Xiao-Yong

2017-01-01

Environmental conditions in coastal salt marsh habitats have led to the development of specialist genetic adaptations. We evaluated six DNA barcode loci of the 53 species of Poaceae and 15 species of Chenopodiaceae from China's coastal salt marsh area and inland area. Our results indicate that the optimum DNA barcode was ITS for coastal salt-tolerant Poaceae and matK for the Chenopodiaceae. Sampling strategies for ten common species of Poaceae and Chenopodiaceae were analyzed according to optimum barcode. We found that by increasing the number of samples collected from the coastal salt marsh area on the basis of inland samples, the number of haplotypes of Arundinella hirta, Digitaria ciliaris, Eleusine indica, Imperata cylindrica, Setaria viridis, and Chenopodium glaucum increased, with a principal coordinate plot clearly showing increased distribution points. The results of a Mann-Whitney test showed that for Digitaria ciliaris, Eleusine indica, Imperata cylindrica, and Setaria viridis, the distribution of intraspecific genetic distances was significantly different when samples from the coastal salt marsh area were included (P < 0.01). These results suggest that increasing the sample size in specialist habitats can improve measurements of intraspecific genetic diversity, and will have a positive effect on the application of the DNA barcodes in widely distributed species. The results of random sampling showed that when sample size reached 11 for Chloris virgata, Chenopodium glaucum, and Dysphania ambrosioides, 13 for Setaria viridis, and 15 for Eleusine indica, Imperata cylindrica and Chenopodium album, average intraspecific distance tended to reach stability. These results indicate that the sample size for DNA barcode of globally distributed species should be increased to 11–15. PMID:28934362

Evaluating sampling strategy for DNA barcoding study of coastal and inland halo-tolerant Poaceae and Chenopodiaceae: A case study for increased sample size.

PubMed

Yao, Peng-Cheng; Gao, Hai-Yan; Wei, Ya-Nan; Zhang, Jian-Hang; Chen, Xiao-Yong; Li, Hong-Qing

2017-01-01

Environmental conditions in coastal salt marsh habitats have led to the development of specialist genetic adaptations. We evaluated six DNA barcode loci of the 53 species of Poaceae and 15 species of Chenopodiaceae from China's coastal salt marsh area and inland area. Our results indicate that the optimum DNA barcode was ITS for coastal salt-tolerant Poaceae and matK for the Chenopodiaceae. Sampling strategies for ten common species of Poaceae and Chenopodiaceae were analyzed according to optimum barcode. We found that by increasing the number of samples collected from the coastal salt marsh area on the basis of inland samples, the number of haplotypes of Arundinella hirta, Digitaria ciliaris, Eleusine indica, Imperata cylindrica, Setaria viridis, and Chenopodium glaucum increased, with a principal coordinate plot clearly showing increased distribution points. The results of a Mann-Whitney test showed that for Digitaria ciliaris, Eleusine indica, Imperata cylindrica, and Setaria viridis, the distribution of intraspecific genetic distances was significantly different when samples from the coastal salt marsh area were included (P < 0.01). These results suggest that increasing the sample size in specialist habitats can improve measurements of intraspecific genetic diversity, and will have a positive effect on the application of the DNA barcodes in widely distributed species. The results of random sampling showed that when sample size reached 11 for Chloris virgata, Chenopodium glaucum, and Dysphania ambrosioides, 13 for Setaria viridis, and 15 for Eleusine indica, Imperata cylindrica and Chenopodium album, average intraspecific distance tended to reach stability. These results indicate that the sample size for DNA barcode of globally distributed species should be increased to 11-15.

Effect of Pore Size and Porosity on the Biomechanical Properties and Cytocompatibility of Porous NiTi Alloys

PubMed Central

Jian, Yu-Tao; Yang, Yue; Tian, Tian; Stanford, Clark; Zhang, Xin-Ping; Zhao, Ke

2015-01-01

Five types of porous Nickel-Titanium (NiTi) alloy samples of different porosities and pore sizes were fabricated. According to compressive and fracture strengths, three groups of porous NiTi alloy samples underwent further cytocompatibility experiments. Porous NiTi alloys exhibited a lower Young’s modulus (2.0 GPa ~ 0.8 GPa). Both compressive strength (108.8 MPa ~ 56.2 MPa) and fracture strength (64.6 MPa ~ 41.6 MPa) decreased gradually with increasing mean pore size (MPS). Cells grew and spread well on all porous NiTi alloy samples. Cells attached more strongly on control group and blank group than on all porous NiTi alloy samples (p < 0.05). Cell adhesion on porous NiTi alloys was correlated negatively to MPS (277.2 μm ~ 566.5 μm; p < 0.05). More cells proliferated on control group and blank group than on all porous NiTi alloy samples (p < 0.05). Cellular ALP activity on all porous NiTi alloy samples was higher than on control group and blank group (p < 0.05). The porous NiTi alloys with optimized pore size could be a potential orthopedic material. PMID:26047515

"PowerUp"!: A Tool for Calculating Minimum Detectable Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-Experimental Design Studies

ERIC Educational Resources Information Center

Dong, Nianbo; Maynard, Rebecca

2013-01-01

This paper and the accompanying tool are intended to complement existing supports for conducting power analysis tools by offering a tool based on the framework of Minimum Detectable Effect Sizes (MDES) formulae that can be used in determining sample size requirements and in estimating minimum detectable effect sizes for a range of individual- and…

Marine sources of ice nucleating particles: results from phytoplankton cultures and samples collected at sea

NASA Astrophysics Data System (ADS)

Wilbourn, E.; Thornton, D.; Brooks, S. D.; Graff, J.

2016-12-01

The role of marine aerosols as ice nucleating particles is currently poorly understood. Despite growing interest, there are remarkably few ice nucleation measurements on representative marine samples. Here we present results of heterogeneous ice nucleation from laboratory studies and in-situ air and sea water samples collected during NAAMES (North Atlantic Aerosol and Marine Ecosystems Study). Thalassiosira weissflogii (CCMP 1051) was grown under controlled conditions in batch cultures and the ice nucleating activity depended on the growth phase of the cultures. Immersion freezing temperatures of the lab-grown diatoms were determined daily using a custom ice nucleation apparatus cooled at a set rate. Our results show that the age of the culture had a significant impact on ice nucleation temperature, with samples in stationary phase causing nucleation at -19.9 °C, approximately nine degrees warmer than the freezing temperature during exponential growth phase. Field samples gathered during the NAAMES II cruise in May 2016 were also tested for ice nucleating ability. Two types of samples were gathered. Firstly, whole cells were fractionated by size from surface seawater using a BD Biosciences Influx Cell Sorter (BD BS ISD). Secondly, aerosols were generated using the SeaSweep and subsequently size-selected using a PIXE Cascade Impactor. Samples were tested for the presence of ice nucleating particles (INP) using the technique described above. There were significant differences in the freezing temperature of the different samples; of the three sample types the lab-grown cultures tested during stationary phase froze at the warmest temperatures, followed by the SeaSweep samples (-25.6 °C) and the size-fractionated cell samples (-31.3 °C). Differences in ice nucleation ability may be due to size differences between the INP, differences in chemical composition of the sample, or some combination of these two factors. Results will be presented and atmospheric implications discussed.

Heavy metals relationship with water and size-fractionated sediments in rivers using canonical correlation analysis (CCA) case study, rivers of south western Caspian Sea.

PubMed

Vosoogh, Ali; Saeedi, Mohsen; Lak, Raziyeh

2016-11-01

Some pollutants can qualitatively affect aquatic freshwater such as rivers, and heavy metals are one of the most important pollutants in aquatic fresh waters. Heavy metals can be found in the form of components dissolved in these waters or in compounds with suspended particles and surface sediments. It can be said that heavy metals are in equilibrium between water and sediment. In this study, the amount of heavy metals is determined in water and different sizes of sediment. To obtain the relationship between heavy metals in water and size-fractionated sediments, a canonical correlation analysis (CCA) was utilized in rivers of the southwestern Caspian Sea. In this research, a case study was carried out on 18 sampling stations in nine rivers. In the first step, the concentrations of heavy metals (Cu, Zn, Cr, Fe, Mn, Pb, Ni, and Cd) were determined in water and size-fractionated sediment samples. Water sampling sites were classified by hierarchical cluster analysis (HCA) utilizing squared Euclidean distance with Ward's method. In addition, for interpreting the obtained results and the relationships between the concentration of heavy metals in the tested river water and sample sediments, canonical correlation analysis (CCA) was utilized. The rivers were grouped into two classes (those having no pollution and those having low pollution) based on the HCA results obtained for river water samples. CCA results found numerous relationships between rivers in Iran's Guilan province and their size-fractionated sediments samples. The heavy metals of sediments with 0.038 to 0.125 mm size in diameter are slightly correlated with those of water samples.

Addressing small sample size bias in multiple-biomarker trials: Inclusion of biomarker-negative patients and Firth correction.

PubMed

Habermehl, Christina; Benner, Axel; Kopp-Schneider, Annette

2018-03-01

In recent years, numerous approaches for biomarker-based clinical trials have been developed. One of these developments are multiple-biomarker trials, which aim to investigate multiple biomarkers simultaneously in independent subtrials. For low-prevalence biomarkers, small sample sizes within the subtrials have to be expected, as well as many biomarker-negative patients at the screening stage. The small sample sizes may make it unfeasible to analyze the subtrials individually. This imposes the need to develop new approaches for the analysis of such trials. With an expected large group of biomarker-negative patients, it seems reasonable to explore options to benefit from including them in such trials. We consider advantages and disadvantages of the inclusion of biomarker-negative patients in a multiple-biomarker trial with a survival endpoint. We discuss design options that include biomarker-negative patients in the study and address the issue of small sample size bias in such trials. We carry out a simulation study for a design where biomarker-negative patients are kept in the study and are treated with standard of care. We compare three different analysis approaches based on the Cox model to examine if the inclusion of biomarker-negative patients can provide a benefit with respect to bias and variance of the treatment effect estimates. We apply the Firth correction to reduce the small sample size bias. The results of the simulation study suggest that for small sample situations, the Firth correction should be applied to adjust for the small sample size bias. Additional to the Firth penalty, the inclusion of biomarker-negative patients in the analysis can lead to further but small improvements in bias and standard deviation of the estimates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys.

PubMed

Alegana, Victor A; Wright, Jim; Bosco, Claudio; Okiro, Emelda A; Atkinson, Peter M; Snow, Robert W; Tatem, Andrew J; Noor, Abdisalan M

2017-11-21

One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted. Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty. Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7-79.4) for the 2015 Kenya MIS (estimated sample size of children 0-4 years 7218 [7099-7288]), and 54.1% [50.1-56.5] for the 2014-2015 Rwanda DHS (12,220 [11,950-12,410]). This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

75 FR 81789 - Third Party Testing for Certain Children's Products; Full-Size Baby Cribs and Non-Full-Size Baby...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-28

... sufficient samples of the product, or samples that are identical in all material respects to the product. The... 1220, Safety Standards for Full-Size Baby Cribs and Non-Full- Size Baby Cribs. A true copy, in English... assessment bodies seeking accredited status must submit to the Commission copies, in English, of their...

Size-selective separation of polydisperse gold nanoparticles in supercritical ethane.

PubMed

Williams, Dylan P; Satherley, John

2009-04-09

The aim of this study was to use supercritical ethane to selectively disperse alkanethiol-stabilized gold nanoparticles of one size from a polydisperse sample in order to recover a monodisperse fraction of the nanoparticles. A disperse sample of metal nanoparticles with diameters in the range of 1-5 nm was prepared using established techniques then further purified by Soxhlet extraction. The purified sample was subjected to supercritical ethane at a temperature of 318 K in the pressure range 50-276 bar. Particles were characterized by UV-vis absorption spectroscopy, TEM, and MALDI-TOF mass spectroscopy. The results show that with increasing pressure the dispersibility of the nanoparticles increases, this effect is most pronounced for smaller nanoparticles. At the highest pressure investigated a sample of the particles was effectively stripped of all the smaller particles leaving a monodisperse sample. The relationship between dispersibility and supercritical fluid density for two different size samples of alkanethiol-stabilized gold nanoparticles was considered using the Chrastil chemical equilibrium model.

Effect of resin infiltration on the thermal and mechanical properties of nano-sized silica-based thermal insulation.

PubMed

Lee, Jae Chun; Kim, Yun-Il; Lee, Dong-Hun; Kim, Won-Jun; Park, Sung; Lee, Dong Bok

2011-08-01

Several kinds of nano-sized silica-based thermal insulation were prepared by dry processing of mixtures consisting of fumed silica, ceramic fiber, and a SiC opacifier. Infiltration of phenolic resin solution into the insulation, followed by hot-pressing, was attempted to improve the mechanical strength of the insulation. More than 22% resin content was necessary to increase the strength of the insulation by a factor of two or more. The structural integrity of the resin-infiltrated samples could be maintained, even after resin burn-out, presumably due to reinforcement from ceramic fibers. For all temperature ranges and similar sample bulk density values, the thermal conductivities of the samples after resin burn-out were consistently higher than those of the samples obtained from the dry process. Mercury intrusion curves indicated that the median size of the nanopores formed by primary silica aggregates in the samples after resin burn-out is consistently larger than that of the sample without resin infiltration.

Estimating accuracy of land-cover composition from two-stage cluster sampling

USGS Publications Warehouse

Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

2009-01-01

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

Support vector regression to predict porosity and permeability: Effect of sample size

NASA Astrophysics Data System (ADS)

Al-Anazi, A. F.; Gates, I. D.

2012-02-01

Porosity and permeability are key petrophysical parameters obtained from laboratory core analysis. Cores, obtained from drilled wells, are often few in number for most oil and gas fields. Porosity and permeability correlations based on conventional techniques such as linear regression or neural networks trained with core and geophysical logs suffer poor generalization to wells with only geophysical logs. The generalization problem of correlation models often becomes pronounced when the training sample size is small. This is attributed to the underlying assumption that conventional techniques employing the empirical risk minimization (ERM) inductive principle converge asymptotically to the true risk values as the number of samples increases. In small sample size estimation problems, the available training samples must span the complexity of the parameter space so that the model is able both to match the available training samples reasonably well and to generalize to new data. This is achieved using the structural risk minimization (SRM) inductive principle by matching the capability of the model to the available training data. One method that uses SRM is support vector regression (SVR) network. In this research, the capability of SVR to predict porosity and permeability in a heterogeneous sandstone reservoir under the effect of small sample size is evaluated. Particularly, the impact of Vapnik's ɛ-insensitivity loss function and least-modulus loss function on generalization performance was empirically investigated. The results are compared to the multilayer perception (MLP) neural network, a widely used regression method, which operates under the ERM principle. The mean square error and correlation coefficients were used to measure the quality of predictions. The results demonstrate that SVR yields consistently better predictions of the porosity and permeability with small sample size than the MLP method. Also, the performance of SVR depends on both kernel function type and loss functions used.

Grain size dependence of dynamic mechanical behavior of AZ31B magnesium alloy sheet under compressive shock loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asgari, H., E-mail: hamed.asgari@usask.ca; Odeshi, A.G.; Szpunar, J.A.

2015-08-15

The effects of grain size on the dynamic deformation behavior of rolled AZ31B alloy at high strain rates were investigated. Rolled AZ31B alloy samples with grain sizes of 6, 18 and 37 μm, were subjected to shock loading tests using Split Hopkinson Pressure Bar at room temperature and at a strain rate of 1100 s{sup −} {sup 1}. It was found that a double-peak basal texture formed in the shock loaded samples. The strength and ductility of the alloy under the high strain-rate compressive loading increased with decreasing grain size. However, twinning fraction and strain hardening rate were found tomore » decrease with decreasing grain size. In addition, orientation imaging microscopy showed a higher contribution of double and contraction twins in the deformation process of the coarse-grained samples. Using transmission electron microscopy, pyramidal dislocations were detected in the shock loaded sample, proving the activation of pyramidal slip system under dynamic impact loading. - Highlights: • A double-peak basal texture developed in all shock loaded samples. • Both strength and ductility increased with decreasing grain size. • Twinning fraction and strain hardening rate decreased with decreasing grain size. • ‘g.b’ analysis confirmed the presence of dislocations in shock loaded alloy.« less

Concurrent measurements of size-segregated particulate sulfate, nitrate and ammonium using quartz fiber filters, glass fiber filters and cellulose membranes

NASA Astrophysics Data System (ADS)

Tian, Shili; Pan, Yuepeng; Wang, Jian; Wang, Yuesi

2016-11-01

Current science and policy requirements have focused attention on the need to expand and improve particulate matter (PM) sampling methods. To explore how sampling filter type affects artifacts in PM composition measurements, size-resolved particulate SO42-, NO3- and NH4+ (SNA) were measured on quartz fiber filters (QFF), glass fiber filters (GFF) and cellulose membranes (CM) concurrently in an urban area of Beijing on both clean and hazy days. The results showed that SNA concentrations in most of the size fractions exhibited the following patterns on different filters: CM > QFF > GFF for NH4+; GFF > QFF > CM for SO42-; and GFF > CM > QFF for NO3-. The different patterns in coarse particles were mainly affected by filter acidity, and that in fine particles were mainly affected by hygroscopicity of the filters (especially in size fraction of 0.65-2.1 μm). Filter acidity and hygroscopicity also shifted the peaks of the annual mean size distributions of SNA on QFF from 0.43-0.65 μm on clean days to 0.65-1.1 μm on hazy days. However, this size shift was not as distinct for samples measured with CM and GFF. In addition, relative humidity (RH) and pollution levels are important factors that can enhance particulate size mode shifts of SNA on clean and hazy days. Consequently, the annual mean size distributions of SNA had maxima at 0.65-1.1 μm for QFF samples and 0.43-0.65 μm for GFF and CM samples. Compared with NH4+ and SO42-, NO3- is more sensitive to RH and pollution levels, accordingly, the annual mean size distribution of NO3- exhibited peak at 0.65-1.1 μm for CM samples instead of 0.43-0.65 μm. These methodological uncertainties should be considered when quantifying the concentrations and size distributions of SNA under different RH and haze conditions.

Characterization of the Particle Size and Polydispersity of Dicumarol Using Solid-State NMR Spectroscopy.

PubMed

Dempah, Kassibla Elodie; Lubach, Joseph W; Munson, Eric J

2017-03-06

A variety of particle sizes of a model compound, dicumarol, were prepared and characterized in order to investigate the correlation between particle size and solid-state NMR (SSNMR) proton spin-lattice relaxation ( 1 H T 1 ) times. Conventional laser diffraction and scanning electron microscopy were used as particle size measurement techniques and showed crystalline dicumarol samples with sizes ranging from tens of micrometers to a few micrometers. Dicumarol samples were prepared using both bottom-up and top-down particle size control approaches, via antisolvent microprecipitation and cryogrinding. It was observed that smaller particles of dicumarol generally had shorter 1 H T 1 times than larger ones. Additionally, cryomilled particles had the shortest 1 H T 1 times encountered (8 s). SSNMR 1 H T 1 times of all the samples were measured and showed as-received dicumarol to have a T 1 of 1500 s, whereas the 1 H T 1 times of the precipitated samples ranged from 20 to 80 s, with no apparent change in the physical form of dicumarol. Physical mixtures of different sized particles were also analyzed to determine the effect of sample inhomogeneity on 1 H T 1 values. Mixtures of cryoground and as-received dicumarol were clearly inhomogeneous as they did not fit well to a one-component relaxation model, but could be fit much better to a two-component model with both fast-and slow-relaxing regimes. Results indicate that samples of crystalline dicumarol containing two significantly different particle size populations could be deconvoluted solely based on their differences in 1 H T 1 times. Relative populations of each particle size regime could also be approximated using two-component fitting models. Using NMR theory on spin diffusion as a reference, and taking into account the presence of crystal defects, a model for the correlation between the particle size of dicumarol and its 1 H T 1 time was proposed.

A Mars Sample Return Sample Handling System

NASA Technical Reports Server (NTRS)

Wilson, David; Stroker, Carol

2013-01-01

We present a sample handling system, a subsystem of the proposed Dragon landed Mars Sample Return (MSR) mission [1], that can return to Earth orbit a significant mass of frozen Mars samples potentially consisting of: rock cores, subsurface drilled rock and ice cuttings, pebble sized rocks, and soil scoops. The sample collection, storage, retrieval and packaging assumptions and concepts in this study are applicable for the NASA's MPPG MSR mission architecture options [2]. Our study assumes a predecessor rover mission collects samples for return to Earth to address questions on: past life, climate change, water history, age dating, understanding Mars interior evolution [3], and, human safety and in-situ resource utilization. Hence the rover will have "integrated priorities for rock sampling" [3] that cover collection of subaqueous or hydrothermal sediments, low-temperature fluidaltered rocks, unaltered igneous rocks, regolith and atmosphere samples. Samples could include: drilled rock cores, alluvial and fluvial deposits, subsurface ice and soils, clays, sulfates, salts including perchlorates, aeolian deposits, and concretions. Thus samples will have a broad range of bulk densities, and require for Earth based analysis where practical: in-situ characterization, management of degradation such as perchlorate deliquescence and volatile release, and contamination management. We propose to adopt a sample container with a set of cups each with a sample from a specific location. We considered two sample cups sizes: (1) a small cup sized for samples matching those submitted to in-situ characterization instruments, and, (2) a larger cup for 100 mm rock cores [4] and pebble sized rocks, thus providing diverse samples and optimizing the MSR sample mass payload fraction for a given payload volume. We minimize sample degradation by keeping them frozen in the MSR payload sample canister using Peltier chip cooling. The cups are sealed by interference fitted heat activated memory alloy caps [5] if the heating does not affect the sample, or by crimping caps similar to bottle capping. We prefer cap sealing surfaces be external to the cup rim to prevent sample dust inside the cups interfering with sealing, or, contamination of the sample by Teflon seal elements (if adopted). Finally the sample collection rover, or a Fetch rover, selects cups with best choice samples and loads them into a sample tray, before delivering it to the Earth Return Vehicle (ERV) in the MSR Dragon capsule as described in [1] (Fig 1). This ensures best use of the MSR payload mass allowance. A 3 meter long jointed robot arm is extended from the Dragon capsule's crew hatch, retrieves the sample tray and inserts it into the sample canister payload located on the ERV stage. The robot arm has capacity to obtain grab samples in the event of a rover failure. The sample canister has a robot arm capture casting to enable capture by crewed or robot spacecraft when it returns to Earth orbit

Laboratory theory and methods for sediment analysis

USGS Publications Warehouse

Guy, Harold P.

1969-01-01

The diverse character of fluvial sediments makes the choice of laboratory analysis somewhat arbitrary and the pressing of sediment samples difficult. This report presents some theories and methods used by the Water Resources Division for analysis of fluvial sediments to determine the concentration of suspended-sediment samples and the particle-size distribution of both suspended-sediment and bed-material samples. Other analyses related to these determinations may include particle shape, mineral content, and specific gravity, the organic matter and dissolved solids of samples, and the specific weight of soils. The merits and techniques of both the evaporation and filtration methods for concentration analysis are discussed. Methods used for particle-size analysis of suspended-sediment samples may include the sieve pipet, the VA tube-pipet, or the BW tube-VA tube depending on the equipment available, the concentration and approximate size of sediment in the sample, and the settling medium used. The choice of method for most bed-material samples is usually limited to procedures suitable for sand or to some type of visual analysis for large sizes. Several tested forms are presented to help insure a well-ordered system in the laboratory to handle the samples, to help determine the kind of analysis required for each, to conduct the required processes, and to assist in the required computations. Use of the manual should further 'standardize' methods of fluvial sediment analysis among the many laboratories and thereby help to achieve uniformity and precision of the data.

Diagnostic test accuracy and prevalence inferences based on joint and sequential testing with finite population sampling.

PubMed

Su, Chun-Lung; Gardner, Ian A; Johnson, Wesley O

2004-07-30

The two-test two-population model, originally formulated by Hui and Walter, for estimation of test accuracy and prevalence estimation assumes conditionally independent tests, constant accuracy across populations and binomial sampling. The binomial assumption is incorrect if all individuals in a population e.g. child-care centre, village in Africa, or a cattle herd are sampled or if the sample size is large relative to population size. In this paper, we develop statistical methods for evaluating diagnostic test accuracy and prevalence estimation based on finite sample data in the absence of a gold standard. Moreover, two tests are often applied simultaneously for the purpose of obtaining a 'joint' testing strategy that has either higher overall sensitivity or specificity than either of the two tests considered singly. Sequential versions of such strategies are often applied in order to reduce the cost of testing. We thus discuss joint (simultaneous and sequential) testing strategies and inference for them. Using the developed methods, we analyse two real and one simulated data sets, and we compare 'hypergeometric' and 'binomial-based' inferences. Our findings indicate that the posterior standard deviations for prevalence (but not sensitivity and specificity) based on finite population sampling tend to be smaller than their counterparts for infinite population sampling. Finally, we make recommendations about how small the sample size should be relative to the population size to warrant use of the binomial model for prevalence estimation. Copyright 2004 John Wiley & Sons, Ltd.

Whole Brain Size and General Mental Ability: A Review

PubMed Central

Rushton, J. Philippe; Ankney, C. Davison

2009-01-01

We review the literature on the relation between whole brain size and general mental ability (GMA) both within and between species. Among humans, in 28 samples using brain imaging techniques, the mean brain size/GMA correlation is 0.40 (N = 1,389; p < 10−10); in 59 samples using external head size measures it is 0.20 (N = 63,405; p < 10−10). In 6 samples using the method of correlated vectors to distill g, the general factor of mental ability, the mean r is 0.63. We also describe the brain size/GMA correlations with age, socioeconomic position, sex, and ancestral population groups, which also provide information about brain–behavior relationships. Finally, we examine brain size and mental ability from an evolutionary and behavior genetic perspective. PMID:19283594

Robust Covariate-Adjusted Log-Rank Statistics and Corresponding Sample Size Formula for Recurrent Events Data

PubMed Central

Song, Rui; Kosorok, Michael R.; Cai, Jianwen

2009-01-01

Summary Recurrent events data are frequently encountered in clinical trials. This article develops robust covariate-adjusted log-rank statistics applied to recurrent events data with arbitrary numbers of events under independent censoring and the corresponding sample size formula. The proposed log-rank tests are robust with respect to different data-generating processes and are adjusted for predictive covariates. It reduces to the Kong and Slud (1997, Biometrika 84, 847–862) setting in the case of a single event. The sample size formula is derived based on the asymptotic normality of the covariate-adjusted log-rank statistics under certain local alternatives and a working model for baseline covariates in the recurrent event data context. When the effect size is small and the baseline covariates do not contain significant information about event times, it reduces to the same form as that of Schoenfeld (1983, Biometrics 39, 499–503) for cases of a single event or independent event times within a subject. We carry out simulations to study the control of type I error and the comparison of powers between several methods in finite samples. The proposed sample size formula is illustrated using data from an rhDNase study. PMID:18162107

A Bayesian sequential design with adaptive randomization for 2-sided hypothesis test.

PubMed

Yu, Qingzhao; Zhu, Lin; Zhu, Han

2017-11-01

Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic. Algorithms are presented to calculate the optimal randomization rate, critical values, and power for the proposed design. Sensitivity analysis is implemented to check the influence on design by changing the prior distributions. Simulation studies are applied to compare the proposed method and traditional methods in terms of power and actual sample sizes. Simulations show that, when total sample size is fixed, the proposed design can obtain greater power and/or cost smaller actual sample size than the traditional Bayesian sequential design. Finally, we apply the proposed method to a real data set and compare the results with the Bayesian sequential design without adaptive randomization in terms of sample sizes. The proposed method can further reduce required sample size. Copyright © 2017 John Wiley & Sons, Ltd.

Sampling studies to estimate the HIV prevalence rate in female commercial sex workers.

PubMed

Pascom, Ana Roberta Pati; Szwarcwald, Célia Landmann; Barbosa Júnior, Aristides

2010-01-01

We investigated sampling methods being used to estimate the HIV prevalence rate among female commercial sex workers. The studies were classified according to the adequacy or not of the sample size to estimate HIV prevalence rate and according to the sampling method (probabilistic or convenience). We identified 75 studies that estimated the HIV prevalence rate among female sex workers. Most of the studies employed convenience samples. The sample size was not adequate to estimate HIV prevalence rate in 35 studies. The use of convenience sample limits statistical inference for the whole group. It was observed that there was an increase in the number of published studies since 2005, as well as in the number of studies that used probabilistic samples. This represents a large advance in the monitoring of risk behavior practices and HIV prevalence rate in this group.

Effects of Sample Preparation on the Infrared Reflectance Spectra of Powders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brauer, Carolyn S.; Johnson, Timothy J.; Myers, Tanya L.

2015-05-22

While reflectance spectroscopy is a useful tool in identifying molecular compounds, laboratory measurement of solid (particularly powder) samples often is confounded by sample preparation methods. For example, both the packing density and surface roughness can have an effect on the quantitative reflectance spectra of powdered samples. Recent efforts in our group have focused on developing standard methods for measuring reflectance spectra that accounts for sample preparation, as well as other factors such as particle size and provenance. In this work, the effect of preparation method on sample reflectivity was investigated by measuring the directional-hemispherical spectra of samples that were hand-packedmore » as well as pressed into pellets using an integrating sphere attached to a Fourier transform infrared spectrometer. The results show that the methods used to prepare the sample have a substantial effect on the measured reflectance spectra, as do other factors such as particle size.« less

Effects of sample preparation on the infrared reflectance spectra of powders

NASA Astrophysics Data System (ADS)

Brauer, Carolyn S.; Johnson, Timothy J.; Myers, Tanya L.; Su, Yin-Fong; Blake, Thomas A.; Forland, Brenda M.

2015-05-01

While reflectance spectroscopy is a useful tool for identifying molecular compounds, laboratory measurement of solid (particularly powder) samples often is confounded by sample preparation methods. For example, both the packing density and surface roughness can have an effect on the quantitative reflectance spectra of powdered samples. Recent efforts in our group have focused on developing standard methods for measuring reflectance spectra that accounts for sample preparation, as well as other factors such as particle size and provenance. In this work, the effect of preparation method on sample reflectivity was investigated by measuring the directional-hemispherical spectra of samples that were hand-loaded as well as pressed into pellets using an integrating sphere attached to a Fourier transform infrared spectrometer. The results show that the methods used to prepare the sample can have a substantial effect on the measured reflectance spectra, as do other factors such as particle size.

Image analysis of representative food structures: application of the bootstrap method.

PubMed

Ramírez, Cristian; Germain, Juan C; Aguilera, José M

2009-08-01

Images (for example, photomicrographs) are routinely used as qualitative evidence of the microstructure of foods. In quantitative image analysis it is important to estimate the area (or volume) to be sampled, the field of view, and the resolution. The bootstrap method is proposed to estimate the size of the sampling area as a function of the coefficient of variation (CV(Bn)) and standard error (SE(Bn)) of the bootstrap taking sub-areas of different sizes. The bootstrap method was applied to simulated and real structures (apple tissue). For simulated structures, 10 computer-generated images were constructed containing 225 black circles (elements) and different coefficient of variation (CV(image)). For apple tissue, 8 images of apple tissue containing cellular cavities with different CV(image) were analyzed. Results confirmed that for simulated and real structures, increasing the size of the sampling area decreased the CV(Bn) and SE(Bn). Furthermore, there was a linear relationship between the CV(image) and CV(Bn) (.) For example, to obtain a CV(Bn) = 0.10 in an image with CV(image) = 0.60, a sampling area of 400 x 400 pixels (11% of whole image) was required, whereas if CV(image) = 1.46, a sampling area of 1000 x 100 pixels (69% of whole image) became necessary. This suggests that a large-size dispersion of element sizes in an image requires increasingly larger sampling areas or a larger number of images.

Industrial Application of Valuable Materials Generated from PLK Rock-A Bauxite Mining Waste

NASA Astrophysics Data System (ADS)

Swain, Ranjita; Routray, Sunita; Mohapatra, Abhisek; Ranjan Patra, Biswa

2018-03-01

PLK rock classified in to two products after a selective grinding to a particular size fraction. PLK rocks ground to below 45-micron size which is followed by a classifier i.e. hydrocyclone. The ground product classified in to different sizes of apex and vortex finder. The pressure gauge was attached for the measurement of the pressure. The production of fines is also increasing with increase in the vortex finder diameter. In order to increase in the feed capacity of the hydrocyclone, the vortex finder 11.1 mm diameter and the spigot diameter 8.0 mm has been considered as the best optimum condition for recovery of fines from PLK rock sample. The overflow sample contains 5.39% iron oxide (Fe2O3) with 0.97% of TiO2 and underflow sample contains 1.87% Fe2O3 with 2.39% of TiO2. The cut point or separation size of overflow sample is 25 μm. The efficiency of separation, or the so-called imperfection I, is at 6 μm size. In this study, the iron oxide content in underflow sample is less than 2% which is suitable for making of refractory application. The overflow sample is very fine which can also be a raw material for ceramic industry as well as a cosmetic product.

Sample Size in Clinical Cardioprotection Trials Using Myocardial Salvage Index, Infarct Size, or Biochemical Markers as Endpoint.

PubMed

Engblom, Henrik; Heiberg, Einar; Erlinge, David; Jensen, Svend Eggert; Nordrehaug, Jan Erik; Dubois-Randé, Jean-Luc; Halvorsen, Sigrun; Hoffmann, Pavel; Koul, Sasha; Carlsson, Marcus; Atar, Dan; Arheden, Håkan

2016-03-09

Cardiac magnetic resonance (CMR) can quantify myocardial infarct (MI) size and myocardium at risk (MaR), enabling assessment of myocardial salvage index (MSI). We assessed how MSI impacts the number of patients needed to reach statistical power in relation to MI size alone and levels of biochemical markers in clinical cardioprotection trials and how scan day affect sample size. Controls (n=90) from the recent CHILL-MI and MITOCARE trials were included. MI size, MaR, and MSI were assessed from CMR. High-sensitivity troponin T (hsTnT) and creatine kinase isoenzyme MB (CKMB) levels were assessed in CHILL-MI patients (n=50). Utilizing distribution of these variables, 100 000 clinical trials were simulated for calculation of sample size required to reach sufficient power. For a treatment effect of 25% decrease in outcome variables, 50 patients were required in each arm using MSI compared to 93, 98, 120, 141, and 143 for MI size alone, hsTnT (area under the curve [AUC] and peak), and CKMB (AUC and peak) in order to reach a power of 90%. If average CMR scan day between treatment and control arms differed by 1 day, sample size needs to be increased by 54% (77 vs 50) to avoid scan day bias masking a treatment effect of 25%. Sample size in cardioprotection trials can be reduced 46% to 65% without compromising statistical power when using MSI by CMR as an outcome variable instead of MI size alone or biochemical markers. It is essential to ensure lack of bias in scan day between treatment and control arms to avoid compromising statistical power. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

The late Neandertal supraorbital fossils from Vindija Cave, Croatia: a biased sample?

PubMed

Ahern, James C M; Lee, Sang-Hee; Hawks, John D

2002-09-01

The late Neandertal sample from Vindija (Croatia) has been described as transitional between the earlier Central European Neandertals from Krapina (Croatia) and modern humans. However, the morphological differences indicating this transition may rather be the result of different sex and/or age compositions between the samples. This study tests the hypothesis that the metric differences between the Krapina and Vindija supraorbital samples are due to sampling bias. We focus upon the supraorbital region because past studies have posited this region as particularly indicative of the Vindija sample's transitional nature. Furthermore, the supraorbital region varies significantly with both age and sex. We analyzed four chords and two derived indices of supraorbital torus form as defined by Smith & Ranyard (1980, Am. J. phys. Anthrop.93, pp. 589-610). For each variable, we analyzed relative sample bias of the Krapina and Vindija samples using three sampling methods. In order to test the hypothesis that the Vindija sample contains an over-representation of females and/or young while the Krapina sample is normal or also female/young biased, we determined the probability of drawing a sample of the same size as and with a mean equal to or less than Vindija's from a Krapina-based population. In order to test the hypothesis that the Vindija sample is female/young biased while the Krapina sample is male/old biased, we determined the probability of drawing a sample of the same size as and with a mean equal or less than Vindija's from a generated population whose mean is halfway between Krapina's and Vindija's. Finally, in order to test the hypothesis that the Vindija sample is normal while the Krapina sample contains an over-representation of males and/or old, we determined the probability of drawing a sample of the same size as and with a mean equal to or greater than Krapina's from a Vindija-based population. Unless we assume that the Vindija sample is female/young and the Krapina sample is male/old biased, our results falsify the hypothesis that the metric differences between the Krapina and Vindija samples are due to sample bias.

Random vs. systematic sampling from administrative databases involving human subjects.

PubMed

Hagino, C; Lo, R J

1998-09-01

Two sampling techniques, simple random sampling (SRS) and systematic sampling (SS), were compared to determine whether they yield similar and accurate distributions for the following four factors: age, gender, geographic location and years in practice. Any point estimate within 7 yr or 7 percentage points of its reference standard (SRS or the entire data set, i.e., the target population) was considered "acceptably similar" to the reference standard. The sampling frame was from the entire membership database of the Canadian Chiropractic Association. The two sampling methods were tested using eight different sample sizes of n (50, 100, 150, 200, 250, 300, 500, 800). From the profile/characteristics, summaries of four known factors [gender, average age, number (%) of chiropractors in each province and years in practice], between- and within-methods chi 2 tests and unpaired t tests were performed to determine whether any of the differences [descriptively greater than 7% or 7 yr] were also statistically significant. The strengths of the agreements between the provincial distributions were quantified by calculating the percent agreements for each (provincial pairwise-comparison methods). Any percent agreement less than 70% was judged to be unacceptable. Our assessments of the two sampling methods (SRS and SS) for the different sample sizes tested suggest that SRS and SS yielded acceptably similar results. Both methods started to yield "correct" sample profiles at approximately the same sample size (n > 200). SS is not only convenient, it can be recommended for sampling from large databases in which the data are listed without any inherent order biases other than alphabetical listing by surname.

Big Data and Large Sample Size: A Cautionary Note on the Potential for Bias

PubMed Central

Chambers, David A.; Glasgow, Russell E.

2014-01-01

Abstract A number of commentaries have suggested that large studies are more reliable than smaller studies and there is a growing interest in the analysis of “big data” that integrates information from many thousands of persons and/or different data sources. We consider a variety of biases that are likely in the era of big data, including sampling error, measurement error, multiple comparisons errors, aggregation error, and errors associated with the systematic exclusion of information. Using examples from epidemiology, health services research, studies on determinants of health, and clinical trials, we conclude that it is necessary to exercise greater caution to be sure that big sample size does not lead to big inferential errors. Despite the advantages of big studies, large sample size can magnify the bias associated with error resulting from sampling or study design. Clin Trans Sci 2014; Volume #: 1–5 PMID:25043853

Temporal change in the size distribution of airborne Radiocesium derived from the Fukushima accident

NASA Astrophysics Data System (ADS)

Kaneyasu, Naoki; Ohashi, Hideo; Suzuki, Fumie; Okuda, Tomoaki; Ikemori, Fumikazu; Akata, Naofumi

2013-04-01

The accident of Fukushima Dai-ichi nuclear power plant discharged a large amount of radioactive materials into the environment. After 40 days of the accident, we started to collect the size-segregated aerosol at Tsukuba City, Japan, located 170 km south of the plant, by use of a low-pressure cascade impactor. The sampling continued from April 28, through October 26, 2011. The number of sample sets collected in total was 8. The radioactivity of 134Cs and 137Cs in aerosols collected at each stage were determined by gamma-ray with a high sensitivity Germanic detector. After the gamma-ray spectrometry analysis, the chemical species in the aerosols were analyzed. The analyses of first (April 28-May 12) and second (May 12-26) samples showed that the activity size distributions of 134Cs and 137Cs in aerosols reside mostly in the accumulation mode size range. These activity size distributions almost overlapped with the mass size distribution of non-sea-salt sulfate aerosol. From the results, we regarded that sulfate is the main transport medium of these radionuclides, and re-suspended soil particles that attached radionuclides were not the major airborne radioactive substances by the end of May, 2011 (Kaneyasu et al., 2012). We further conducted the successive extraction experiment of radiocesium from the aerosol deposits on the aluminum sheet substrate (8th stage of the first aerosol sample, 0.5-0.7 μm in aerodynamic diameter) with water and 0.1M HCl. In contrast to the relatively insoluble property of Chernobyl radionuclides, those in aerosols collected at Tsukuba in fine mode are completely water-soluble (100%). From the third aerosol sample, the activity size distributions started to change, i.e., the major peak in the accumulation mode size range seen in the first and second aerosol samples became smaller and an additional peak appeared in the coarse mode size range. The comparison of the activity size distributions of radiocesium and the mass size distributions of major aerosol components collected by the end of August, 2011, (i.e., sample No.5) and its implication will be discussed in the presentation. Reference Kaneyasu et al., Environ. Sci. Technol. 46, 5720-5726 (2012).

Sampling bee communities using pan traps: alternative methods increase sample size

USDA-ARS?s Scientific Manuscript database

Monitoring of the status of bee populations and inventories of bee faunas require systematic sampling. Efficiency and ease of implementation has encouraged the use of pan traps to sample bees. Efforts to find an optimal standardized sampling method for pan traps have focused on pan trap color. Th...

A Scanning Transmission Electron Microscopy Method for Determining Manganese Composition in Welding Fume as a Function of Primary Particle Size

PubMed Central

Richman, Julie D.; Livi, Kenneth J.T.; Geyh, Alison S.

2011-01-01

Increasing evidence suggests that the physicochemical properties of inhaled nanoparticles influence the resulting toxicokinetics and toxicodynamics. This report presents a method using scanning transmission electron microscopy (STEM) to measure the Mn content throughout the primary particle size distribution of welding fume particle samples collected on filters for application in exposure and health research. Dark field images were collected to assess the primary particle size distribution and energy-dispersive X-ray and electron energy loss spectroscopy were performed for measurement of Mn composition as a function of primary particle size. A manual method incorporating imaging software was used to measure the primary particle diameter and to select an integration region for compositional analysis within primary particles throughout the size range. To explore the variation in the developed metric, the method was applied to 10 gas metal arc welding (GMAW) fume particle samples of mild steel that were collected under a variety of conditions. The range of Mn composition by particle size was −0.10 to 0.19 %/nm, where a positive estimate indicates greater relative abundance of Mn increasing with primary particle size and a negative estimate conversely indicates decreasing Mn content with size. However, the estimate was only statistically significant (p<0.05) in half of the samples (n=5), which all had a positive estimate. In the remaining samples, no significant trend was measured. Our findings indicate that the method is reproducible and that differences in the abundance of Mn by primary particle size among welding fume samples can be detected. PMID:21625364

A Scanning Transmission Electron Microscopy Method for Determining Manganese Composition in Welding Fume as a Function of Primary Particle Size.

PubMed

Richman, Julie D; Livi, Kenneth J T; Geyh, Alison S

2011-06-01

Increasing evidence suggests that the physicochemical properties of inhaled nanoparticles influence the resulting toxicokinetics and toxicodynamics. This report presents a method using scanning transmission electron microscopy (STEM) to measure the Mn content throughout the primary particle size distribution of welding fume particle samples collected on filters for application in exposure and health research. Dark field images were collected to assess the primary particle size distribution and energy-dispersive X-ray and electron energy loss spectroscopy were performed for measurement of Mn composition as a function of primary particle size. A manual method incorporating imaging software was used to measure the primary particle diameter and to select an integration region for compositional analysis within primary particles throughout the size range. To explore the variation in the developed metric, the method was applied to 10 gas metal arc welding (GMAW) fume particle samples of mild steel that were collected under a variety of conditions. The range of Mn composition by particle size was -0.10 to 0.19 %/nm, where a positive estimate indicates greater relative abundance of Mn increasing with primary particle size and a negative estimate conversely indicates decreasing Mn content with size. However, the estimate was only statistically significant (p<0.05) in half of the samples (n=5), which all had a positive estimate. In the remaining samples, no significant trend was measured. Our findings indicate that the method is reproducible and that differences in the abundance of Mn by primary particle size among welding fume samples can be detected.

Estimating the quadratic mean diameter of fine woody debris for forest type groups of the United States

Treesearch

Christopher W. Woodall; Vicente J. Monleon

2009-01-01

The Forest Inventory and Analysis program of the Forest Service, U.S. Department of Agriculture conducts a national inventory of fine woody debris (FWD); however, the sampling protocols involve tallying only the number of FWD pieces by size class that intersect a sampling transect with no measure of actual size. The line intersect estimator used with those samples...

Diet- and Body Size-Related Attitudes and Behaviors Associated with Vitamin Supplement Use in a Representative Sample of Fourth-Grade Students in Texas

ERIC Educational Resources Information Center

George, Goldy C.; Hoelscher, Deanna M.; Nicklas, Theresa A.; Kelder, Steven H.

2009-01-01

Objective: To examine diet- and body size-related attitudes and behaviors associated with supplement use in a representative sample of fourth-grade students in Texas. Design: Cross-sectional data from the School Physical Activity and Nutrition study, a probability-based sample of schoolchildren. Children completed a questionnaire that assessed…

Meta-analysis of genome-wide association from genomic prediction models

USDA-ARS?s Scientific Manuscript database

A limitation of many genome-wide association studies (GWA) in animal breeding is that there are many loci with small effect sizes; thus, larger sample sizes (N) are required to guarantee suitable power of detection. To increase sample size, results from different GWA can be combined in a meta-analys...

75 FR 48815 - Medicaid Program and Children's Health Insurance Program (CHIP); Revisions to the Medicaid...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-11

... size may be reduced by the finite population correction factor. The finite population correction is a statistical formula utilized to determine sample size where the population is considered finite rather than... program may notify us and the annual sample size will be reduced by the finite population correction...

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

The Precision Efficacy Analysis for Regression Sample Size Method.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.

The general purpose of this study was to examine the efficiency of the Precision Efficacy Analysis for Regression (PEAR) method for choosing appropriate sample sizes in regression studies used for precision. The PEAR method, which is based on the algebraic manipulation of an accepted cross-validity formula, essentially uses an effect size to…

Sampling of illicit drugs for quantitative analysis--part II. Study of particle size and its influence on mass reduction.

PubMed

Bovens, M; Csesztregi, T; Franc, A; Nagy, J; Dujourdy, L

2014-01-01

The basic goal in sampling for the quantitative analysis of illicit drugs is to maintain the average concentration of the drug in the material from its original seized state (the primary sample) all the way through to the analytical sample, where the effect of particle size is most critical. The size of the largest particles of different authentic illicit drug materials, in their original state and after homogenisation, using manual or mechanical procedures, was measured using a microscope with a camera attachment. The comminution methods employed included pestle and mortar (manual) and various ball and knife mills (mechanical). The drugs investigated were amphetamine, heroin, cocaine and herbal cannabis. It was shown that comminution of illicit drug materials using these techniques reduces the nominal particle size from approximately 600 μm down to between 200 and 300 μm. It was demonstrated that the choice of 1 g increments for the primary samples of powdered drugs and cannabis resin, which were used in the heterogeneity part of our study (Part I) was correct for the routine quantitative analysis of illicit seized drugs. For herbal cannabis we found that the appropriate increment size was larger. Based on the results of this study we can generally state that: An analytical sample weight of between 20 and 35 mg of an illicit powdered drug, with an assumed purity of 5% or higher, would be considered appropriate and would generate an RSDsampling in the same region as the RSDanalysis for a typical quantitative method of analysis for the most common, powdered, illicit drugs. For herbal cannabis, with an assumed purity of 1% THC (tetrahydrocannabinol) or higher, an analytical sample weight of approximately 200 mg would be appropriate. In Part III we will pull together our homogeneity studies and particle size investigations and use them to devise sampling plans and sample preparations suitable for the quantitative instrumental analysis of the most common illicit drugs. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Thermal conductivity of graphene mediated by strain and size

DOE PAGES

Kuang, Youdi; Shi, Sanqiang; Wang, Xinjiang; ...

2016-06-09

Based on first-principles calculations and full iterative solution of the linearized Boltzmann–Peierls transport equation for phonons, we systematically investigate effects of strain, size and temperature on the thermal conductivity k of suspended graphene. The calculated size-dependent and temperature-dependent k for finite samples agree well with experimental data. The results show that, contrast to the convergent room-temperature k = 5450 W/m-K of unstrained graphene at a sample size ~8 cm, k of strained graphene diverges with increasing the sample size even at high temperature. Out-of-plane acoustic phonons are responsible for the significant size effect in unstrained and strained graphene due tomore » their ultralong mean free path and acoustic phonons with wavelength smaller than 10 nm contribute 80% to the intrinsic room temperature k of unstrained graphene. Tensile strain hardens the flexural modes and increases their lifetimes, causing interesting dependence of k on sample size and strain due to the competition between boundary scattering and intrinsic phonon–phonon scattering. k of graphene can be tuned within a large range by strain for the size larger than 500 μm. These findings shed light on the nature of thermal transport in two-dimensional materials and may guide predicting and engineering k of graphene by varying strain and size.« less

Development of a copula-based particle filter (CopPF) approach for hydrologic data assimilation under consideration of parameter interdependence

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, G. H.; Baetz, B. W.; Li, Y. P.; Huang, K.

2017-06-01

In this study, a copula-based particle filter (CopPF) approach was developed for sequential hydrological data assimilation by considering parameter correlation structures. In CopPF, multivariate copulas are proposed to reflect parameter interdependence before the resampling procedure with new particles then being sampled from the obtained copulas. Such a process can overcome both particle degeneration and sample impoverishment. The applicability of CopPF is illustrated with three case studies using a two-parameter simplified model and two conceptual hydrologic models. The results for the simplified model indicate that model parameters are highly correlated in the data assimilation process, suggesting a demand for full description of their dependence structure. Synthetic experiments on hydrologic data assimilation indicate that CopPF can rejuvenate particle evolution in large spaces and thus achieve good performances with low sample size scenarios. The applicability of CopPF is further illustrated through two real-case studies. It is shown that, compared with traditional particle filter (PF) and particle Markov chain Monte Carlo (PMCMC) approaches, the proposed method can provide more accurate results for both deterministic and probabilistic prediction with a sample size of 100. Furthermore, the sample size would not significantly influence the performance of CopPF. Also, the copula resampling approach dominates parameter evolution in CopPF, with more than 50% of particles sampled by copulas in most sample size scenarios.

Bed-material characteristics of the Sacramento–San Joaquin Delta, California, 2010–13

USGS Publications Warehouse

Marineau, Mathieu D.; Wright, Scott A.

2017-02-10

The characteristics of bed material at selected sites within the Sacramento–San Joaquin Delta, California, during 2010–13 are described in a study conducted by the U.S. Geological Survey in cooperation with the Bureau of Reclamation. During 2010‒13, six complete sets of samples were collected. Samples were initially collected at 30 sites; however, starting in 2012, samples were collected at 7 additional sites. These sites are generally collocated with an active streamgage. At all but one site, a separate bed-material sample was collected at three locations within the channel (left, right, and center). Bed-material samples were collected using either a US BMH–60 or a US BM–54 (for sites with higher stream velocity) cable-suspended, scoop sampler. Samples from each location were oven-dried and sieved. Bed material finer than 2 millimeters was subsampled using a sieving riffler and processed using a Beckman Coulter LS 13–320 laser diffraction particle-size analyzer. To determine the organic content of the bed material, the loss on ignition method was used for one subsample from each location. Particle-size distributions are presented as cumulative percent finer than a given size. Median and 90th-percentile particle size, and the percentage of subsample mass lost using the loss on ignition method for each sample are also presented in this report.

Mesh-size effects on drift sample composition as determined with a triple net sampler

USGS Publications Warehouse

Slack, K.V.; Tilley, L.J.; Kennelly, S.S.

1991-01-01

Nested nets of three different mesh apertures were used to study mesh-size effects on drift collected in a small mountain stream. The innermost, middle, and outermost nets had, respectively, 425 ??m, 209 ??m and 106 ??m openings, a design that reduced clogging while partitioning collections into three size groups. The open area of mesh in each net, from largest to smallest mesh opening, was 3.7, 5.7 and 8.0 times the area of the net mouth. Volumes of filtered water were determined with a flowmeter. The results are expressed as (1) drift retained by each net, (2) drift that would have been collected by a single net of given mesh size, and (3) the percentage of total drift (the sum of the catches from all three nets) that passed through the 425 ??m and 209 ??m nets. During a two day period in August 1986, Chironomidae larvae were dominant numerically in all 209 ??m and 106 ??m samples and midday 425 ??m samples. Large drifters (Ephemerellidae) occurred only in 425 ??m or 209 ??m nets, but the general pattern was an increase in abundance and number of taxa with decreasing mesh size. Relatively more individuals occurred in the larger mesh nets at night than during the day. The two larger mesh sizes retained 70% of the total sediment/detritus in the drift collections, and this decreased the rate of clogging of the 106 ??m net. If an objective of a sampling program is to compare drift density or drift rate between areas or sampling dates, the same mesh size should be used for all sample collection and processing. The mesh aperture used for drift collection should retain all species and life stages of significance in a study. The nested net design enables an investigator to test the adequacy of drift samples. ?? 1991 Kluwer Academic Publishers.

Particle size distribution of distillers dried grains with solubles (DDGS) and relationships to compositional and color properties.

PubMed

Liu, Keshun

2008-11-01

Eleven distillers dried grains with solubles (DDGS), processed from yellow corn, were collected from different ethanol processing plants in the US Midwest area. Particle size distribution (PSD) by mass of each sample was determined using a series of six selected US standard sieves: Nos. 8, 12, 18, 35, 60, and 100, and a pan. The original sample and sieve sized fractions were measured for surface color and contents of moisture, protein, oil, ash, and starch. Total carbohydrate (CHO) and total non-starch CHO were also calculated. Results show that there was a great variation in composition and color among DDGS from different plants. Surprisingly, a few DDGS samples contained unusually high amounts of residual starch (11.1-17.6%, dry matter basis, vs. about 5% of the rest), presumably resulting from modified processing methods. Particle size of DDGS varied greatly within a sample and PSD varied greatly among samples. The 11 samples had a mean value of 0.660mm for the geometric mean diameter (dgw) of particles and a mean value of 0.440mm for the geometric standard deviation (Sgw) of particle diameters by mass. The majority had a unimodal PSD, with a mode in the size class between 0.5 and 1.0mm. Although PSD and color parameters had little correlation with composition of whole DDGS samples, distribution of nutrients as well as color attributes correlated well with PSD. In sieved fractions, protein content, L and a color values negatively while contents of oil and total CHO positively correlated with particle size. It is highly feasible to fractionate DDGS for compositional enrichment based on particle size, while the extent of PSD can serve as an index for potential of DDGS fractionation. The above information should be a vital addition to quality and baseline data of DDGS.

Optimisation of a sample preparation procedure for the screening of fungal infection and assessment of deoxynivalenol content in maize using mid-infrared attenuated total reflection spectroscopy.

PubMed

Kos, Gregor; Lohninger, Hans; Mizaikoff, Boris; Krska, Rudolf

2007-07-01

A sample preparation procedure for the determination of deoxynivalenol (DON) using attenuated total reflection mid-infrared spectroscopy is presented. Repeatable spectra were obtained from samples featuring a narrow particle size distribution. Samples were ground with a centrifugal mill and analysed with an analytical sieve shaker. Particle sizes of <100, 100-250, 250-500, 500-710 and 710-1000 microm were obtained. Repeatability, classification and quantification abilities for DON were compared with non-sieved samples. The 100-250 microm fraction showed the best repeatability. The relative standard deviation of spectral measurements improved from 20 to 4.4% and 100% of sieved samples were correctly classified compared with 79% of non-sieved samples. The DON level in analysed fractions was a good estimate of overall toxin content.

Weighting by Inverse Variance or by Sample Size in Random-Effects Meta-Analysis

ERIC Educational Resources Information Center

Marin-Martinez, Fulgencio; Sanchez-Meca, Julio

2010-01-01

Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a…

Optimal sample sizes for the design of reliability studies: power consideration.

PubMed

Shieh, Gwowen

2014-09-01

Intraclass correlation coefficients are used extensively to measure the reliability or degree of resemblance among group members in multilevel research. This study concerns the problem of the necessary sample size to ensure adequate statistical power for hypothesis tests concerning the intraclass correlation coefficient in the one-way random-effects model. In view of the incomplete and problematic numerical results in the literature, the approximate sample size formula constructed from Fisher's transformation is reevaluated and compared with an exact approach across a wide range of model configurations. These comprehensive examinations showed that the Fisher transformation method is appropriate only under limited circumstances, and therefore it is not recommended as a general method in practice. For advance design planning of reliability studies, the exact sample size procedures are fully described and illustrated for various allocation and cost schemes. Corresponding computer programs are also developed to implement the suggested algorithms.

Sample size in psychological research over the past 30 years.

PubMed

Marszalek, Jacob M; Barber, Carolyn; Kohlhart, Julie; Holmes, Cooper B

2011-04-01

The American Psychological Association (APA) Task Force on Statistical Inference was formed in 1996 in response to a growing body of research demonstrating methodological issues that threatened the credibility of psychological research, and made recommendations to address them. One issue was the small, even dramatically inadequate, size of samples used in studies published by leading journals. The present study assessed the progress made since the Task Force's final report in 1999. Sample sizes reported in four leading APA journals in 1955, 1977, 1995, and 2006 were compared using nonparametric statistics, while data from the last two waves were fit to a hierarchical generalized linear growth model for more in-depth analysis. Overall, results indicate that the recommendations for increasing sample sizes have not been integrated in core psychological research, although results slightly vary by field. This and other implications are discussed in the context of current methodological critique and practice.

Accounting for between-study variation in incremental net benefit in value of information methodology.

PubMed

Willan, Andrew R; Eckermann, Simon

2012-10-01

Previous applications of value of information methods for determining optimal sample size in randomized clinical trials have assumed no between-study variation in mean incremental net benefit. By adopting a hierarchical model, we provide a solution for determining optimal sample size with this assumption relaxed. The solution is illustrated with two examples from the literature. Expected net gain increases with increasing between-study variation, reflecting the increased uncertainty in incremental net benefit and reduced extent to which data are borrowed from previous evidence. Hence, a trial can become optimal where current evidence is sufficient assuming no between-study variation. However, despite the expected net gain increasing, the optimal sample size in the illustrated examples is relatively insensitive to the amount of between-study variation. Further percentage losses in expected net gain were small even when choosing sample sizes that reflected widely different between-study variation. Copyright © 2011 John Wiley & Sons, Ltd.

Statistical Analysis Techniques for Small Sample Sizes

NASA Technical Reports Server (NTRS)

Navard, S. E.

1984-01-01

The small sample sizes problem which is encountered when dealing with analysis of space-flight data is examined. Because of such a amount of data available, careful analyses are essential to extract the maximum amount of information with acceptable accuracy. Statistical analysis of small samples is described. The background material necessary for understanding statistical hypothesis testing is outlined and the various tests which can be done on small samples are explained. Emphasis is on the underlying assumptions of each test and on considerations needed to choose the most appropriate test for a given type of analysis.

Some physical properties of Apollo 12 lunar samples

NASA Technical Reports Server (NTRS)

Gold, T.; Oleary, B. T.; Campbell, M.

1971-01-01

The size distribution of the lunar fines is measured, and small but significant differences are found between the Apollo 11 and 12 samples as well as among the Apollo 12 core samples. The observed differences in grain size distribtuion in the core samples are related to surface transportation processes, and the importance of a sedimentation process versus meteoritic impact gardening of the mare grounds is discussed. The optical and the radio frequency electrical properties are measured and are also found to differ only slightly from Apollo 11 results.

Sample size allocation for food item radiation monitoring and safety inspection.

PubMed

Seto, Mayumi; Uriu, Koichiro

2015-03-01

The objective of this study is to identify a procedure for determining sample size allocation for food radiation inspections of more than one food item to minimize the potential risk to consumers of internal radiation exposure. We consider a simplified case of food radiation monitoring and safety inspection in which a risk manager is required to monitor two food items, milk and spinach, in a contaminated area. Three protocols for food radiation monitoring with different sample size allocations were assessed by simulating random sampling and inspections of milk and spinach in a conceptual monitoring site. Distributions of (131)I and radiocesium concentrations were determined in reference to (131)I and radiocesium concentrations detected in Fukushima prefecture, Japan, for March and April 2011. The results of the simulations suggested that a protocol that allocates sample size to milk and spinach based on the estimation of (131)I and radiocesium concentrations using the apparent decay rate constants sequentially calculated from past monitoring data can most effectively minimize the potential risks of internal radiation exposure. © 2014 Society for Risk Analysis.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

USGS Publications Warehouse

Keiter, David A.; Cunningham, Fred L.; Rhodes, Olin E.; Irwin, Brian J.; Beasley, James

2016-01-01

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keiter, David A.; Cunningham, Fred L.; Rhodes, Jr., Olin E.

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocolsmore » with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig ( Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. In conclusion, knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.« less

Optimization of Scat Detection Methods for a Social Ungulate, the Wild Pig, and Experimental Evaluation of Factors Affecting Detection of Scat.

PubMed

Keiter, David A; Cunningham, Fred L; Rhodes, Olin E; Irwin, Brian J; Beasley, James C

2016-01-01

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocols with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig (Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. Knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.

Optimization of scat detection methods for a social ungulate, the wild pig, and experimental evaluation of factors affecting detection of scat

DOE PAGES

Keiter, David A.; Cunningham, Fred L.; Rhodes, Jr., Olin E.; ...

2016-05-25

Collection of scat samples is common in wildlife research, particularly for genetic capture-mark-recapture applications. Due to high degradation rates of genetic material in scat, large numbers of samples must be collected to generate robust estimates. Optimization of sampling approaches to account for taxa-specific patterns of scat deposition is, therefore, necessary to ensure sufficient sample collection. While scat collection methods have been widely studied in carnivores, research to maximize scat collection and noninvasive sampling efficiency for social ungulates is lacking. Further, environmental factors or scat morphology may influence detection of scat by observers. We contrasted performance of novel radial search protocolsmore » with existing adaptive cluster sampling protocols to quantify differences in observed amounts of wild pig ( Sus scrofa) scat. We also evaluated the effects of environmental (percentage of vegetative ground cover and occurrence of rain immediately prior to sampling) and scat characteristics (fecal pellet size and number) on the detectability of scat by observers. We found that 15- and 20-m radial search protocols resulted in greater numbers of scats encountered than the previously used adaptive cluster sampling approach across habitat types, and that fecal pellet size, number of fecal pellets, percent vegetative ground cover, and recent rain events were significant predictors of scat detection. Our results suggest that use of a fixed-width radial search protocol may increase the number of scats detected for wild pigs, or other social ungulates, allowing more robust estimation of population metrics using noninvasive genetic sampling methods. Further, as fecal pellet size affected scat detection, juvenile or smaller-sized animals may be less detectable than adult or large animals, which could introduce bias into abundance estimates. In conclusion, knowledge of relationships between environmental variables and scat detection may allow researchers to optimize sampling protocols to maximize utility of noninvasive sampling for wild pigs and other social ungulates.« less

Controlled synthesis and luminescence properties of CaMoO4:Eu3+ microcrystals

NASA Astrophysics Data System (ADS)

Xie, Ying; Ma, Siming; Wang, Yu; Xu, Mai; Lu, Chengxi; Xiao, Linjiu; Deng, Shuguang

2018-03-01

Pure tetragonal-phased Ca0.9MoO4:0.1Eu3+ (CaMoO4:Eu3+) microcrystals with varying particle sizes were prepared via a co-deposition in water/oil (w/o) phase method. The particle sizes of as-prepared samples were controlled by calcination temperature and calcination time, and the crystallinity of the samples enhances with increasing particle size. The luminescence properties of CaMoO4:Eu3+ microcrystals were studied with varying particle size. The results reveal that the intensity of emission spectra of the CaMoO4:Eu3+ samples increases with increasing particle size, and they have closely correlation with each other. It is the same with the luminescence lifetime. The luminescence lifetime of the CaMoO4:Eu3+ samples decreases from 0.637 ms to 0.447 ms with increasing particle size from 0.12 μm to 1.79 μm, respectively. This study not only provides information for size-dependent luminescence properties of CaMoO4:Eu3+ but also gives a reference for potential applications in high voltage electric porcelain material.

Multi-passes warm rolling of AZ31 magnesium alloy, effect on evaluation of texture, microstructure, grain size and hardness

NASA Astrophysics Data System (ADS)

Kamran, J.; Hasan, B. A.; Tariq, N. H.; Izhar, S.; Sarwar, M.

2014-06-01

In this study the effect of multi-passes warm rolling of AZ31 magnesium alloy on texture, microstructure, grain size variation and hardness of as cast sample (A) and two rolled samples (B & C) taken from different locations of the as-cast ingot was investigated. The purpose was to enhance the formability of AZ31 alloy in order to help manufacturability. It was observed that multi-passes warm rolling (250°C to 350°C) of samples B & C with initial thickness 7.76mm and 7.73 mm was successfully achieved up to 85% reduction without any edge or surface cracks in ten steps with a total of 26 passes. The step numbers 1 to 4 consist of 5, 2, 11 and 3 passes respectively, the remaining steps 5 to 10 were single pass rolls. In each discrete step a fixed roll gap is used in a way that true strain per step increases very slowly from 0.0067 in the first step to 0.7118 in the 26th step. Both samples B & C showed very similar behavior after 26th pass and were successfully rolled up to 85% thickness reduction. However, during 10th step (27th pass) with a true strain value of 0.772 the sample B experienced very severe surface as well as edge cracks. Sample C was therefore not rolled for the 10th step and retained after 26 passes. Both samples were studied in terms of their basal texture, microstructure, grain size and hardness. Sample C showed an equiaxed grain structure after 85% total reduction. The equiaxed grain structure of sample C may be due to the effective involvement of dynamic recrystallization (DRX) which led to formation of these grains with relatively low misorientations with respect to the parent as cast grains. The sample B on the other hand showed a microstructure in which all the grains were elongated along the rolling direction (RD) after 90 % total reduction and DRX could not effectively play its role due to heavy strain and lack of plastic deformation systems. The microstructure of as cast sample showed a near-random texture (mrd 4.3), with average grain size of 44 & micro-hardness of 52 Hv. The grain size of sample B and C was 14μm and 27μm respectively and mrd intensity of basal texture was 5.34 and 5.46 respectively. The hardness of sample B and C came out to be 91 and 66 Hv respectively due to reduction in grain size and followed the well known Hall-Petch relationship.

Finite element and analytical solutions for van der Pauw and four-point probe correction factors when multiple non-ideal measurement conditions coexist

NASA Astrophysics Data System (ADS)

Reveil, Mardochee; Sorg, Victoria C.; Cheng, Emily R.; Ezzyat, Taha; Clancy, Paulette; Thompson, Michael O.

2017-09-01

This paper presents an extensive collection of calculated correction factors that account for the combined effects of a wide range of non-ideal conditions often encountered in realistic four-point probe and van der Pauw experiments. In this context, "non-ideal conditions" refer to conditions that deviate from the assumptions on sample and probe characteristics made in the development of these two techniques. We examine the combined effects of contact size and sample thickness on van der Pauw measurements. In the four-point probe configuration, we examine the combined effects of varying the sample's lateral dimensions, probe placement, and sample thickness. We derive an analytical expression to calculate correction factors that account, simultaneously, for finite sample size and asymmetric probe placement in four-point probe experiments. We provide experimental validation of the analytical solution via four-point probe measurements on a thin film rectangular sample with arbitrary probe placement. The finite sample size effect is very significant in four-point probe measurements (especially for a narrow sample) and asymmetric probe placement only worsens such effects. The contribution of conduction in multilayer samples is also studied and found to be substantial; hence, we provide a map of the necessary correction factors. This library of correction factors will enable the design of resistivity measurements with improved accuracy and reproducibility over a wide range of experimental conditions.

Field substitution of nonresponders can maintain sample size and structure without altering survey estimates-the experience of the Italian behavioral risk factors surveillance system (PASSI).

PubMed

Baldissera, Sandro; Ferrante, Gianluigi; Quarchioni, Elisa; Minardi, Valentina; Possenti, Valentina; Carrozzi, Giuliano; Masocco, Maria; Salmaso, Stefania

2014-04-01

Field substitution of nonrespondents can be used to maintain the planned sample size and structure in surveys but may introduce additional bias. Sample weighting is suggested as the preferable alternative; however, limited empirical evidence exists comparing the two methods. We wanted to assess the impact of substitution on surveillance results using data from Progressi delle Aziende Sanitarie per la Salute in Italia-Progress by Local Health Units towards a Healthier Italy (PASSI). PASSI is conducted by Local Health Units (LHUs) through telephone interviews of stratified random samples of residents. Nonrespondents are replaced with substitutes randomly preselected in the same LHU stratum. We compared the weighted estimates obtained in the original PASSI sample (used as a reference) and in the substitutes' sample. The differences were evaluated using a Wald test. In 2011, 50,697 units were selected: 37,252 were from the original sample and 13,445 were substitutes; 37,162 persons were interviewed. The initially planned size and demographic composition were restored. No significant differences in the estimates between the original and the substitutes' sample were found. In our experience, field substitution is an acceptable method for dealing with nonresponse, maintaining the characteristics of the original sample without affecting the results. This evidence can support appropriate decisions about planning and implementing a surveillance system. Copyright © 2014 Elsevier Inc. All rights reserved.

Finite element and analytical solutions for van der Pauw and four-point probe correction factors when multiple non-ideal measurement conditions coexist.

PubMed

Reveil, Mardochee; Sorg, Victoria C; Cheng, Emily R; Ezzyat, Taha; Clancy, Paulette; Thompson, Michael O

2017-09-01

This paper presents an extensive collection of calculated correction factors that account for the combined effects of a wide range of non-ideal conditions often encountered in realistic four-point probe and van der Pauw experiments. In this context, "non-ideal conditions" refer to conditions that deviate from the assumptions on sample and probe characteristics made in the development of these two techniques. We examine the combined effects of contact size and sample thickness on van der Pauw measurements. In the four-point probe configuration, we examine the combined effects of varying the sample's lateral dimensions, probe placement, and sample thickness. We derive an analytical expression to calculate correction factors that account, simultaneously, for finite sample size and asymmetric probe placement in four-point probe experiments. We provide experimental validation of the analytical solution via four-point probe measurements on a thin film rectangular sample with arbitrary probe placement. The finite sample size effect is very significant in four-point probe measurements (especially for a narrow sample) and asymmetric probe placement only worsens such effects. The contribution of conduction in multilayer samples is also studied and found to be substantial; hence, we provide a map of the necessary correction factors. This library of correction factors will enable the design of resistivity measurements with improved accuracy and reproducibility over a wide range of experimental conditions.

Angiographic core laboratory reproducibility analyses: implications for planning clinical trials using coronary angiography and left ventriculography end-points.

PubMed

Steigen, Terje K; Claudio, Cheryl; Abbott, David; Schulzer, Michael; Burton, Jeff; Tymchak, Wayne; Buller, Christopher E; John Mancini, G B

2008-06-01

To assess reproducibility of core laboratory performance and impact on sample size calculations. Little information exists about overall reproducibility of core laboratories in contradistinction to performance of individual technicians. Also, qualitative parameters are being adjudicated increasingly as either primary or secondary end-points. The comparative impact of using diverse indexes on sample sizes has not been previously reported. We compared initial and repeat assessments of five quantitative parameters [e.g., minimum lumen diameter (MLD), ejection fraction (EF), etc.] and six qualitative parameters [e.g., TIMI myocardial perfusion grade (TMPG) or thrombus grade (TTG), etc.], as performed by differing technicians and separated by a year or more. Sample sizes were calculated from these results. TMPG and TTG were also adjudicated by a second core laboratory. MLD and EF were the most reproducible, yielding the smallest sample size calculations, whereas percent diameter stenosis and centerline wall motion require substantially larger trials. Of the qualitative parameters, all except TIMI flow grade gave reproducibility characteristics yielding sample sizes of many 100's of patients. Reproducibility of TMPG and TTG was only moderately good both within and between core laboratories, underscoring an intrinsic difficulty in assessing these. Core laboratories can be shown to provide reproducibility performance that is comparable to performance commonly ascribed to individual technicians. The differences in reproducibility yield huge differences in sample size when comparing quantitative and qualitative parameters. TMPG and TTG are intrinsically difficult to assess and conclusions based on these parameters should arise only from very large trials.

Minimum and Maximum Times Required to Obtain Representative Suspended Sediment Samples

NASA Astrophysics Data System (ADS)

Gitto, A.; Venditti, J. G.; Kostaschuk, R.; Church, M. A.

2014-12-01

Bottle sampling is a convenient method of obtaining suspended sediment measurements for the development of sediment budgets. While these methods are generally considered to be reliable, recent analysis of depth-integrated sampling has identified considerable uncertainty in measurements of grain-size concentration between grain-size classes of multiple samples. Point-integrated bottle sampling is assumed to represent the mean concentration of suspended sediment but the uncertainty surrounding this method is not well understood. Here we examine at-a-point variability in velocity, suspended sediment concentration, grain-size distribution, and grain-size moments to determine if traditional point-integrated methods provide a representative sample of suspended sediment. We present continuous hour-long observations of suspended sediment from the sand-bedded portion of the Fraser River at Mission, British Columbia, Canada, using a LISST laser-diffraction instrument. Spectral analysis suggests that there are no statistically significant peak in energy density, suggesting the absence of periodic fluctuations in flow and suspended sediment. However, a slope break in the spectra at 0.003 Hz corresponds to a period of 5.5 minutes. This coincides with the threshold between large-scale turbulent eddies that scale with channel width/mean velocity and hydraulic phenomena related to channel dynamics. This suggests that suspended sediment samples taken over a period longer than 5.5 minutes incorporate variability that is larger scale than turbulent phenomena in this channel. Examination of 5.5-minute periods of our time series indicate that ~20% of the time a stable mean value of volumetric concentration is reached within 30 seconds, a typical bottle sample duration. In ~12% of measurements a stable mean was not reached over the 5.5 minute sample duration. The remaining measurements achieve a stable mean in an even distribution over the intervening interval.

Validation of abundance estimates from mark–recapture and removal techniques for rainbow trout captured by electrofishing in small streams

USGS Publications Warehouse

Rosenberger, Amanda E.; Dunham, Jason B.

2005-01-01

Estimation of fish abundance in streams using the removal model or the Lincoln - Peterson mark - recapture model is a common practice in fisheries. These models produce misleading results if their assumptions are violated. We evaluated the assumptions of these two models via electrofishing of rainbow trout Oncorhynchus mykiss in central Idaho streams. For one-, two-, three-, and four-pass sampling effort in closed sites, we evaluated the influences of fish size and habitat characteristics on sampling efficiency and the accuracy of removal abundance estimates. We also examined the use of models to generate unbiased estimates of fish abundance through adjustment of total catch or biased removal estimates. Our results suggested that the assumptions of the mark - recapture model were satisfied and that abundance estimates based on this approach were unbiased. In contrast, the removal model assumptions were not met. Decreasing sampling efficiencies over removal passes resulted in underestimated population sizes and overestimates of sampling efficiency. This bias decreased, but was not eliminated, with increased sampling effort. Biased removal estimates based on different levels of effort were highly correlated with each other but were less correlated with unbiased mark - recapture estimates. Stream size decreased sampling efficiency, and stream size and instream wood increased the negative bias of removal estimates. We found that reliable estimates of population abundance could be obtained from models of sampling efficiency for different levels of effort. Validation of abundance estimates requires extra attention to routine sampling considerations but can help fisheries biologists avoid pitfalls associated with biased data and facilitate standardized comparisons among studies that employ different sampling methods.

A comparison of two sampling approaches for assessing the urban forest canopy cover from aerial photography.

Treesearch

Ucar Zennure; Pete Bettinger; Krista Merry; Jacek Siry; J.M. Bowker

2016-01-01

Two different sampling approaches for estimating urban tree canopy cover were applied to two medium-sized cities in the United States, in conjunction with two freely available remotely sensed imagery products. A random point-based sampling approach, which involved 1000 sample points, was compared against a plot/grid sampling (cluster sampling) approach that involved a...

Sampling through time and phylodynamic inference with coalescent and birth–death models

PubMed Central

Volz, Erik M.; Frost, Simon D. W.

2014-01-01

Many population genetic models have been developed for the purpose of inferring population size and growth rates from random samples of genetic data. We examine two popular approaches to this problem, the coalescent and the birth–death-sampling model (BDM), in the context of estimating population size and birth rates in a population growing exponentially according to the birth–death branching process. For sequences sampled at a single time, we found the coalescent and the BDM gave virtually indistinguishable results in terms of the growth rates and fraction of the population sampled, even when sampling from a small population. For sequences sampled at multiple time points, we find that the birth–death model estimators are subject to large bias if the sampling process is misspecified. Since BDMs incorporate a model of the sampling process, we show how much of the statistical power of BDMs arises from the sequence of sample times and not from the genealogical tree. This motivates the development of a new coalescent estimator, which is augmented with a model of the known sampling process and is potentially more precise than the coalescent that does not use sample time information. PMID:25401173

QA/QC requirements for physical properties sampling and analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Innis, B.E.

1993-07-21

This report presents results of an assessment of the available information concerning US Environmental Protection Agency (EPA) quality assurance/quality control (QA/QC) requirements and guidance applicable to sampling, handling, and analyzing physical parameter samples at Comprehensive Environmental Restoration, Compensation, and Liability Act (CERCLA) investigation sites. Geotechnical testing laboratories measure the following physical properties of soil and sediment samples collected during CERCLA remedial investigations (RI) at the Hanford Site: moisture content, grain size by sieve, grain size by hydrometer, specific gravity, bulk density/porosity, saturated hydraulic conductivity, moisture retention, unsaturated hydraulic conductivity, and permeability of rocks by flowing air. Geotechnical testing laboratories alsomore » measure the following chemical parameters of soil and sediment samples collected during Hanford Site CERCLA RI: calcium carbonate and saturated column leach testing. Physical parameter data are used for (1) characterization of vadose and saturated zone geology and hydrogeology, (2) selection of monitoring well screen sizes, (3) to support modeling and analysis of the vadose and saturated zones, and (4) for engineering design. The objectives of this report are to determine the QA/QC levels accepted in the EPA Region 10 for the sampling, handling, and analysis of soil samples for physical parameters during CERCLA RI.« less

Understanding the cluster randomised crossover design: a graphical illustraton of the components of variation and a sample size tutorial.

PubMed

Arnup, Sarah J; McKenzie, Joanne E; Hemming, Karla; Pilcher, David; Forbes, Andrew B

2017-08-15

In a cluster randomised crossover (CRXO) design, a sequence of interventions is assigned to a group, or 'cluster' of individuals. Each cluster receives each intervention in a separate period of time, forming 'cluster-periods'. Sample size calculations for CRXO trials need to account for both the cluster randomisation and crossover aspects of the design. Formulae are available for the two-period, two-intervention, cross-sectional CRXO design, however implementation of these formulae is known to be suboptimal. The aims of this tutorial are to illustrate the intuition behind the design; and provide guidance on performing sample size calculations. Graphical illustrations are used to describe the effect of the cluster randomisation and crossover aspects of the design on the correlation between individual responses in a CRXO trial. Sample size calculations for binary and continuous outcomes are illustrated using parameters estimated from the Australia and New Zealand Intensive Care Society - Adult Patient Database (ANZICS-APD) for patient mortality and length(s) of stay (LOS). The similarity between individual responses in a CRXO trial can be understood in terms of three components of variation: variation in cluster mean response; variation in the cluster-period mean response; and variation between individual responses within a cluster-period; or equivalently in terms of the correlation between individual responses in the same cluster-period (within-cluster within-period correlation, WPC), and between individual responses in the same cluster, but in different periods (within-cluster between-period correlation, BPC). The BPC lies between zero and the WPC. When the WPC and BPC are equal the precision gained by crossover aspect of the CRXO design equals the precision lost by cluster randomisation. When the BPC is zero there is no advantage in a CRXO over a parallel-group cluster randomised trial. Sample size calculations illustrate that small changes in the specification of the WPC or BPC can increase the required number of clusters. By illustrating how the parameters required for sample size calculations arise from the CRXO design and by providing guidance on both how to choose values for the parameters and perform the sample size calculations, the implementation of the sample size formulae for CRXO trials may improve.

Sampling of suspended particulate matter using particle traps in the Rhône River: Relevance and representativeness for the monitoring of contaminants.

PubMed

Masson, M; Angot, H; Le Bescond, C; Launay, M; Dabrin, A; Miège, C; Le Coz, J; Coquery, M

2018-05-10

Monitoring hydrophobic contaminants in surface freshwaters requires measuring contaminant concentrations in the particulate fraction (sediment or suspended particulate matter, SPM) of the water column. Particle traps (PTs) have been recently developed to sample SPM as cost-efficient, easy to operate and time-integrative tools. But the representativeness of SPM collected with PTs is not fully understood, notably in terms of grain size distribution and particulate organic carbon (POC) content, which could both skew particulate contaminant concentrations. The aim of this study was to evaluate the representativeness of SPM characteristics (i.e. grain size distribution and POC content) and associated contaminants (i.e. polychlorinated biphenyls, PCBs; mercury, Hg) in samples collected in a large river using PTs for differing hydrological conditions. Samples collected using PTs (n = 74) were compared with samples collected during the same time period by continuous flow centrifugation (CFC). The grain size distribution of PT samples shifted with increasing water discharge: the proportion of very fine silts (2-6 μm) decreased while that of coarse silts (27-74 μm) increased. Regardless of water discharge, POC contents were different likely due to integration by PT of high POC-content phytoplankton blooms or low POC-content flood events. Differences in PCBs and Hg concentrations were usually within the range of analytical uncertainties and could not be related to grain size or POC content shifts. Occasional Hg-enriched inputs may have led to higher Hg concentrations in a few PT samples (n = 4) which highlights the time-integrative capacity of the PTs. The differences of annual Hg and PCB fluxes calculated either from PT samples or CFC samples were generally below 20%. Despite some inherent limitations (e.g. grain size distribution bias), our findings suggest that PT sampling is a valuable technique to assess reliable spatial and temporal trends of particulate contaminants such as PCBs and Hg within a river monitoring network. Copyright © 2018 Elsevier B.V. All rights reserved.

Sampling hazelnuts for aflatoxin: uncertainty associated with sampling, sample preparation, and analysis.

PubMed

Ozay, Guner; Seyhan, Ferda; Yilmaz, Aysun; Whitaker, Thomas B; Slate, Andrew B; Giesbrecht, Francis

2006-01-01

The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a high-performance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.

Phase transformations in a Cu−Cr alloy induced by high pressure torsion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Korneva, Anna, E-mail: a.korniewa@imim.pl; Straumal, Boris; Institut für Nanotechnologie, Karlsruher Institut für Technologie, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen

2016-04-15

Phase transformations induced by high pressure torsion (HPT) at room temperature in two samples of the Cu-0.86 at.% Cr alloy, pre-annealed at 550 °C and 1000 °C, were studied in order to obtain two different initial states for the HPT procedure. Observation of microstructure of the samples before HPT revealed that the sample annealed at 550 °C contained two types of Cr precipitates in the Cu matrix: large particles (size about 500 nm) and small ones (size about 70 nm). The sample annealed at 1000 °C showed only a little fraction of Cr precipitates (size about 2 μm). The subsequentmore » HPT process resulted in the partial dissolution of Cr precipitates in the first sample and dissolution of Cr precipitates with simultaneous decomposition of the supersaturated solid solution in another. However, the resulting microstructure of the samples after HPT was very similar from the standpoint of grain size, phase composition, texture analysis and hardness measurements. - Highlights: • Cu−Cr alloy with two different initial states was deformed by HPT. • Phase transformations in the deformed materials were studied. • SEM, TEM and X-ray diffraction techniques were used for microstructure analysis. • HPT leads to formation the same microstructure independent of the initial state.« less

Seasonal variation in size-dependent survival of juvenile Atlantic salmon (Salmo salar): Performance of multistate capture-mark-recapture models

USGS Publications Warehouse

Letcher, B.H.; Horton, G.E.

2008-01-01

We estimated the magnitude and shape of size-dependent survival (SDS) across multiple sampling intervals for two cohorts of stream-dwelling Atlantic salmon (Salmo salar) juveniles using multistate capture-mark-recapture (CMR) models. Simulations designed to test the effectiveness of multistate models for detecting SDS in our system indicated that error in SDS estimates was low and that both time-invariant and time-varying SDS could be detected with sample sizes of >250, average survival of >0.6, and average probability of capture of >0.6, except for cases of very strong SDS. In the field (N ??? 750, survival 0.6-0.8 among sampling intervals, probability of capture 0.6-0.8 among sampling occasions), about one-third of the sampling intervals showed evidence of SDS, with poorer survival of larger fish during the age-2+ autumn and quadratic survival (opposite direction between cohorts) during age-1+ spring. The varying magnitude and shape of SDS among sampling intervals suggest a potential mechanism for the maintenance of the very wide observed size distributions. Estimating SDS using multistate CMR models appears complementary to established approaches, can provide estimates with low error, and can be used to detect intermittent SDS. ?? 2008 NRC Canada.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features.

PubMed

McDonald, Linda S; Panozzo, Joseph F; Salisbury, Phillip A; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features

PubMed Central

McDonald, Linda S.; Panozzo, Joseph F.; Salisbury, Phillip A.; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective. PMID:27176469

Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data.

PubMed

Bhaskar, Anand; Wang, Y X Rachel; Song, Yun S

2015-02-01

With the recent increase in study sample sizes in human genetics, there has been growing interest in inferring historical population demography from genomic variation data. Here, we present an efficient inference method that can scale up to very large samples, with tens or hundreds of thousands of individuals. Specifically, by utilizing analytic results on the expected frequency spectrum under the coalescent and by leveraging the technique of automatic differentiation, which allows us to compute gradients exactly, we develop a very efficient algorithm to infer piecewise-exponential models of the historical effective population size from the distribution of sample allele frequencies. Our method is orders of magnitude faster than previous demographic inference methods based on the frequency spectrum. In addition to inferring demography, our method can also accurately estimate locus-specific mutation rates. We perform extensive validation of our method on simulated data and show that it can accurately infer multiple recent epochs of rapid exponential growth, a signal that is difficult to pick up with small sample sizes. Lastly, we use our method to analyze data from recent sequencing studies, including a large-sample exome-sequencing data set of tens of thousands of individuals assayed at a few hundred genic regions. © 2015 Bhaskar et al.; Published by Cold Spring Harbor Laboratory Press.

Considerations for throughfall chemistry sample-size determination

Treesearch

Pamela J. Edwards; Paul Mohai; Howard G. Halverson; David R. DeWalle

1989-01-01

Both the number of trees sampled per species and the number of sampling points under each tree are important throughfall sampling considerations. Chemical loadings obtained from an urban throughfall study were used to evaluate the relative importance of both of these sampling factors in tests for determining species' differences. Power curves for detecting...

Using Candy Samples to Learn about Sampling Techniques and Statistical Data Evaluation

ERIC Educational Resources Information Center

Canaes, Larissa S.; Brancalion, Marcel L.; Rossi, Adriana V.; Rath, Susanne

2008-01-01

A classroom exercise for undergraduate and beginning graduate students that takes about one class period is proposed and discussed. It is an easy, interesting exercise that demonstrates important aspects of sampling techniques (sample amount, particle size, and the representativeness of the sample in relation to the bulk material). The exercise…

An Investigation of the Sampling Distribution of the Congruence Coefficient.

ERIC Educational Resources Information Center

Broadbooks, Wendy J.; Elmore, Patricia B.

This study developed and investigated an empirical sampling distribution of the congruence coefficient. The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model and…

Effect of Sampling Plans on the Risk of Escherichia coli O157 Illness.

PubMed

Kiermeier, Andreas; Sumner, John; Jenson, Ian

2015-07-01

Australia exports about 150,000 to 200,000 tons of manufacturing beef to the United States annually. Each lot is tested for Escherichia coli O157 using the N-60 sampling protocol, where 60 small pieces of surface meat from each lot of production are tested. A risk assessment of E. coli O157 illness from the consumption of hamburgers made from Australian manufacturing meat formed the basis to evaluate the effect of sample size and amount on the number of illnesses predicted. The sampling plans evaluated included no sampling (resulting in an estimated 55.2 illnesses per annum), the current N-60 plan (50.2 illnesses), N-90 (49.6 illnesses), N-120 (48.4 illnesses), and a more stringent N-60 sampling plan taking five 25-g samples from each of 12 cartons (47.4 illnesses per annum). While sampling may detect some highly contaminated lots, it does not guarantee that all such lots are removed from commerce. It is concluded that increasing the sample size or sample amount from the current N-60 plan would have a very small public health effect.

Developing optimum sample size and multistage sampling plans for Lobesia botrana (Lepidoptera: Tortricidae) larval infestation and injury in northern Greece.

PubMed

Ifoulis, A A; Savopoulou-Soultani, M

2006-10-01

The purpose of this research was to quantify the spatial pattern and develop a sampling program for larvae of Lobesia botrana Denis and Schiffermüller (Lepidoptera: Tortricidae), an important vineyard pest in northern Greece. Taylor's power law and Iwao's patchiness regression were used to model the relationship between the mean and the variance of larval counts. Analysis of covariance was carried out, separately for infestation and injury, with combined second and third generation data, for vine and half-vine sample units. Common regression coefficients were estimated to permit use of the sampling plan over a wide range of conditions. Optimum sample sizes for infestation and injury, at three levels of precision, were developed. An investigation of a multistage sampling plan with a nested analysis of variance showed that if the goal of sampling is focusing on larval infestation, three grape clusters should be sampled in a half-vine; if the goal of sampling is focusing on injury, then two grape clusters per half-vine are recommended.

Measuring the specific surface area of natural and manmade glasses: effects of formation process, morphology, and particle size

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papelis, Charalambos; Um, Wooyong; Russel, Charles E.

2003-03-28

The specific surface area of natural and manmade solid materials is a key parameter controlling important interfacial processes in natural environments and engineered systems, including dissolution reactions and sorption processes at solid-fluid interfaces. To improve our ability to quantify the release of trace elements trapped in natural glasses, the release of hazardous compounds trapped in manmade glasses, or the release of radionuclides from nuclear melt glass, we measured the specific surface area of natural and manmade glasses as a function of particle size, morphology, and composition. Volcanic ash, volcanic tuff, tektites, obsidian glass, and in situ vitrified rock were analyzed.more » Specific surface area estimates were obtained using krypton as gas adsorbent and the BET model. The range of surface areas measured exceeded three orders of magnitude. A tektite sample had the highest surface area (1.65 m2/g), while one of the samples of in situ vitrified rock had the lowest surf ace area (0.0016 m2/g). The specific surface area of the samples was a function of particle size, decreasing with increasing particle size. Different types of materials, however, showed variable dependence on particle size, and could be assigned to one of three distinct groups: (1) samples with low surface area dependence on particle size and surface areas approximately two orders of magnitude higher than the surface area of smooth spheres of equivalent size. The specific surface area of these materials was attributed mostly to internal porosity and surface roughness. (2) samples that showed a trend of decreasing surface area dependence on particle size as the particle size increased. The minimum specific surface area of these materials was between 0.1 and 0.01 m2/g and was also attributed to internal porosity and surface roughness. (3) samples whose surface area showed a monotonic decrease with increasing particle size, never reaching an ultimate surface area limit within the particle size range examined. The surface area results were consistent with particle morphology, examined by scanning electron microscopy, and have significant implications for the release of radionuclides and toxic metals in the environment.« less

In vitro inflammatory and cytotoxic effects of size-segregated particulate samples collected during long-range transport of wildfire smoke to Helsinki.

PubMed

Jalava, Pasi I; Salonen, Raimo O; Hälinen, Arja I; Penttinen, Piia; Pennanen, Arto S; Sillanpää, Markus; Sandell, Erik; Hillamo, Risto; Hirvonen, Maija-Riitta

2006-09-15

The impact of long-range transport (LRT) episodes of wildfire smoke on the inflammogenic and cytotoxic activity of urban air particles was investigated in the mouse RAW 264.7 macrophages. The particles were sampled in four size ranges using a modified Harvard high-volume cascade impactor, and the samples were chemically characterized for identification of different emission sources. The particulate mass concentration in the accumulation size range (PM(1-0.2)) was highly increased during two LRT episodes, but the contents of total and genotoxic polycyclic aromatic hydrocarbons (PAH) in collected particulate samples were only 10-25% of those in the seasonal average sample. The ability of coarse (PM(10-2.5)), intermodal size range (PM(2.5-1)), PM(1-0.2) and ultrafine (PM(0.2)) particles to cause cytokine production (TNFalpha, IL-6, MIP-2) reduced along with smaller particle size, but the size range had a much smaller impact on induced nitric oxide (NO) production and cytotoxicity or apoptosis. The aerosol particles collected during LRT episodes had a substantially lower activity in cytokine production than the corresponding particles of the seasonal average period, which is suggested to be due to chemical transformation of the organic fraction during aging. However, the episode events were associated with enhanced inflammogenic and cytotoxic activities per inhaled cubic meter of air due to the greatly increased particulate mass concentration in the accumulation size range, which may have public health implications.

[An investigation of the statistical power of the effect size in randomized controlled trials for the treatment of patients with type 2 diabetes mellitus using Chinese medicine].

PubMed

Ma, Li-Xin; Liu, Jian-Ping

2012-01-01

To investigate whether the power of the effect size was based on adequate sample size in randomized controlled trials (RCTs) for the treatment of patients with type 2 diabetes mellitus (T2DM) using Chinese medicine. China Knowledge Resource Integrated Database (CNKI), VIP Database for Chinese Technical Periodicals (VIP), Chinese Biomedical Database (CBM), and Wangfang Data were systematically recruited using terms like "Xiaoke" or diabetes, Chinese herbal medicine, patent medicine, traditional Chinese medicine, randomized, controlled, blinded, and placebo-controlled. Limitation was set on the intervention course > or = 3 months in order to identify the information of outcome assessement and the sample size. Data collection forms were made according to the checking lists found in the CONSORT statement. Independent double data extractions were performed on all included trials. The statistical power of the effects size for each RCT study was assessed using sample size calculation equations. (1) A total of 207 RCTs were included, including 111 superiority trials and 96 non-inferiority trials. (2) Among the 111 superiority trials, fasting plasma glucose (FPG) and glycosylated hemoglobin HbA1c (HbA1c) outcome measure were reported in 9% and 12% of the RCTs respectively with the sample size > 150 in each trial. For the outcome of HbA1c, only 10% of the RCTs had more than 80% power. For FPG, 23% of the RCTs had more than 80% power. (3) In the 96 non-inferiority trials, the outcomes FPG and HbA1c were reported as 31% and 36% respectively. These RCTs had a samples size > 150. For HbA1c only 36% of the RCTs had more than 80% power. For FPG, only 27% of the studies had more than 80% power. The sample size for statistical analysis was distressingly low and most RCTs did not achieve 80% power. In order to obtain a sufficient statistic power, it is recommended that clinical trials should establish clear research objective and hypothesis first, and choose scientific and evidence-based study design and outcome measurements. At the same time, calculate required sample size to ensure a precise research conclusion.

Considerations in Forest Growth Estimation Between Two Measurements of Mapped Forest Inventory Plots

Treesearch

Michael T. Thompson

2006-01-01

Several aspects of the enhanced Forest Inventory and Analysis (FIA) program?s national plot design complicate change estimation. The design incorporates up to three separate plot sizes (microplot, subplot, and macroplot) to sample trees of different sizes. Because multiple plot sizes are involved, change estimators designed for polyareal plot sampling, such as those...

Sediment Grain Size Measurements: Is There a Differenc Between Digested and Un-digested Samples? And Does the Organic Carbon of the Sample Play a Role

EPA Science Inventory

Grain size is a physical measurement commonly made in the analysis of many benthic systems. Grain size influences benthic community composition, can influence contaminant loading and can indicate the energy regime of a system. We have recently investigated the relationship betw...

Estimation and applications of size-biased distributions in forestry

Treesearch

Jeffrey H. Gove

2003-01-01

Size-biased distributions arise naturally in several contexts in forestry and ecology. Simple power relationships (e.g. basal area and diameter at breast height) between variables are one such area of interest arising from a modelling perspective. Another, probability proportional to size PPS) sampling, is found in the most widely used methods for sampling standing or...

Efficiency of Sampling and Analysis of Asbestos Fibers on Filter Media: Implications for Exposure Assessment

EPA Science Inventory

To measure airborne asbestos and other fibers, an air sample must represent the actual number and size of fibers. Typically, mixed cellulose ester (MCE, 0.45 or 0.8 µm pore size) and to a much lesser extent, capillary-pore polycarbonate (PC, 0.4 µm pore size) membrane filters are...

A Future Moon Mission: Curatorial Statistics on Regolith Fragments Applicable to Sample Collection by Raking

NASA Technical Reports Server (NTRS)

Allton, J. H.; Bevill, T. J.

2003-01-01

The strategy of raking rock fragments from the lunar regolith as a means of acquiring representative samples has wide support due to science return, spacecraft simplicity (reliability) and economy [3, 4, 5]. While there exists widespread agreement that raking or sieving the bulk regolith is good strategy, there is lively discussion about the minimum sample size. Advocates of consor-tium studies desire fragments large enough to support petrologic and isotopic studies. Fragments from 5 to 10 mm are thought adequate [4, 5]. Yet, Jolliff et al. [6] demonstrated use of 2-4 mm fragments as repre-sentative of larger rocks. Here we make use of cura-torial records and sample catalogs to give a different perspective on minimum sample size for a robotic sample collector.

A new estimator of the discovery probability.

PubMed

Favaro, Stefano; Lijoi, Antonio; Prünster, Igor

2012-12-01

Species sampling problems have a long history in ecological and biological studies and a number of issues, including the evaluation of species richness, the design of sampling experiments, and the estimation of rare species variety, are to be addressed. Such inferential problems have recently emerged also in genomic applications, however, exhibiting some peculiar features that make them more challenging: specifically, one has to deal with very large populations (genomic libraries) containing a huge number of distinct species (genes) and only a small portion of the library has been sampled (sequenced). These aspects motivate the Bayesian nonparametric approach we undertake, since it allows to achieve the degree of flexibility typically needed in this framework. Based on an observed sample of size n, focus will be on prediction of a key aspect of the outcome from an additional sample of size m, namely, the so-called discovery probability. In particular, conditionally on an observed basic sample of size n, we derive a novel estimator of the probability of detecting, at the (n+m+1)th observation, species that have been observed with any given frequency in the enlarged sample of size n+m. Such an estimator admits a closed-form expression that can be exactly evaluated. The result we obtain allows us to quantify both the rate at which rare species are detected and the achieved sample coverage of abundant species, as m increases. Natural applications are represented by the estimation of the probability of discovering rare genes within genomic libraries and the results are illustrated by means of two expressed sequence tags datasets. © 2012, The International Biometric Society.

Comparison of Bottomless Lift Nets and Breder Traps for Sampling Salt-Marsh Nekton

EPA Pesticide Factsheets

Data set contains: the length of mummichogs (Fundulus heteroclitus) caught on lift nets and Breder traps from May to September 2002; the sizes of green crabs caught in the lift nets and Breder traps during same time frame; the mean density and sample size data for each sampling time and each site (3 sites total) for total nekton sampled and total nekton minus shrimp.This dataset is associated with the following publication:Raposa, K., and M. Chintala. Comparison of Bottomless Lift Nets and Breder Traps for Sampling Salt-Marsh Nekton. TRANSACTIONS OF THE AMERICAN FISHERIES SOCIETY. American Fisheries Society, Bethesda, MD, USA, 145(1): 163-172, (2016).

Recent advances of mesoporous materials in sample preparation.

PubMed

Zhao, Liang; Qin, Hongqiang; Wu, Ren'an; Zou, Hanfa

2012-03-09

Sample preparation has been playing an important role in the analysis of complex samples. Mesoporous materials as the promising adsorbents have gained increasing research interest in sample preparation due to their desirable characteristics of high surface area, large pore volume, tunable mesoporous channels with well defined pore-size distribution, controllable wall composition, as well as modifiable surface properties. The aim of this paper is to review the recent advances of mesoporous materials in sample preparation with emphases on extraction of metal ions, adsorption of organic compounds, size selective enrichment of peptides/proteins, specific capture of post-translational peptides/proteins and enzymatic reactor for protein digestion. Copyright © 2011 Elsevier B.V. All rights reserved.

Effects of crystallite size on the structure and magnetism of ferrihydrite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Xiaoming; Zhu, Mengqiang; Koopal, Luuk K.

2015-12-15

The structure and magnetic properties of nano-sized (1.6 to 4.4 nm) ferrihydrite samples are systematically investigated through a combination of X-ray diffraction (XRD), X-ray pair distribution function (PDF), X-ray absorption spectroscopy (XAS) and magnetic analyses. The XRD, PDF and Fe K-edge XAS data of the ferrihydrite samples are all fitted well with the Michel ferrihydrite model, indicating similar local-, medium- and long-range ordered structures. PDF and XAS fitting results indicate that, with increasing crystallite size, the average coordination numbers of Fe–Fe and the unit cell parameter c increase, while Fe2 and Fe3 vacancies and the unit cell parameter a decrease.more » Mössbauer results indicate that the surface layer is relatively disordered, which might have been caused by the random distribution of Fe vacancies. These results support Hiemstra's surface-depletion model in terms of the location of disorder and the variations of Fe2 and Fe3 occupancies with size. Magnetic data indicate that the ferrihydrite samples show antiferromagnetism superimposed with a ferromagnetic-like moment at lower temperatures (100 K and 10 K), but ferrihydrite is paramagnetic at room temperature. In addition, both the magnetization and coercivity decrease with increasing ferrihydrite crystallite size due to strong surface effects in fine-grained ferrihydrites. Smaller ferrihydrite samples show less magnetic hyperfine splitting and a lower unblocking temperature (T B) than larger samples. The dependence of magnetic properties on grain size for nano-sized ferrihydrite provides a practical way to determine the crystallite size of ferrihydrite quantitatively in natural environments or artificial systems.« less

Only pick the right grains: Modelling the bias due to subjective grain-size interval selection for chronometric and fingerprinting approaches.

NASA Astrophysics Data System (ADS)

Dietze, Michael; Fuchs, Margret; Kreutzer, Sebastian

2016-04-01

Many modern approaches of radiometric dating or geochemical fingerprinting rely on sampling sedimentary deposits. A key assumption of most concepts is that the extracted grain-size fraction of the sampled sediment adequately represents the actual process to be dated or the source area to be fingerprinted. However, these assumptions are not always well constrained. Rather, they have to align with arbitrary, method-determined size intervals, such as "coarse grain" or "fine grain" with partly even different definitions. Such arbitrary intervals violate principal process-based concepts of sediment transport and can thus introduce significant bias to the analysis outcome (i.e., a deviation of the measured from the true value). We present a flexible numerical framework (numOlum) for the statistical programming language R that allows quantifying the bias due to any given analysis size interval for different types of sediment deposits. This framework is applied to synthetic samples from the realms of luminescence dating and geochemical fingerprinting, i.e. a virtual reworked loess section. We show independent validation data from artificially dosed and subsequently mixed grain-size proportions and we present a statistical approach (end-member modelling analysis, EMMA) that allows accounting for the effect of measuring the compound dosimetric history or geochemical composition of a sample. EMMA separates polymodal grain-size distributions into the underlying transport process-related distributions and their contribution to each sample. These underlying distributions can then be used to adjust grain-size preparation intervals to minimise the incorporation of "undesired" grain-size fractions.

Optimizing the triple-axis spectrometer PANDA at the MLZ for small samples and complex sample environment conditions

NASA Astrophysics Data System (ADS)

Utschick, C.; Skoulatos, M.; Schneidewind, A.; Böni, P.

2016-11-01

The cold-neutron triple-axis spectrometer PANDA at the neutron source FRM II has been serving an international user community studying condensed matter physics problems. We report on a new setup, improving the signal-to-noise ratio for small samples and pressure cell setups. Analytical and numerical Monte Carlo methods are used for the optimization of elliptic and parabolic focusing guides. They are placed between the monochromator and sample positions, and the flux at the sample is compared to the one achieved by standard monochromator focusing techniques. A 25 times smaller spot size is achieved, associated with a factor of 2 increased intensity, within the same divergence limits, ± 2 ° . This optional neutron focusing guide shall establish a top-class spectrometer for studying novel exotic properties of matter in combination with more stringent sample environment conditions such as extreme pressures associated with small sample sizes.

The use of mini-samples in palaeomagnetism

NASA Astrophysics Data System (ADS)

Böhnel, Harald; Michalk, Daniel; Nowaczyk, Norbert; Naranjo, Gildardo Gonzalez

2009-10-01

Rock cores of ~25 mm diameter are widely used in palaeomagnetism. Occasionally smaller diameters have been used as well which represents distinct advantages in terms of throughput, weight of equipment and core collections. How their orientation precision compares to 25 mm cores, however, has not been evaluated in detail before. Here we compare the site mean directions and their statistical parameters for 12 lava flows sampled with 25 mm cores (standard samples, typically 8 cores per site) and with 12 mm drill cores (mini-samples, typically 14 cores per site). The site-mean directions for both sample sizes appear to be indistinguishable in most cases. For the mini-samples, site dispersion parameters k on average are slightly lower than for the standard samples reflecting their larger orienting and measurement errors. Applying the Wilcoxon signed-rank test the probability that k or α95 have the same distribution for both sizes is acceptable only at the 17.4 or 66.3 per cent level, respectively. The larger mini-core numbers per site appears to outweigh the lower k values yielding also slightly smaller confidence limits α95. Further, both k and α95 are less variable for mini-samples than for standard size samples. This is interpreted also to result from the larger number of mini-samples per site, which better averages out the detrimental effect of undetected abnormal remanence directions. Sampling of volcanic rocks with mini-samples therefore does not present a disadvantage in terms of the overall obtainable uncertainty of site mean directions. Apart from this, mini-samples do present clear advantages during the field work, as about twice the number of drill cores can be recovered compared to 25 mm cores, and the sampled rock unit is then more widely covered, which reduces the contribution of natural random errors produced, for example, by fractures, cooling joints, and palaeofield inhomogeneities. Mini-samples may be processed faster in the laboratory, which is of particular advantage when carrying out palaeointensity experiments.

Invited Review Small is beautiful: The analysis of nanogram-sized astromaterials

NASA Astrophysics Data System (ADS)

Zolensky, M. E.; Pieters, C.; Clark, B.; Papike, J. J.

2000-01-01

The capability of modern methods to characterize ultra-small samples is well established from analysis of interplanetary dust particles (IDPs), interstellar grains recovered from meteorites, and other materials requiring ultra-sensitive analytical capabilities. Powerful analytical techniques are available that require, under favorable circumstances, single particles of only a few nanograms for entire suites of fairly comprehensive characterizations. A returned sample of >1,000 particles with total mass of just one microgram permits comprehensive quantitative geochemical measurements that are impractical to carry out in situ by flight instruments. The main goal of this paper is to describe the state-of-the-art in microanalysis of astromaterials. Given that we can analyze fantastically small quantities of asteroids and comets, etc., we have to ask ourselves how representative are microscopic samples of bodies that measure a few to many km across? With the Galileo flybys of Gaspra and Ida, it is now recognized that even very small airless bodies have indeed developed a particulate regolith. Acquiring a sample of the bulk regolith, a simple sampling strategy, provides two critical pieces of information about the body. Regolith samples are excellent bulk samples since they normally contain all the key components of the local environment, albeit in particulate form. Furthermore, since this fine fraction dominates remote measurements, regolith samples also provide information about surface alteration processes and are a key link to remote sensing of other bodies. Studies indicate that a statistically significant number of nanogram-sized particles should be able to characterize the regolith of a primitive asteroid, although the presence of larger components within even primitive meteorites (e.g.. Murchison), e.g. chondrules, CAI, large crystal fragments, etc., points out the limitations of using data obtained from nanogram-sized samples to characterize entire primitive asteroids. However, most important asteroidal geological processes have left their mark on the matrix, since this is the finest-grained portion and therefore most sensitive to chemical and physical changes. Thus, the following information can be learned from this fine grain size fraction alone: (1) mineral paragenesis; (2) regolith processes, (3) bulk composition; (4) conditions of thermal and aqueous alteration (if any); (5) relationships to planets, comets, meteorites (via isotopic analyses, including oxygen; (6) abundance of water and hydrated material; (7) abundance of organics; (8) history of volatile mobility, (9) presence and origin of presolar and/or interstellar material. Most of this information can even be obtained from dust samples from bodies for which nanogram-sized samples are not truly representative. Future advances in sensitivity and accuracy of laboratory analytical techniques can be expected to enhance the science value of nano- to microgram sized samples even further. This highlights a key advantage of sample returns - that the most advanced analysis techniques can always be applied in the laboratory, and that well-preserved samples are available for future investigations.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

PubMed

Kunz, Cornelia U; Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2017-03-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re-assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one-sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. © 2016 The Authors. Biometrical Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations

PubMed Central

Stallard, Nigel; Parsons, Nicholas; Todd, Susan; Friede, Tim

2016-01-01

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under‐ or overestimation of the sample size. Both situations are unfavourable as the first one decreases the power and the latter one leads to a waste of resources. Hence, designs have been suggested that allow a re‐assessment of the sample size in an ongoing trial. These methods usually focus on estimating the variance. However, for some methods the performance depends not only on the variance but also on the correlation between measurements. We develop and compare different methods for blinded estimation of the correlation coefficient that are less likely to introduce operational bias when the blinding is maintained. Their performance with respect to bias and standard error is compared to the unblinded estimator. We simulated two different settings: one assuming that all group means are the same and one assuming that different groups have different means. Simulation results show that the naïve (one‐sample) estimator is only slightly biased and has a standard error comparable to that of the unblinded estimator. However, if the group means differ, other estimators have better performance depending on the sample size per group and the number of groups. PMID:27886393

Sample size and power considerations in network meta-analysis

PubMed Central

2012-01-01

Background Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. Findings In this article, we develop easy-to-use flexible methods for estimating the ‘effective sample size’ in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. Conclusion The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates. PMID:22992327

On the role of dimensionality and sample size for unstructured and structured covariance matrix estimation

NASA Technical Reports Server (NTRS)

Morgera, S. D.; Cooper, D. B.

1976-01-01

The experimental observation that a surprisingly small sample size vis-a-vis dimension is needed to achieve good signal-to-interference ratio (SIR) performance with an adaptive predetection filter is explained. The adaptive filter requires estimates as obtained by a recursive stochastic algorithm of the inverse of the filter input data covariance matrix. The SIR performance with sample size is compared for the situations where the covariance matrix estimates are of unstructured (generalized) form and of structured (finite Toeplitz) form; the latter case is consistent with weak stationarity of the input data stochastic process.

Reporting and methodological quality of sample size calculations in cluster randomized trials could be improved: a review.

PubMed

Rutterford, Clare; Taljaard, Monica; Dixon, Stephanie; Copas, Andrew; Eldridge, Sandra

2015-06-01

To assess the quality of reporting and accuracy of a priori estimates used in sample size calculations for cluster randomized trials (CRTs). We reviewed 300 CRTs published between 2000 and 2008. The prevalence of reporting sample size elements from the 2004 CONSORT recommendations was evaluated and a priori estimates compared with those observed in the trial. Of the 300 trials, 166 (55%) reported a sample size calculation. Only 36 of 166 (22%) reported all recommended descriptive elements. Elements specific to CRTs were the worst reported: a measure of within-cluster correlation was specified in only 58 of 166 (35%). Only 18 of 166 articles (11%) reported both a priori and observed within-cluster correlation values. Except in two cases, observed within-cluster correlation values were either close to or less than a priori values. Even with the CONSORT extension for cluster randomization, the reporting of sample size elements specific to these trials remains below that necessary for transparent reporting. Journal editors and peer reviewers should implement stricter requirements for authors to follow CONSORT recommendations. Authors should report observed and a priori within-cluster correlation values to enable comparisons between these over a wider range of trials. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

[Experimental study on particle size distributions of an engine fueled with blends of biodiesel].

PubMed

Lu, Xiao-Ming; Ge, Yun-Shan; Han, Xiu-Kun; Wu, Si-Jin; Zhu, Rong-Fu; He, Chao

2007-04-01

The purpose of this study is to obtain the particle size distributions of an engine fueled biodiesel and its blends. A turbocharged DI diesel engine was tested on a dynamometer. A pump of 80 L/min and fiber glass filters with diameter of 90 mm were used to sample engine particles in exhaust pipe. Sampling duration was 10 minutes. Particle size distributions were measured by a laser diffraction particle size analyzer. Results indicated that higher engine speed resulted in smaller particle sizes and narrower distributions. The modes on distribution curves and mode variation were larger with dry samples than with wet samples (dry: around 10 - 12 microm vs. wet: around 4 - 10 microm). At low speed, Sauter mean diameter d32 of dry samples was the biggest with B100, the smallest with diesel fuel, and among them with B20, while at high speed, d32 the biggest with B20, the smallest with B100, and in middle with diesel. Median diameter d(0.5) also reflected the results. Except for 2 000 r/min, d32 of wet with B20 is the biggest, the smallest with diesel, and in middle with B100. The large mode variation resulted in increase of d32.

Design of Phase II Non-inferiority Trials.

PubMed

Jung, Sin-Ho

2017-09-01

With the development of inexpensive treatment regimens and less invasive surgical procedures, we are confronted with non-inferiority study objectives. A non-inferiority phase III trial requires a roughly four times larger sample size than that of a similar standard superiority trial. Because of the large required sample size, we often face feasibility issues to open a non-inferiority trial. Furthermore, due to lack of phase II non-inferiority trial design methods, we do not have an opportunity to investigate the efficacy of the experimental therapy through a phase II trial. As a result, we often fail to open a non-inferiority phase III trial and a large number of non-inferiority clinical questions still remain unanswered. In this paper, we want to develop some designs for non-inferiority randomized phase II trials with feasible sample sizes. At first, we review a design method for non-inferiority phase III trials. Subsequently, we propose three different designs for non-inferiority phase II trials that can be used under different settings. Each method is demonstrated with examples. Each of the proposed design methods is shown to require a reasonable sample size for non-inferiority phase II trials. The three different non-inferiority phase II trial designs are used under different settings, but require similar sample sizes that are typical for phase II trials.

A Bayesian sequential design using alpha spending function to control type I error.

PubMed

Zhu, Han; Yu, Qingzhao

2017-10-01

We propose in this article a Bayesian sequential design using alpha spending functions to control the overall type I error in phase III clinical trials. We provide algorithms to calculate critical values, power, and sample sizes for the proposed design. Sensitivity analysis is implemented to check the effects from different prior distributions, and conservative priors are recommended. We compare the power and actual sample sizes of the proposed Bayesian sequential design with different alpha spending functions through simulations. We also compare the power of the proposed method with frequentist sequential design using the same alpha spending function. Simulations show that, at the same sample size, the proposed method provides larger power than the corresponding frequentist sequential design. It also has larger power than traditional Bayesian sequential design which sets equal critical values for all interim analyses. When compared with other alpha spending functions, O'Brien-Fleming alpha spending function has the largest power and is the most conservative in terms that at the same sample size, the null hypothesis is the least likely to be rejected at early stage of clinical trials. And finally, we show that adding a step of stop for futility in the Bayesian sequential design can reduce the overall type I error and reduce the actual sample sizes.

Sample size determination for disease prevalence studies with partially validated data.

PubMed

Qiu, Shi-Fang; Poon, Wai-Yin; Tang, Man-Lai

2016-02-01

Disease prevalence is an important topic in medical research, and its study is based on data that are obtained by classifying subjects according to whether a disease has been contracted. Classification can be conducted with high-cost gold standard tests or low-cost screening tests, but the latter are subject to the misclassification of subjects. As a compromise between the two, many research studies use partially validated datasets in which all data points are classified by fallible tests, and some of the data points are validated in the sense that they are also classified by the completely accurate gold-standard test. In this article, we investigate the determination of sample sizes for disease prevalence studies with partially validated data. We use two approaches. The first is to find sample sizes that can achieve a pre-specified power of a statistical test at a chosen significance level, and the second is to find sample sizes that can control the width of a confidence interval with a pre-specified confidence level. Empirical studies have been conducted to demonstrate the performance of various testing procedures with the proposed sample sizes. The applicability of the proposed methods are illustrated by a real-data example. © The Author(s) 2012.

Sample size determination for a three-arm equivalence trial of Poisson and negative binomial responses.

PubMed

Chang, Yu-Wei; Tsong, Yi; Zhao, Zhigen

2017-01-01

Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.

Impact of Different Visual Field Testing Paradigms on Sample Size Requirements for Glaucoma Clinical Trials.

PubMed

Wu, Zhichao; Medeiros, Felipe A

2018-03-20

Visual field testing is an important endpoint in glaucoma clinical trials, and the testing paradigm used can have a significant impact on the sample size requirements. To investigate this, this study included 353 eyes of 247 glaucoma patients seen over a 3-year period to extract real-world visual field rates of change and variability estimates to provide sample size estimates from computer simulations. The clinical trial scenario assumed that a new treatment was added to one of two groups that were both under routine clinical care, with various treatment effects examined. Three different visual field testing paradigms were evaluated: a) evenly spaced testing, b) United Kingdom Glaucoma Treatment Study (UKGTS) follow-up scheme, which adds clustered tests at the beginning and end of follow-up in addition to evenly spaced testing, and c) clustered testing paradigm, with clusters of tests at the beginning and end of the trial period and two intermediary visits. The sample size requirements were reduced by 17-19% and 39-40% using the UKGTS and clustered testing paradigms, respectively, when compared to the evenly spaced approach. These findings highlight how the clustered testing paradigm can substantially reduce sample size requirements and improve the feasibility of future glaucoma clinical trials.

Intrafamilial clustering of anti-ATLA-positive persons.

PubMed

Kajiyama, W; Kashiwagi, S; Hayashi, J; Nomura, H; Ikematsu, H; Okochi, K

1986-11-01

A total of 1,333 persons in 627 families were surveyed for presence of antibody to adult T-cell leukemia-associated antigen (anti-ATLA). Each person was classified according to the anti-ATLA status (positive for sample 1, negative for sample 2) of the head of household of his or her family. In sample 1, the sex- and age-standardized prevalence of anti-ATLA was 38.5%. This was five times as high as the standardized prevalence in sample 2 (7.8%). There were significant differences in prevalence of anti-ATLA between males in samples 1 and 2 and between females in samples 1 and 2. In every age group, prevalence in sample 1 was greater than that in sample 2 except for males aged 60-69 years. In each of four subareas, families in sample 1 had higher standardized prevalence (29.6-42.5%) than families in sample 2 (6.0-9.7%). Although crude prevalence decreased with family size in sample 1 (62.1-25.4%) as well as in sample 2, indirectly standardized prevalence was almost equal within each sample, regardless of number of family members. The degree of aggregation was independent of locality and family size. These data suggest that anti-ATLA-positive persons aggregate in family units.

Multi-species attributes as the condition for adaptive sampling of rare species using two-stage sequential sampling with an auxiliary variable

USGS Publications Warehouse

Panahbehagh, B.; Smith, D.R.; Salehi, M.M.; Hornbach, D.J.; Brown, D.J.; Chan, F.; Marinova, D.; Anderssen, R.S.

2011-01-01

Assessing populations of rare species is challenging because of the large effort required to locate patches of occupied habitat and achieve precise estimates of density and abundance. The presence of a rare species has been shown to be correlated with presence or abundance of more common species. Thus, ecological community richness or abundance can be used to inform sampling of rare species. Adaptive sampling designs have been developed specifically for rare and clustered populations and have been applied to a wide range of rare species. However, adaptive sampling can be logistically challenging, in part, because variation in final sample size introduces uncertainty in survey planning. Two-stage sequential sampling (TSS), a recently developed design, allows for adaptive sampling, but avoids edge units and has an upper bound on final sample size. In this paper we present an extension of two-stage sequential sampling that incorporates an auxiliary variable (TSSAV), such as community attributes, as the condition for adaptive sampling. We develop a set of simulations to approximate sampling of endangered freshwater mussels to evaluate the performance of the TSSAV design. The performance measures that we are interested in are efficiency and probability of sampling a unit occupied by the rare species. Efficiency measures the precision of population estimate from the TSSAV design relative to a standard design, such as simple random sampling (SRS). The simulations indicate that the density and distribution of the auxiliary population is the most important determinant of the performance of the TSSAV design. Of the design factors, such as sample size, the fraction of the primary units sampled was most important. For the best scenarios, the odds of sampling the rare species was approximately 1.5 times higher for TSSAV compared to SRS and efficiency was as high as 2 (i.e., variance from TSSAV was half that of SRS). We have found that design performance, especially for adaptive designs, is often case-specific. Efficiency of adaptive designs is especially sensitive to spatial distribution. We recommend that simulations tailored to the application of interest are highly useful for evaluating designs in preparation for sampling rare and clustered populations.

The fundamentals of average local variance--Part II: Sampling simple regular patterns with optical imagery.

PubMed

Bøcher, Peder Klith; McCloy, Keith R

2006-02-01

In this investigation, the characteristics of the average local variance (ALV) function is investigated through the acquisition of images at different spatial resolutions of constructed scenes of regular patterns of black and white squares. It is shown that the ALV plot consistently peaks at a spatial resolution in which the pixels has a size corresponding to half the distance between scene objects, and that, under very specific conditions, it also peaks at a spatial resolution in which the pixel size corresponds to the whole distance between scene objects. It is argued that the peak at object distance when present is an expression of the Nyquist sample rate. The presence of this peak is, hence, shown to be a function of the matching between the phase of the scene pattern and the phase of the sample grid, i.e., the image. When these phases match, a clear and distinct peak is produced on the ALV plot. The fact that the peak at half the distance consistently occurs in the ALV plot is linked to the circumstance that the sampling interval (distance between pixels) and the extent of the sampling unit (size of pixels) are equal. Hence, at twice the Nyquist sampling rate, each fundamental period of the pattern is covered by four pixels; therefore, at least one pixel is always completely embedded within one pattern element, regardless of sample scene phase. If the objects in the scene are scattered with a distance larger than their extent, the peak will be related to the size by a factor larger than 1/2. This is suggested to be the explanation to the results presented by others that the ALV plot is related to scene-object size by a factor of 1/2-3/4.

Factors Affecting Pathogen Survival in Finished Dairy Compost with Different Particle Sizes Under Greenhouse Conditions.

PubMed

Diao, Junshu; Chen, Zhao; Gong, Chao; Jiang, Xiuping

2015-09-01

This study investigated the survival of Escherichia coli O157:H7 and Salmonella Typhimurium in finished dairy compost with different particle sizes during storage as affected by moisture content and temperature under greenhouse conditions. The mixture of E. coli O157:H7 and S. Typhimurium strains was inoculated into the finished composts with moisture contents of 20, 30, and 40%, separately. The finished compost samples were then sieved into 3 different particle sizes (>1000, 500-1000, and <500 μm) and stored under greenhouse conditions. For compost samples with moisture contents of 20 and 30%, the average Salmonella reductions in compost samples with particle sizes of >1000, 500-1000, and <500 μm were 2.15, 2.27, and 2.47 log colony-forming units (CFU) g(-1) within 5 days of storage in summer, respectively, as compared with 1.60, 2.03, and 2.26 log CFU g(-1) in late fall, respectively, and 2.61, 3.33, and 3.67 log CFU g(-1) in winter, respectively. The average E. coli O157:H7 reductions in compost samples with particle sizes of >1000, 500-1000, and <500 μm were 1.98, 2.30, and 2.54 log CFU g(-1) within 5 days of storage in summer, respectively, as compared with 1.70, 2.56, and 2.90 log CFU g(-1) in winter, respectively. Our results revealed that both Salmonella and E. coli O157:H7 in compost samples with larger particle size survived better than those with smaller particle sizes, and the initial rapid moisture loss in compost may contribute to the fast inactivation of pathogens in the finished compost. For the same season, the pathogens in the compost samples with the same particle size survived much better at the initial moisture content of 20% compared to 40%.

Evaluation of a new tear osmometer for repeatability and accuracy, using 0.5-microL (500-Nanoliter) samples.

PubMed

Yildiz, Elvin H; Fan, Vincent C; Banday, Hina; Ramanathan, Lakshmi V; Bitra, Ratna K; Garry, Eileen; Asbell, Penny A

2009-07-01

To evaluate the repeatability and accuracy of a new tear osmometer that measures the osmolality of 0.5-microL (500-nanoliter) samples. Four standardized solutions were tested with 0.5-microL (500-nanoliter) samples for repeatability of measurements and comparability to standardized technique. Two known standard salt solutions (290 mOsm/kg H2O, 304 mOsm/kg H2O), a normal artificial tear matrix sample (306 mOsm/kg H2O), and an abnormal artificial tear matrix sample (336 mOsm/kg H2O) were repeatedly tested (n = 20 each) for osmolality with use of the Advanced Instruments Model 3100 Tear Osmometer (0.5-microL [500-nanoliter] sample size) and the FDA-approved Advanced Instruments Model 3D2 Clinical Osmometer (250-microL sample size). Four standard solutions were used, with osmolality values of 290, 304, 306, and 336 mOsm/kg H2O. The respective precision data, including the mean and standard deviation, were: 291.8 +/- 4.4, 305.6 +/- 2.4, 305.1 +/- 2.3, and 336.4 +/- 2.2 mOsm/kg H2O. The percent recoveries for the 290 mOsm/kg H2O standard solution, the 304 mOsm/kg H2O reference solution, the normal value-assigned 306 mOsm/kg H2O sample, and the abnormal value-assigned 336 mOsm/kg H2O sample were 100.3, 100.2, 99.8, and 100.3 mOsm/kg H2O, respectively. The repeatability data are in accordance with data obtained on clinical osmometers with use of larger sample sizes. All 4 samples tested on the tear osmometer have osmolality values that correlate well to the clinical instrument method. The tear osmometer is a suitable instrument for testing the osmolality of microliter-sized samples, such as tears, and therefore may be useful in diagnosing, monitoring, and classifying tear abnormalities such as the severity of dry eye disease.

Porosity characterization for heterogeneous shales using integrated multiscale microscopy

NASA Astrophysics Data System (ADS)

Rassouli, F.; Andrew, M.; Zoback, M. D.

2016-12-01

Pore size distribution analysis plays a critical role in gas storage capacity and fluid transport characterization of shales. Study of the diverse distribution of pore size and structure in such low permeably rocks is withheld by the lack of tools to visualize the microstructural properties of shale rocks. In this paper we try to use multiple techniques to investigate the full pore size range in different sample scales. Modern imaging techniques are combined with routine analytical investigations (x-ray diffraction, thin section analysis and mercury porosimetry) to describe pore size distribution of shale samples from Haynesville formation in East Texas to generate a more holistic understanding of the porosity structure in shales, ranging from standard core plug down to nm scales. Standard 1" diameter core plug samples were first imaged using a Versa 3D x-ray microscope at lower resolutions. Then we pick several regions of interest (ROIs) with various micro-features (such as micro-cracks and high organic matters) in the rock samples to run higher resolution CT scans using a non-destructive interior tomography scans. After this step, we cut the samples and drill 5 mm diameter cores out of the selected ROIs. Then we rescan the samples to measure porosity distribution of the 5 mm cores. We repeat this step for samples with diameter of 1 mm being cut out of the 5 mm cores using a laser cutting machine. After comparing the pore structure and distribution of the samples measured form micro-CT analysis, we move to nano-scale imaging to capture the ultra-fine pores within the shale samples. At this stage, the diameter of the 1 mm samples will be milled down to 70 microns using the laser beam. We scan these samples in a nano-CT Ultra x-ray microscope and calculate the porosity of the samples by image segmentation methods. Finally, we use images collected from focused ion beam scanning electron microscopy (FIB-SEM) to be able to compare the results of porosity measurements from all different imaging techniques. These multi-scale characterization techniques are then compared with traditional analytical techniques such as Mercury Porosimetry.

What is the extent of prokaryotic diversity?

PubMed Central

Curtis, Thomas P; Head, Ian M; Lunn, Mary; Woodcock, Stephen; Schloss, Patrick D; Sloan, William T

2006-01-01

The extent of microbial diversity is an intrinsically fascinating subject of profound practical importance. The term ‘diversity’ may allude to the number of taxa or species richness as well as their relative abundance. There is uncertainty about both, primarily because sample sizes are too small. Non-parametric diversity estimators make gross underestimates if used with small sample sizes on unevenly distributed communities. One can make richness estimates over many scales using small samples by assuming a species/taxa-abundance distribution. However, no one knows what the underlying taxa-abundance distributions are for bacterial communities. Latterly, diversity has been estimated by fitting data from gene clone libraries and extrapolating from this to taxa-abundance curves to estimate richness. However, since sample sizes are small, we cannot be sure that such samples are representative of the community from which they were drawn. It is however possible to formulate, and calibrate, models that predict the diversity of local communities and of samples drawn from that local community. The calibration of such models suggests that migration rates are small and decrease as the community gets larger. The preliminary predictions of the model are qualitatively consistent with the patterns seen in clone libraries in ‘real life’. The validation of this model is also confounded by small sample sizes. However, if such models were properly validated, they could form invaluable tools for the prediction of microbial diversity and a basis for the systematic exploration of microbial diversity on the planet. PMID:17028084

[Sequential sampling plans to Orthezia praelonga Douglas (Hemiptera: Sternorrhyncha, Ortheziidae) in citrus].

PubMed

Costa, Marilia G; Barbosa, José C; Yamamoto, Pedro T

2007-01-01

The sequential sampling is characterized by using samples of variable sizes, and has the advantage of reducing sampling time and costs if compared to fixed-size sampling. To introduce an adequate management for orthezia, sequential sampling plans were developed for orchards under low and high infestation. Data were collected in Matão, SP, in commercial stands of the orange variety 'Pêra Rio', at five, nine and 15 years of age. Twenty samplings were performed in the whole area of each stand by observing the presence or absence of scales on plants, being plots comprised of ten plants. After observing that in all of the three stands the scale population was distributed according to the contagious model, fitting the Negative Binomial Distribution in most samplings, two sequential sampling plans were constructed according to the Sequential Likelihood Ratio Test (SLRT). To construct these plans an economic threshold of 2% was adopted and the type I and II error probabilities were fixed in alpha = beta = 0.10. Results showed that the maximum numbers of samples expected to determine control need were 172 and 76 samples for stands with low and high infestation, respectively.

Comparison of particle sizes between 238PuO 2 before aqueous processing, after aqueous processing, and after ball milling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mulford, Roberta Nancy

Particle sizes determined for a single lot of incoming Russian fuel and for a lot of fuel after aqueous processing are compared with particle sizes measured on fuel after ball-milling. The single samples of each type are believed to have particle size distributions typical of oxide from similar lots, as the processing of fuel lots is fairly uniform. Variation between lots is, as yet, uncharacterized. Sampling and particle size measurement methods are discussed elsewhere.

Power of tests of normality for detecting contaminated normal samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thode, H.C. Jr.; Smith, L.A.; Finch, S.J.

1981-01-01

Seventeen tests of normality or goodness of fit were evaluated for power at detecting a contaminated normal sample. This study used 1000 replications each of samples of size 12, 17, 25, 33, 50, and 100 from six different contaminated normal distributions. The kurtosis test was the most powerful over all sample sizes and contaminations. The Hogg and weighted Kolmogorov-Smirnov tests were second. The Kolmogorov-Smirnov, chi-squared, Anderson-Darling, and Cramer-von-Mises tests had very low power at detecting contaminated normal random variables. Tables of the power of the tests and the power curves of certain tests are given.

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hero, Alfred O.; Rajaratnam, Bala

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

PubMed Central

Hero, Alfred O.; Rajaratnam, Bala

2015-01-01

When can reliable inference be drawn in fue “Big Data” context? This paper presents a framework for answering this fundamental question in the context of correlation mining, wifu implications for general large scale inference. In large scale data applications like genomics, connectomics, and eco-informatics fue dataset is often variable-rich but sample-starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than fue number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for “Big Data”. Sample complexity however has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address fuis gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where fue variable dimension is fixed and fue sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; 3) the purely high dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa cale data dimension. We illustrate this high dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables fua t are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. we demonstrate various regimes of correlation mining based on the unifying perspective of high dimensional learning rates and sample complexity for different structured covariance models and different inference tasks. PMID:27087700

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

DOE PAGES

Hero, Alfred O.; Rajaratnam, Bala

2015-12-09

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, hasmore » received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.« less

Field size, length, and width distributions based on LACIE ground truth data. [large area crop inventory experiment

NASA Technical Reports Server (NTRS)

Pitts, D. E.; Badhwar, G.

1980-01-01

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

A Note on Maximized Posttest Contrasts.

ERIC Educational Resources Information Center

Williams, John D.

1979-01-01

Hollingsworth recently showed a posttest contrast for analysis of variance situations that, for equal sample sizes, had several favorable qualities. However, for unequal sample sizes, the contrast fails to achieve status as a maximized contrast; thus, separate testing of the contrast is required. (Author/GSK)

Grain Size and Parameter Recovery with TIMSS and the General Diagnostic Model

ERIC Educational Resources Information Center

Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F.

2016-01-01

The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…

Investigation of the Specht density estimator

NASA Technical Reports Server (NTRS)

Speed, F. M.; Rydl, L. M.

1971-01-01

The feasibility of using the Specht density estimator function on the IBM 360/44 computer is investigated. Factors such as storage, speed, amount of calculations, size of the smoothing parameter and sample size have an effect on the results. The reliability of the Specht estimator for normal and uniform distributions and the effects of the smoothing parameter and sample size are investigated.

Meta-analysis of multiple outcomes: a multilevel approach.

PubMed

Van den Noortgate, Wim; López-López, José Antonio; Marín-Martínez, Fulgencio; Sánchez-Meca, Julio

2015-12-01

In meta-analysis, dependent effect sizes are very common. An example is where in one or more studies the effect of an intervention is evaluated on multiple outcome variables for the same sample of participants. In this paper, we evaluate a three-level meta-analytic model to account for this kind of dependence, extending the simulation results of Van den Noortgate, López-López, Marín-Martínez, and Sánchez-Meca Behavior Research Methods, 45, 576-594 (2013) by allowing for a variation in the number of effect sizes per study, in the between-study variance, in the correlations between pairs of outcomes, and in the sample size of the studies. At the same time, we explore the performance of the approach if the outcomes used in a study can be regarded as a random sample from a population of outcomes. We conclude that although this approach is relatively simple and does not require prior estimates of the sampling covariances between effect sizes, it gives appropriate mean effect size estimates, standard error estimates, and confidence interval coverage proportions in a variety of realistic situations.

Long-term effective population size dynamics of an intensively monitored vertebrate population

PubMed Central

Mueller, A-K; Chakarov, N; Krüger, O; Hoffman, J I

2016-01-01

Long-term genetic data from intensively monitored natural populations are important for understanding how effective population sizes (Ne) can vary over time. We therefore genotyped 1622 common buzzard (Buteo buteo) chicks sampled over 12 consecutive years (2002–2013 inclusive) at 15 microsatellite loci. This data set allowed us to both compare single-sample with temporal approaches and explore temporal patterns in the effective number of parents that produced each cohort in relation to the observed population dynamics. We found reasonable consistency between linkage disequilibrium-based single-sample and temporal estimators, particularly during the latter half of the study, but no clear relationship between annual Ne estimates () and census sizes. We also documented a 14-fold increase in between 2008 and 2011, a period during which the census size doubled, probably reflecting a combination of higher adult survival and immigration from further afield. Our study thus reveals appreciable temporal heterogeneity in the effective population size of a natural vertebrate population, confirms the need for long-term studies and cautions against drawing conclusions from a single sample. PMID:27553455

Dependence of flux-flow critical frequencies and generalized bundle sizes on distance of fluxoid traversal and fluxoid length in foil samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, J.D.; Joiner, W.C.H.

1979-10-01

Flux-flow noise power spectra taken on Pb/sub 80/In/sub 20/ foils as a function of the orientation of the magnetic field with respect to the sample surfaces are used to study changes in frequencies and bundle sizes as distances of fluxoid traversal and fluxoid lengths change. The results obtained for the frequency dependence of the noise spectra are entirely consistent with our model for flux motion interrupted by pinning centers, provided one makes the reasonable assumption that the distance between pinning centers which a fluxoid may encounter scales inversely with the fluxoid length. The importance of pinning centers in determining themore » noise characteristics is also demonstrated by the way in which subpulse distributions and generalized bundle sizes are altered by changes in the metallurgical structure of the sample. In unannealed samples the dependence of bundle size on magnetic field orientation is controlled by a structural anisotropy, and we find a correlation between large bundle size and the absence of short subpulse times. Annealing removes this anisotropy, and we find a stronger angular variation of bundle size than would be expected using present simplified models.« less

Epistemological Issues in Astronomy Education Research: How Big of a Sample is "Big Enough"?

NASA Astrophysics Data System (ADS)

Slater, Stephanie; Slater, T. F.; Souri, Z.

2012-01-01

As astronomy education research (AER) continues to evolve into a sophisticated enterprise, we must begin to grapple with defining our epistemological parameters. Moreover, as we attempt to make pragmatic use of our findings, we must make a concerted effort to communicate those parameters in a sensible way to the larger astronomical community. One area of much current discussion involves a basic discussion of methodologies, and subsequent sample sizes, that should be considered appropriate for generating knowledge in the field. To address this question, we completed a meta-analysis of nearly 1,000 peer-reviewed studies published in top tier professional journals. Data related to methodologies and sample sizes were collected from "hard science” and "human science” journals to compare the epistemological systems of these two bodies of knowledge. Working back in time from August 2011, the 100 most recent studies reported in each journal were used as a data source: Icarus, ApJ and AJ, NARST, IJSE and SciEd. In addition, data was collected from the 10 most recent AER dissertations, a set of articles determined by the science education community to be the most influential in the field, and the nearly 400 articles used as reference materials for the NRC's Taking Science to School. Analysis indicates these bodies of knowledge have a great deal in common; each relying on a large variety of methodologies, and each building its knowledge through studies that proceed from surprisingly low sample sizes. While both fields publish a small percentage of studies with large sample sizes, the vast majority of top tier publications consist of rich studies of a small number of objects. We conclude that rigor in each field is determined not by a circumscription of methodologies and sample sizes, but by peer judgments that the methods and sample sizes are appropriate to the research question.

Grain-size-induced weakening of H2O ices I and II and associated anisotropic recrystallization

USGS Publications Warehouse

Stern, L.A.; Durham, W.B.; Kirby, S.H.

1997-01-01

Grain-size-dependent flow mechanisms tend to be favored over dislocation creep at low differential stresses and can potentially influence the rheology of low-stress, low-strain rate environments such as those of planetary interiors. We experimentally investigated the effect of reduced grain size on the solid-state flow of water ice I, a principal component of the asthenospheres of many icy moons of the outer solar system, using techniques new to studies of this deformation regime. We fabricated fully dense ice samples of approximate grain size 2 ?? 1 ??m by transforming "standard" ice I samples of 250 ?? 50 ??m grain size to the higher-pressure phase ice II, deforming them in the ice II field, and then rapidly releasing the pressure deep into the ice I stability field. At T ??? 200 K, slow growth and rapid nucleation of ice I combine to produce a fine grain size. Constant-strain rate deformation tests conducted on these samples show that deformation rates are less stress sensitive than for standard ice and that the fine-grained material is markedly weaker than standard ice, particularly during the transient approach to steady state deformation. Scanning electron microscope examination of the deformed fine-grained ice samples revealed an unusual microstructure dominated by platelike grains that grew normal to the compression direction, with c axes preferentially oriented parallel to compression. In samples tested at T ??? 220 K the elongation of the grains is so pronounced that the samples appear finely banded, with aspect ratios of grains approaching 50:1. The anisotropic growth of these crystallographically oriented neoblasts likely contributes to progressive work hardening observed during the transient stage of deformation. We have also documented remarkably similar microstructural development and weak mechanical behavior in fine-grained ice samples partially transformed and deformed in the ice II field.

The sample handling system for the Mars Icebreaker Life mission: from dirt to data.

PubMed

Davé, Arwen; Thompson, Sarah J; McKay, Christopher P; Stoker, Carol R; Zacny, Kris; Paulsen, Gale; Mellerowicz, Bolek; Glass, Brian J; Willson, David; Bonaccorsi, Rosalba; Rask, Jon

2013-04-01

The Mars Icebreaker Life mission will search for subsurface life on Mars. It consists of three payload elements: a drill to retrieve soil samples from approximately 1 m below the surface, a robotic sample handling system to deliver the sample from the drill to the instruments, and the instruments themselves. This paper will discuss the robotic sample handling system. Collecting samples from ice-rich soils on Mars in search of life presents two challenges: protection of that icy soil--considered a "special region" with respect to planetary protection--from contamination from Earth, and delivery of the icy, sticky soil to spacecraft instruments. We present a sampling device that meets these challenges. We built a prototype system and tested it at martian pressure, drilling into ice-cemented soil, collecting cuttings, and transferring them to the inlet port of the SOLID2 life-detection instrument. The tests successfully demonstrated that the Icebreaker drill, sample handling system, and life-detection instrument can collectively operate in these conditions and produce science data that can be delivered via telemetry--from dirt to data. Our results also demonstrate the feasibility of using an air gap to prevent forward contamination. We define a set of six analog soils for testing over a range of soil cohesion, from loose sand to basalt soil, with angles of repose of 27° and 39°, respectively. Particle size is a key determinant of jamming of mechanical parts by soil particles. Jamming occurs when the clearance between moving parts is equal in size to the most common particle size or equal to three of these particles together. Three particles acting together tend to form bridges and lead to clogging. Our experiments show that rotary-hammer action of the Icebreaker drill influences the particle size, typically reducing particle size by ≈ 100 μm.

The effects of neutralized particles on the sampling efficiency of polyurethane foam used to estimate the extrathoracic deposition fraction.

PubMed

Tomyn, Ronald L; Sleeth, Darrah K; Thiese, Matthew S; Larson, Rodney R

2016-01-01

In addition to chemical composition, the site of deposition of inhaled particles is important for determining the potential health effects from an exposure. As a result, the International Organization for Standardization adopted a particle deposition sampling convention. This includes extrathoracic particle deposition sampling conventions for the anterior nasal passages (ET1) and the posterior nasal and oral passages (ET2). This study assessed how well a polyurethane foam insert placed in an Institute of Occupational Medicine (IOM) sampler can match an extrathoracic deposition sampling convention, while accounting for possible static buildup in the test particles. In this way, the study aimed to assess whether neutralized particles affected the performance of this sampler for estimating extrathoracic particle deposition. A total of three different particle sizes (4.9, 9.5, and 12.8 µm) were used. For each trial, one particle size was introduced into a low-speed wind tunnel with a wind speed set a 0.2 m/s (∼40 ft/min). This wind speed was chosen to closely match the conditions of most indoor working environments. Each particle size was tested twice either neutralized, using a high voltage neutralizer, or left in its normal (non neutralized) state as standard particles. IOM samplers were fitted with a polyurethane foam insert and placed on a rotating mannequin inside the wind tunnel. Foam sampling efficiencies were calculated for all trials to compare against the normalized ET1 sampling deposition convention. The foam sampling efficiencies matched well to the ET1 deposition convention for the larger particle sizes, but had a general trend of underestimating for all three particle sizes. The results of a Wilcoxon Rank Sum Test also showed that only at 4.9 µm was there a statistically significant difference (p-value = 0.03) between the foam sampling efficiency using the standard particles and the neutralized particles. This is interpreted to mean that static buildup may be occurring and neutralizing the particles that are 4.9 µm diameter in size did affect the performance of the foam sampler when estimating extrathoracic particle deposition.

A USANS/SANS study of the accessibility of pores in the Barnett Shale to methane and water

USGS Publications Warehouse

Ruppert, Leslie F.; Sakurovs, Richard; Blach, Tomasz P.; He, Lilin; Melnichenko, Yuri B.; Mildner, David F.; Alcantar-Lopez, Leo

2013-01-01

Shale is an increasingly important source of natural gas in the United States. The gas is held in fine pores that need to be accessed by horizontal drilling and hydrofracturing techniques. Understanding the nature of the pores may provide clues to making gas extraction more efficient. We have investigated two Mississippian Barnett Shale samples, combining small-angle neutron scattering (SANS) and ultrasmall-angle neutron scattering (USANS) to determine the pore size distribution of the shale over the size range 10 nm to 10 μm. By adding deuterated methane (CD4) and, separately, deuterated water (D2O) to the shale, we have identified the fraction of pores that are accessible to these compounds over this size range. The total pore size distribution is essentially identical for the two samples. At pore sizes >250 nm, >85% of the pores in both samples are accessible to both CD4 and D2O. However, differences in accessibility to CD4 are observed in the smaller pore sizes (~25 nm). In one sample, CD4 penetrated the smallest pores as effectively as it did the larger ones. In the other sample, less than 70% of the smallest pores (4, but they were still largely penetrable by water, suggesting that small-scale heterogeneities in methane accessibility occur in the shale samples even though the total porosity does not differ. An additional study investigating the dependence of scattered intensity with pressure of CD4 allows for an accurate estimation of the pressure at which the scattered intensity is at a minimum. This study provides information about the composition of the material immediately surrounding the pores. Most of the accessible (open) pores in the 25 nm size range can be associated with either mineral matter or high reflectance organic material. However, a complementary scanning electron microscopy investigation shows that most of the pores in these shale samples are contained in the organic components. The neutron scattering results indicate that the pores are not equally proportioned in the different constituents within the shale. There is some indication from the SANS results that the composition of the pore-containing material varies with pore size; the pore size distribution associated with mineral matter is different from that associated with organic phases.

The effect of grain size and cement content on index properties of weakly solidified artificial sandstones

NASA Astrophysics Data System (ADS)

Atapour, Hadi; Mortazavi, Ali

2018-04-01

The effects of textural characteristics, especially grain size, on index properties of weakly solidified artificial sandstones are studied. For this purpose, a relatively large number of laboratory tests were carried out on artificial sandstones that were produced in the laboratory. The prepared samples represent fifteen sandstone types consisting of five different median grain sizes and three different cement contents. Indices rock properties including effective porosity, bulk density, point load strength index, and Schmidt hammer values (SHVs) were determined. Experimental results showed that the grain size has significant effects on index properties of weakly solidified sandstones. The porosity of samples is inversely related to the grain size and decreases linearly as grain size increases. While a direct relationship was observed between grain size and dry bulk density, as bulk density increased with increasing median grain size. Furthermore, it was observed that the point load strength index and SHV of samples increased as a result of grain size increase. These observations are indirectly related to the porosity decrease as a function of median grain size.