Estimate Of Central Tendency Research Articles

CONTENT OF TRANS FATTY ACIDS IN FOOD PRODUCTS IN SPAIN

trans fatty acids are associated to several health disorders, as ischemic heart disease or diabetes mellitus. to assess the content of trans fatty acids in products in Spain, and the percentage of trans fatty acids respecting total fatty acids. 443 food products were acquired in Spain, and they were classified into groups. The content in fatty acids was analyzed using gas chromatography. Estimates of central tendency and variability of the content of trans fatty acids in each food group were computed (in g of trans fatty acids/100 g of product). The percentage of trans fatty acids respecting total fatty acids was calculated in each group. 443 products were grouped into 42 groups. Median of trans fatty acids was less than 0.55 g / 100 g of product in all groups except one. 83 % of groups had less than 2 % of trans fatty acids, and 71 % of groups had less than 1 %. the content of trans fatty acids in Spain is low, and it currently doesn't play a public health problem.

Evaluation of PCB sources and releases for identifying priorities to reduce PCBs in Washington State (USA).

Polychlorinated biphenyls (PCBs) are ubiquitously distributed in the environment and produce multiple adverse effects in humans and wildlife. As a result, the purpose of our study was to characterize PCB sources in anthropogenic materials and releases to the environment in Washington State (USA) in order to formulate recommendations to reduce PCB exposures. Methods included review of relevant publications (e.g., open literature, industry studies and reports, federal and state government databases), scaling of PCB sources from national or county estimates to state estimates, and communication with industry associations and private and public utilities. Recognizing high associated uncertainty due to incomplete data, we strived to provide central tendency estimates for PCB sources. In terms of mass (high to low), PCB sources include lamp ballasts, caulk, small capacitors, large capacitors, and transformers. For perspective, these sources (200,000-500,000 kg) overwhelm PCBs estimated to reside in the Puget Sound ecosystem (1500 kg). Annual releases of PCBs to the environment (high to low) are attributed to lamp ballasts (400-1500 kg), inadvertent generation by industrial processes (900 kg), caulk (160 kg), small capacitors (3-150 kg), large capacitors (10-80 kg), pigments and dyes (0.02-31 kg), and transformers (<2 kg). Recommendations to characterize the extent of PCB distribution and decrease exposures include assessment of PCBs in buildings (e.g., schools) and replacement of these materials, development of Best Management Practices (BMPs) to contain PCBs, reduction of inadvertent generation of PCBs in consumer products, expansion of environmental monitoring and public education, and research to identify specific PCB congener profiles in human tissues.

Measuring disparities in access to water based on the normative content of the human right

Measuring access to water in the Sustainable Development Goals era involves taking into account the human rights framework. Therefore, its content should be considered to conceptualize the level of service through adequate indicators and to follow-up inequities reduction at global, national and local level. This research develops and tests a methodology to measure intra-community disparities based on human right to water normative criteria through a stratified sampling, splitting households served by community based organizations and those self-provided. This approach implies considering much reduced populations, thus special care needs to be taken with sample sizes and uncertainty of estimators. The proposed methodology is practical to locate and accurately characterize minority sectors within rural communities and allows moving beyond central-tendency estimators. It implies higher costs for field data collection than traditional approaches, but this can be assumed given the relevance of the approach from a human rights perspective, which calls for adequate tools for equity-oriented policy making at local level. The research point out how results might be used to shape decision-making processes.

Biomonitoring Equivalents for interpretation of urinary fluoride

Exposure to fluoride is widespread due to its natural occurrence in the environment and addition to drinking water and dental products for the prevention of dental caries. The potential health risks of excess fluoride exposure include aesthetically unacceptable dental fluorosis (tooth mottling) and increased skeletal fragility. Numerous organizations have conducted risk assessments and set guidance values to represent maximum recommended exposure levels as well as recommended adequate intake levels based on potential public health benefits of fluoride exposure. Biomonitoring Equivalents (BEs) are estimates of the average biomarker concentrations corresponding to such exposure guidance values. The literature on daily urinary fluoride excretion rates as a function of daily fluoride exposure was reviewed and BE values corresponding to the available US and Canadian exposure guidance values were derived for fluoride in urine. The derived BE values range from 1.1 to 2.1mg/L (1.2–2.5μg/g creatinine). Concentrations of fluoride in single urinary spot samples from individuals, even under exposure conditions consistent with the exposure guidance values, may vary from the predicted average concentrations by several-fold due to within- and across-individual variation in urinary flow and creatinine excretion rates and due to the rapid elimination kinetics of fluoride. Thus, the BE values are most appropriately applied to screen population central tendency estimates for biomarker concentrations rather than interpretation of individual spot sample concentrations.

The intersection of turn-taking and repair: the timing of other-initiations of repair in conversation.

The transitions between turns at talk in conversation tend to occur quickly, with only a slight gap of ∼100–300 ms between them. This estimate of central tendency, however, hides a wealth of complex variation, as a number of factors, such as the type of turns involved, have been shown to influence the timing of turn transitions. This article considers one specific type of turn that does not conform to the statistical trend, namely turns that deal with troubles of speaking, hearing, and understanding, known as other-initiations of repair (OIR). The results of a quantitative analysis of 169 OIRs in face-to-face conversation reveal that the most frequent cases occur after gaps of ∼700 ms. Furthermore, OIRs that locate a source of trouble in a prior turn specifically tend to occur after shorter gaps than those that do not, and those that correct errors in a prior turn, while rare, tend to occur without delay. An analysis of the transitions before OIRs, using methods of conversation analysis, suggests that speakers use the extra time (i) to search for a late recognition of the problematic turn, (ii) to provide an opportunity for the speaker of the problematic turn to resolve the trouble independently, and (iii) to produce visual signals, such as facial gestures. In light of these results, it is argued that OIRs take priority over other turns at talk in conversation and therefore are not subject to the same rules and constraints that motivate fast turn transitions in general.

The Effect of Alcohol Hangover on Choice Response Time

The effect of alcohol hangover on cognitive processing has received little attention. We explored the effect of alcohol hangover on choice response time (RT), a dominant dependent variable in cognitive research. Prior research of the effect of hangover on RT has produced mixed findings; all studies reviewed relied exclusively on estimates of central tendency (e.g., mean RT), which has limited information value. Here we present novel analytical methods by going beyond mean RT analysis. Specifically, we examined performance in hangover conditions across the whole RT distribution by fitting ex-Gaussian models to participant data, providing a formal description of the RT distribution. This analysis showed detriments to performance under hangover conditions at the slower end of the RT distribution; RT variance was also increased under hangover conditions. We also fitted an explicit mathematical process model of choice RT — the diffusion model — to participant data, which estimates parameters reflecting psychologically-meaningful processes underlying choice RT. This analysis showed that hangover reduced information processing efficiency during response selection, and increased response caution; changes in these parameters reflect hangover affecting core decisional-components of RT performance. The implications of the data as well as the methods used for hangover research are discussed.

A review of soil and dust ingestion studies for children

Soil and dust ingestion by children may be important pathways of exposure to environmental contaminants. Contaminated soil and dust may end up on children's hands and objects, because they play close to the ground. These contaminants can be ingested by children, because they have a tendency to place objects, including their fingers, in their mouths. Assessing exposure through this pathway requires information about the amount of soil and dust ingested by children. Estimates of soil and dust ingestion and information on the prevalence of the behavior have been published in the literature, but research in this area is generally limited. Three methodologies have been used to quantify soil and dust ingestion rates. In this paper, these are referred to as the tracer element method, the biokinetic model comparison method, and the activity pattern method. This paper discusses the information available on the prevalence of soil and dust ingestion behavior, summarizes the three methodologies for quantifying soil and dust ingestion, and discusses their limitations. Soil ingestion data derived from studies that use these methodologies are also summarized. Although they are based on different estimation approaches, the central tendency estimates of soil and dust ingestion derived from the three methodologies are generally comparable.

Pooled biological specimens for human biomonitoring of environmental chemicals: Opportunities and limitations

Biomonitoring has become the "gold standard" in assessing chemical exposures, and has an important role in risk assessment. The pooling of biological specimens-combining multiple individual specimens into a single sample-can be used in biomonitoring studies to monitor levels of exposure and identify exposure trends or to identify susceptible populations in a cost-effective manner. Pooled samples provide an estimate of central tendency and may also reveal information about variation within the population. The development of a pooling strategy requires careful consideration of the type and number of samples collected, the number of pools required and the number of specimens to combine per pool in order to maximise the type and robustness of the data. Creative pooling strategies can be used to explore exposure-outcome associations, and extrapolation from other larger studies can be useful in identifying elevated exposures in specific individuals. The use of pooled specimens is advantageous as it saves significantly on analytical costs, may reduce the time and resources required for recruitment and, in certain circumstances, allows quantification of samples approaching the limit of detection. In addition, the use of pooled samples can provide population estimates while avoiding ethical difficulties that may be associated with reporting individual results.

Calculate or wait: Is man an eager or a lazy intuitive statistician?

Research on people's ability to act as intuitive statisticians has mainly focused on the accuracy of estimates of central tendency and variability. In this paper, we investigate two hypothesised cognitive processes by which people make judgements of distribution shape. The first claims that people spontaneously induce abstract representations of distribution properties from experience, including about distribution shape. The second process claims that people construct beliefs about distribution properties post hoc by retrieval from long-term memory of small samples from the distribution, implying format dependence with accuracy that differs depending on judgement format. Results from two experiments confirm the predicted format dependence, suggesting that people are often constrained by the post hoc assessment of distribution properties by sampling from long-term memory. The results, however, also suggest that, although post hoc sampling from memory seems to be the default process, under certain predictable circumstances people do induce abstract representations of distribution shape.

Background and Reflections on the Life Cycle Assessment Harmonization Project

Despite the ever-growing body of life cycle assessment (LCA) literature on electricity generation technologies, inconsistent methods and assumptions hamper comparison across studies and pooling of published results. Synthesis of the body of previous research is necessary to generate robust results to assess and compare environmental performance of different energy technologies for the benefit of policy makers, managers, investors, and citizens. With funding from the U.S. Department of Energy, the National Renewable Energy Laboratory initiated the LCA Harmonization Project in an effort to rigorously leverage the numerous individual studies to develop collective insights. The goals of this project were to: (1) understand the range of published results of LCAs of electricity generation technologies, (2) reduce the variability in published results that stem from inconsistent methods and assumptions, and (3) clarify the central tendency of published estimates to make the collective results of LCAs available to decision makers in the near term. The LCA Harmonization Project's initial focus was evaluating life cycle greenhouse gas (GHG) emissions from electricity generation technologies. Six articles from this first phase of the project are presented in a special supplemental issue of the Journal of Industrial Ecology on Meta-Analysis of LCA: coal (Whitaker et al. 2012), concentratingmore » solar power (Burkhardt et al. 2012), crystalline silicon photovoltaics (PVs) (Hsu et al. 2012), thin-film PVs (Kim et al. 2012), nuclear (Warner and Heath 2012), and wind (Dolan and Heath 2012). Harmonization is a meta-analytical approach that addresses inconsistency in methods and assumptions of previously published life cycle impact estimates. It has been applied in a rigorous manner to estimates of life cycle GHG emissions from many categories of electricity generation technologies in articles that appear in this special supplemental supplemental issue, reducing the variability and clarifying the central tendency of those estimates in ways useful for decision makers and analysts. Each article took a slightly different approach, demonstrating the flexibility of the harmonization approach. Each article also discusses limitations of the current research, and the state of knowledge and of harmonization, pointing toward a path of extending and improving the meta-analysis of LCAs.« less

Effect of non‐normality on test statistics for one‐way independent groups designs

The data obtained from one-way independent groups designs is typically non-normal in form and rarely equally variable across treatment populations (i.e., population variances are heterogeneous). Consequently, the classical test statistic that is used to assess statistical significance (i.e., the analysis of variance F test) typically provides invalid results (e.g., too many Type I errors, reduced power). For this reason, there has been considerable interest in finding a test statistic that is appropriate under conditions of non-normality and variance heterogeneity. Previously recommended procedures for analysing such data include the James test, the Welch test applied either to the usual least squares estimators of central tendency and variability, or the Welch test with robust estimators (i.e., trimmed means and Winsorized variances). A new statistic proposed by Krishnamoorthy, Lu, and Mathew, intended to deal with heterogeneous variances, though not non-normality, uses a parametric bootstrap procedure. In their investigation of the parametric bootstrap test, the authors examined its operating characteristics under limited conditions and did not compare it to the Welch test based on robust estimators. Thus, we investigated how the parametric bootstrap procedure and a modified parametric bootstrap procedure based on trimmed means perform relative to previously recommended procedures when data are non-normal and heterogeneous. The results indicated that the tests based on trimmed means offer the best Type I error control and power when variances are unequal and at least some of the distribution shapes are non-normal.

Central-tendency estimation and nearest-estimate classification of event related potentials

Event related potentials (ERPs) are modeled as random vectors in order to determine multivariate central-tendency (C-T) estimates of ERPs such as the arithmetic mean, geometric mean, harmonic mean, median, tri-mean, trimmed-mean, and the Winsorized mean. Additionally, it is shown that the C-T estimates can be used to implement various forms of minimum-distance classifiers for individual channels and for single-channel heterogeneous, multi-channel homogeneous, and multi-channel heterogeneous-homogenous ERP classification through decision fusion. The study also focuses on answering the following related questions: (a) How do the C-T ERP estimates compare with each other? (b) How do the performances of nearest-estimate classifiers compare with each other? (c) For a given ERP channel, do the heterogeneous nearest-estimate classifiers offer complementary information for improving performance through decision fusion? (d) Do the homogeneous nearest-estimate classifiers of different channels offer complementary information for improving performance through decision fusion? (e) Can the performance be improved by fusing the decisions of all or a selected subset of the entire classifier ensemble? These questions are answered by designing estimation and classification experiments using real 6-channel ERPs. It is shown that although the operations to compute the vector C-T estimates can be quite different, the ERP estimates are similar with respect to their overall waveform shapes and peak latencies. Furthermore, the results of the classification experiments show that by fusing homogeneous nearest-estimate classifier decisions across multiple channels, the classification accuracy can be improved significantly when compared with the accuracies of individual channel classifiers.

STAT1 Is a Master Regulator of Pancreatic β-Cell Apoptosis and Islet Inflammation

Cytokines produced by islet-infiltrating immune cells induce β-cell apoptosis in type 1 diabetes. The IFN-γ-regulated transcription factors STAT1/IRF-1 have apparently divergent effects on β-cells. Thus, STAT1 promotes apoptosis and inflammation, whereas IRF-1 down-regulates inflammatory mediators. To understand the molecular basis for these differential outcomes within a single signal transduction pathway, we presently characterized the gene networks regulated by STAT1 and IRF-1 in β-cells. This was done by using siRNA approaches coupled to microarray analysis of insulin-producing cells exposed or not to IL-1β and IFN-γ. Relevant microarray findings were further studied in INS-1E cells and primary rat β-cells. STAT1, but not IRF-1, mediates the cytokine-induced loss of the differentiated β-cell phenotype, as indicated by decreased insulin, Pdx1, MafA, and Glut2. Furthermore, STAT1 regulates cytokine-induced apoptosis via up-regulation of the proapoptotic protein DP5. STAT1 and IRF-1 have opposite effects on cytokine-induced chemokine production, with IRF-1 exerting negative feedback inhibition on STAT1 and downstream chemokine expression. The present study elucidates the transcriptional networks through which the IFN-γ/STAT1/IRF-1 axis controls β-cell function/differentiation, demise, and islet inflammation.

Variability and Uncertainty in Swedish Exposure Factors for Use in Quantitative Exposure Assessments

Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe--here represented by Sweden--and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments.

Great horned owl (Bubo virginianus) dietary exposure to PCDD/DF in the Tittabawassee River floodplain in Midland, Michigan, USA

Soils and sediments in the floodplain of the Tittabawassee River downstream of Midland, Michigan, USA contain elevated concentrations of polychlorinated dibenzofurans (PCDF) and polychlorinated dibenzo-p-dioxins (PCDD). As a long-lived, resident top predator, the great horned owl (Bubo virginianus; GHO) has the potential to be exposed to bioaccumulative compounds such as PCDD/DF. Site-specific components of the GHO diet were collected along 115 km of the Tittabawassee, Pine, Chippewa, and Saginaw Rivers during 2005 and 2006. The site-specific GHO biomass-based diet was dominated by cottontail rabbits (Sylvilagus floridanus) and muskrats (Ondatra zibethicus). Incidental soil ingestion and cottontail rabbits were the primary contributors of PCDD/DF to the GHO diet. The great horned owl daily dietary exposure estimates were greater in the study area (SA) (3.3 to 5.0 ng 2,3,7,8-TCDD equivalents (TEQ(WHO-avian))/kg body wt/d) than the reference area (RA) (0.07 ng TEQ(WHO-Avian)/kg body wt/d). Hazard quotients (HQs) based on central tendency estimates of the average daily dose and no-observable-adverse effect level (NOAEL) for the screech owl and uncertainty factors were <1.0 for both the RA and the SA. Hazard quotients based on upper end estimates of the average daily dose and NOAEL were <1.0 in the RA and up to 3.4 in the SA.

Chemical-specific screening criteria for interpretation of biomonitoring data for volatile organic compounds (VOCs) – Application of steady-state PBPK model solutions

The National Health and Nutrition Examination Survey (NHANES) generates population-representative biomonitoring data for many chemicals including volatile organic compounds (VOCs) in blood. However, no health or risk-based screening values are available to evaluate these data from a health safety perspective or to use in prioritizing among chemicals for possible risk management actions. We gathered existing risk assessment-based chronic exposure reference values such as reference doses (RfDs), reference concentrations (RfCs), tolerable daily intakes (TDIs), cancer slope factors, etc. and key pharmacokinetic model parameters for 47 VOCs. Using steady-state solutions to a generic physiologically-based pharmacokinetic (PBPK) model structure, we estimated chemical-specific steady-state venous blood concentrations across chemicals associated with unit oral and inhalation exposure rates and with chronic exposure at the identified exposure reference values. The geometric means of the slopes relating modeled steady-state blood concentrations to steady-state exposure to a unit oral dose or unit inhalation concentration among 38 compounds with available pharmacokinetic parameters were 12.0 μg/L per mg/kg-d (geometric standard deviation [GSD] of 3.2) and 3.2 μg/L per mg/m 3 (GSD = 1.7), respectively. Chemical-specific blood concentration screening values based on non-cancer reference values for both oral and inhalation exposure range from 0.0005 to 100 μg/L; blood concentrations associated with cancer risk-specific doses at the 1 E−05 risk level ranged from 5 E−06 to 6 E−02 μg/L. The distribution of modeled steady-state blood concentrations associated with unit exposure levels across VOCs may provide a basis for estimating blood concentration screening values for VOCs that lack chemical-specific pharmacokinetic data. The screening blood concentrations presented here provide a tool for risk assessment-based evaluation of population biomonitoring data for VOCs and are most appropriately applied to central tendency estimates for such datasets.

Using Median Regression to Obtain Adjusted Estimates of Central Tendency for Skewed Laboratory and Epidemiologic Data

Using Median Regression to Obtain Adjusted Estimates of Central Tendency for Skewed Laboratory and Epidemiologic Data

Relative Efficiency of Single‐Outlier Discordancy Tests for Processing Geochemical Data on Reference Materials and Application to Instrumental Calibrations by a Weighted Least‐Squares Linear Regression Model

Numerous studies report geochemical data on reference materials (RMs) processed by outlier‐based methods that use univariate discordancy tests. However, the relative efficiency of the discordancy tests is not precisely known. We used an extensive geochemical database for thirty‐five RMs from four countries (Canada, Japan, South Africa and USA) to empirically evaluate the performance of nine single‐outlier tests with thirteen test variants. It appears that the kurtosis test (N15) is the most powerful test for detecting discordant outliers in such geochemical RM databases and is closely followed by the Grubbs type tests (N1 and N4) and the skewness test (N14). The Dixon‐type tests (N7, N8, N9 and N10) as well as the Grubbs type test (N2) depicted smaller global relative efficiency criterion values for the detection of outlying observations in this extensive database. Upper discordant outliers were more common than the lower discordant outliers, implying that positively skewed inter‐laboratory geochemical datasets are more frequent than negatively skewed ones and that the median, a robust central tendency indicator, is likely to be biased especially for small‐sized samples. Our outlier‐based procedure should be useful for objectively identifying discordant outliers in many fields of science and engineering and for interpreting them accordingly. After processing these databases by single‐outlier discordancy tests and obtaining reliable estimates of central tendency and dispersion parameters of the geochemical data for the RMs in our database, we used these statistical data to apply a weighted least‐squares linear regression (WLR) model for the major element determinations by X‐ray fluorescence spectrometry and compared the WLR results with an ordinary least‐squares linear regression model. An advantage in using our outlier procedure and the new concentration values and uncertainty estimates for these RMs was clearly established.

Mergers and acquisitions and the determinants of bank total factor productivity: empirical evidence from Malaysia

In this paper, we employ alternate techniques to examine the impact of mergers and acquisitions on banks total factor productivity. These alternate techniques extend from use of the non-parametric, 'frontier'-oriented method of Malmquist Productivity Index (MPI) and include the more traditional regression-based approaches using central tendency estimates. Using data from the Malaysian banking sector, we find that the Malaysian banking sector has exhibited a higher total factor productivity level during the post-merger period. The empirical findings from the multivariate regression analysis suggest that income diversification and operating expenses are positively and significantly related to Malaysian banks total factor productivity, whereas credit risk exhibits negative relationship.

Using Median Regression to Obtain Adjusted Estimates of Central Tendency for Skewed Laboratory and Epidemiologic Data

Laboratory studies often involve analyses of highly skewed data for which means are not an adequate measure of central tendency because they are sensitive to outliers. Attempts to transform skewed data to symmetry are not always successful, and medians are better measures of central tendency for such skewed distributions. When medians are compared across groups, confounding can be an issue, so there is a need for adjusted medians. We illustrate the use of quantile regression to obtain adjusted medians. The method is illustrated by use of skewed nutrient data obtained from black and white men attending a prostate cancer screening. For 3 nutrients, saturated fats, caffeine, and vitamin K, we obtained medians adjusted by age, body mass index, and calories for men in each race group. Quantile regression, linear regression, and log-normal regression produced substantially different adjusted estimates of central tendency for saturated fats, caffeine, and vitamin K. Our method was useful for analysis of skewed and other nonnormally distributed continuous outcome data and for calculation of adjusted medians.