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PubMed1983

Intrauterine growth retardation detected in several species by non-normal birthweight distributions.

The statistical distribution of birthweights in 64 litters of pigs, 48 litters of dogs, 59 litters of rabbits, 130 litters of rats and 46 litters of mice was examined. Birthweight followed a Gaussian or normal distribution in about two-thirds of the litters inspected, as judged visually using a normal probability plot, and by the W-test statistic. In the remainder, a single outlying observation in an otherwise normal sample was detected by Dixon's test, and/or a separate sub-population of low birthweight animals could be identified by fitting two normal populations to the observed samples. In the non-Gaussian litters, the average proportion of affected members was 40% of the litter. These results suggest that growth-retarded neonates should not be regarded simply as the tail-end of a normal distribution.

Animals↗
PubMed1996

Estimation of dietary exposure to chemicals: a case study illustrating methods of distributional analyses for food consumption data.

There are a number of sources of variability in food consumption patterns and residue levels of a particular chemical (e.g., pesticide, food additive) in commodities that lead to an expected high level of variability in dietary exposures across a population. This paper focuses on examples of consumption pattern survey data for specific commodities, namely that for wine and grape juice, and demonstrates how such data might be analyzed in preparation for performing stochastic analyses of dietary exposure. Data from the NIAAA/NHIS wine consumption survey were subset for gender and age group and, with matched body weight data from the survey database, were used to define empirically-based percentile estimates for wine intake (microliter wine/kg body weight) for the strata of interest. The data for these two subpopulations were analyzed to estimate 14-day consumption distributional statistics and distributions for only those days on which wine was consumed. Data subsets for all wine-consuming adults and wine-consuming females ages 18 through 45, were determined to fit a lognormal distribution (R2 = 0.99 for both datasets). Market share data were incorporated into estimation of chronic exposures to hypothetical chemical residues in imported table wine. As a separate example, treatment of grape juice consumption data for females, ages 18-40, as a simple lognormal distribution resulted in a significant underestimation of intake, and thus exposure, because the actual distribution is a mixture (i.e., multiple subpopulations of grape juice consumers exist in the parent distribution). Thus, deriving dietary intake statistics from food consumption survey data requires careful analysis of the underlying empirical distributions.

Adolescent↗
PubMed2000

Predicting particulate (PM10) personal exposure distributions using a random component superposition statistical model.

This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless "attenuation factor" between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM10 measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities. Using a fixed 24-hr attenuation factor as a first approximation derived from regression analysis for the respondents, the distributions of nonambient PM10 personal exposures were obtained for each city. Although the mean ambient PM10 concentrations in the three cities varied from 27.9 micrograms/m3 in Toronto to 60.9 micrograms/m3 in Phillipsburg to 94.1 micrograms/m3 in Riverside, the mean nonambient components of personal exposures were found to be closer: 52.6 micrograms/m3 in Toronto; 52.4 micrograms/m3 in Phillipsburg; and 59.2 micrograms/m3 in Riverside. The three frequency distributions of the nonambient components of exposure also were similar in shape, giving support to the hypothesis that nonambient concentrations are similar across different cities and populations. These results indicate that, if the ambient concentrations were completely controlled and set to zero in all three cities, the median of the remaining personal exposures to PM10 would range from 32.0 micrograms/m3 (Toronto) to 34.4 micrograms/m3 (Phillipsburg) to 48.8 micrograms/m3 (Riverside). The highest-exposed 30% of the population in the three cities would still be exposed to 24-hr average PM10 concentrations of 47-74 micrograms/m3; the highest 20% would be exposed to concentrations of 56-92 micrograms/m3; the highest 10% to concentrations of 88-131 micrograms/m3; and the highest 5% to 133-175 micrograms/m3, due only to indoor sources and activities. The distribution for the difference between personal exposures and indoor concentrations, or the "personal cloud," also was similar in the three cities, with a mean of 30-35 micrograms/m3, suggesting that the personal cloud accounts for more than half of the nonambient component of PM10 personal exposure in the three cities. Using only the ambient measurements in Toronto, the nonambient data from THEES in Phillipsburg was used to predict the entire personal exposure distribution in Toronto. The PM10 exposure distribution predicted by the model showed reasonable agreement with the PM10 personal exposure distribution measured in Toronto. These initial results suggest that the RCS model may be a powerful tool for predicting personal exposure distributions and statistics in other cities where only ambient particle data are available.

Air Pollution↗
PubMed1988

Interaction of temperature and other environmental variables influencing plant distribution.

Statistical analyses of the relationships between the patterns of distribution of plants with C4 photosynthesis and Crassulacean acid metabolism (CAM) have revealed a variety of correlations with environmental variables. The worldwide abundance of C4 grasses, relative to C3 grasses, is highly positively correlated with growing season temperature. However, microscale analyses have revealed that C4 grasses are more abundant than C3 grasses in habitats with high levels of solar irradiance and low moisture availability. There are numerous exceptions to these generalizations. C4 dicots generally are more abundant in habitats characterized by high rates of evaporation. Species possessing CAM occur in habitats having low levels of soil moisture store. In the Cactaceae such habitats also have very high potential rates of evaporation and the CAM pathway is the primary mechanism of the uptake of atmospheric CO2. In contrast many species of the Crassulaceae grow in habitats with lower potential rates of evaporation and the CAM pathway is less important or not used at all in the uptake of atmospheric CO2.

Environment↗
PubMed1995

Genetic mapping of quantitative trait loci for traits with ordinal distributions.

Statistical methods for mapping quantitative trait loci relative to genetic markers are now well established for continuous traits with normal distributions. However, many traits of economic importance are recorded on a discrete, ordinal scale. Here we describe a model developed for the analysis of ordinal traits, such as degree of difficulty in calving or categories of plant disease resistance. The model estimates the distance from the quantitative trait locus to neighbouring genetic markers, and also genetic parameters, either as gene effects on an underlying continuous scale or as probabilities of the observed categories. The model is tested on simulated data and is compared with an analysis based on mixtures of normal distributions. The ordinal model is found to estimate the parameters more accurately, especially when the number of categories is small or when only one linked marker is available.

Animal Husbandry↗
PubMed1990

Computerized ultrasound B-scan texture analysis of experimental fatty liver disease: influence of total lipid content and fat deposit distribution.

Statistical pattern recognition procedures allow a quantitative description of ultrasound-B-scan image texture. According to well-established animal models, different types of fatty liver disease were induced in female Wistar rats. For the correlation of the computerized ultrasound image with its underlying histology a variable tissue model based on histomorphological data, texture analysis of the histological image and biochemical measurements of total lipid, water and hydroxyproline content was created. Whereas a regional arrangement of large fat deposits leads to a significant increase in the "mean grey level" (measure of image brightness) of the ultrasound-B-scan image, there is no difference in image brightness between normal liver tissue and liver steatosis for the tissue model with diffuse homogeneous fatty infiltration. It is demonstrated by multiple linear regression analysis that the "mean grey level" of the ultrasound-B-scan image depends not only on total lipid content but even more on the histomorphological fat deposit distribution.

Animals↗
PubMed1997

Monte Carlo simulation of a planar shoulder model.

Although variability of anthropometric measures within a population is a well established phenomenon, most biomechanical models are based on average parameter values. For example, optimisation models for predicting muscle forces from net joint reaction moments typically use average muscle moment arms. However, understanding the distribution of musculoskeletal morbidity within a population requires information about the variation of tissue loads within the population. This study investigated the use of Monte Carlo simulation techniques to predict the statistical distribution of deltoid and rotator cuff muscle forces during static arm elevation. Muscle moment arms were modelled either as independent random variables or jointly distributed random variables. Moment arm data was collected on 22 cadaver specimens. The results demonstrated the use of Monte Carlo techniques to describe the statistical distribution of muscle forces. Although assuming statistically independent moment arms did affect the statistical distribution shape, that assumption did not affect the median predicted forces. The standard deviations of muscle forces predicted using Monte Carlo techniques were similar to the standard deviation of muscle force predictions using the whole sample of specimens. It is concluded that Monte Carlo simulation techniques are a useful tool to analyse the interindividual variability of rotator cuff muscle forces.

Biomechanical Phenomena↗
PubMed1992

Gamma distribution and house 222Rn measurements.

The statistical distribution of 222Rn measurements from basements and first floors of homes in northeastern Pennsylvania was investigated. The gamma distribution was statistically significantly superior to the normal distribution (p less than 0.005) in describing the frequency distribution of the logarithm of observed 222Rn levels. The fit to the data was closer both in the central portion and in the upper tail. The gamma distribution has certain characteristics that make it generally useful in the study of environmental toxic agents where several different exposures over a lifetime occur and must be combined, as for risk assessment or for statistical power calculations for epidemiologic studies.

Air Pollution, Indoor↗
PubMed1993

Are accidents poisson distributed? A statistical test.

The common and convenient assumption in accident count analysis, that accidents are Poisson-distributed, is reexamined. Two statistical tests, for evaluating the assumption are described and compared. It is shown that a test based upon a combinatorial analysis is much more accurate than the alternative chi-square test when accident counts are expected to be small. The more accurate test is used to reinterpret data on accident count variability, the results indicating that the Poisson distribution is appropriate for the analysis of accidents at individual sites.

Accidents↗
PubMed1997

Integrated mismatch negativity (MMNi): a noise-free representation of evoked responses allowing single-point distribution-free statistical tests.

If the repeated presentation of a single (standard) auditory stimulus is randomly interspersed with a second acoustically different (deviant) stimulus, the cortical activity evoked by the deviant stimulus can contain a negative component known as the mismatch negativity (MMN). The MMN is derived by subtracting the averaged response evoked by the standard stimulus from that evoked by the deviant stimulus. When the magnitude of the response is small or the signal-to-noise ratio is poor, it is difficult to judge the presence or absence of the MMN simply by visual inspection, and statistical detection techniques become necessary. A method of analysis is proposed to quantify the magnitude and statistically evaluate the presence of the MMN based on time-integrated evoked responses. This paper demonstrates the use of this integrated mismatch negativity (MMNi) analysis to detect the MMN evoked by stimulus contrasts near the perceptual threshold of two subjects. The MMNi, by virtue of being equivalent to a low-pass filtered response, presents an almost noise-free estimate of MMN magnitude. A single measure of the integrated evoked response at a fixed time point is used in a distribution-free statistic that compares the magnitude of the averaged response evoked by the deviant stimulus with a magnitude distribution derived from 200 subaveraged responses to the standard stimulus (with the number of sweeps per average equal to that of the deviant stimulus). This allows a calculation of the exact probability for the null hypothesis that the negative magnitude of the response evoked by the deviant stimulus is drawn from the magnitude distribution of responses evoked by the standard stimulus. Rejection of this hypothesis provides objective evidence of the presence of the MMN.

Acoustic Stimulation↗
PubMed2001

Using serial imaging data to model variabilities in organ position and shape during radiotherapy.

A model is proposed for incorporating the effects of organ motion into the calculation of dose in a statistical fashion based on serial imaging measurements of organ motion. These measurements can either come from a previously studied population of patients, or they can be specific to the particular patient undergoing therapy. The statistical distribution underlying the measurements of organ motion, including the changes in organ shape, is reconstructed non-parametrically without requiring any assumptions about its functional form. The model is thus capable of simulating organ motions that are not present in the original measurements, yet nonetheless come from the same underlying statistical distribution. The present model overcomes two particular limitations of many organ motion models: (a) the fact that they do not account for changes in organ shape, and (b) the fact that they make physically unrealistic assumptions about the functional form of the statistical distribution of organ motion, such as assuming that it is Gaussian. The present model can form the foundation of methods for the more accurate and clinically relevant calculation of the dose to the target volume and normal tissues.

Algorithms↗