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At least 1,747 records · Page 97Linked to original sources
PubMed1994

Workplace and environmental air contaminant concentrations measured by open path Fourier transform infrared spectroscopy: a statistical process control technique to detect changes from normal operating conditions.

Open path Fourier transform infrared (OP-FTIR) spectroscopy is a new air monitoring technique that can be used to measure concentrations of air contaminants in real or near-real time. OP-FTIR spectroscopy has been used to monitor workplace gas and vapor exposures, emissions from hazardous waste sites, and to track emissions along fence lines. This paper discusses a statistical process control technique that can be used with air monitoring data collected with an OP-FTIR spectrometer to detect departures from normal operating conditions in the workplace or along a fence line. Time series data, produced by plotting consecutive air sample concentrations in time, were analyzed. Autocorrelation in the time series data was removed by fitting dynamic models. Control charts were used with the residuals of the model fit data to determine if departures from defined normal operating conditions could be rapidly detected. Shewhart and exponentially weighted moving average (EWMA) control charts were evaluated for use with data collected under different room air flow and mixing conditions. Under rapidly changing conditions the Shewhart control chart was able to detect a leak in a simulated process area. The EWMA control chart was found to be more sensitive to drifts and slowly changing concentrations in air monitoring data. The time series and statistical process control techniques were also applied to data obtained during a field study at a chemical plant. A production area of an acrylonitrile, 1,3-butadiene, and styrene (ABS) polymer process was monitored in near-real time. Decision logics based on the time series and statistical process control technique introduced suggest several applications in workplace and environmental monitoring. These applications might include signaling of an alarm or warning, increasing levels of worker respiratory protection, or evacuation of a community, when gas and vapor concentrations are determined to be out-of-control.

Air Pollutants↗
PubMed2004

Some statistical and regulatory issues in the evaluation of genetic and genomic tests.

The genomics revolution is reverberating throughout the worlds of pharmaceutical drugs, genetic testing and statistical science. This revolution, which uses single nucleotide polymorphisms (SNPs) and gene expression technology, including cDNA and oligonucleotide microarrays, for a range of tests from home-brews to high-complexity lab kits, can allow the selection or exclusion of patients for therapy (responders or poor metabolizers). The wide variety of US regulatory mechanisms for these tests is discussed. Clinical studies to evaluate the performance of such tests need to follow statistical principles for sound diagnostic test design. Statistical methodology to evaluate such studies can be wide ranging, including receiver operating characteristic (ROC) methodology, logistic regression, discriminant analysis, multiple comparison procedures resampling, Bayesian hierarchical modeling, recursive partitioning, as well as exploratory techniques such as data mining. Recent examples of approved genetic tests are discussed.

Animals↗
PubMed2004

How can statistical approaches enhance transdisciplinary study of drug misuse prevention?

Application of statistical techniques in transdisciplinary research includes statistical model selection and model specification. This paper presents statistical models used in drug misuse prevention research. The historical roots of these models are discussed to illustrate the numerous disciplines from which different techniques originated. Single and multilevel approaches are described to illustrate methods of synthesizing perspectives from different scientific arenas. Using single-level approaches in transdisciplinary research, these models can easily incorporate broader theoretical considerations and more integrated hypotheses by representing each discipline with a set of variables. Simultaneous testing of every set of variables obtained from different disciplines may provide more comparable results to identify critical factors associated with substance-use behavior. Using multilevel approaches, more powerful syntheses across disciplines can be achieved by representing each discipline at a different level.

Biomedical Research↗
PubMed2005

Comparison of the granulation behavior of three different excipients in a laboratory fluidized bed granulator using statistical methods.

The granulation process and, subsequently, the tableting behavior of the resulting granules of alpha-lactose-monohydrate, dicalcium phosphate anhydrous, and potato starch were investigated using statistical designs. The three substances were chosen due to their differences in granulation and tableting behavior, such as water solubility, swelling, and compressional properties. Granulation process variables, namely the inlet air temperature, spray rate, binder concentration of granulating solution, and inlet air flow rate were investigated. A central composite design was applied to study the granulation of alpha-lactose-monohydrate. Granulations of dicalcium phosphate and potato starch were investigated using a 2(3) factorial design, in which the effects of the inlet air temperature, spray rate, and binder concentration were considered. To compare the granulation behavior of theses substances the particle size distribution, angle of repose, and yield of the granules were used as responses for the statistical designs. The granules were compressed into tablets and the tensile strength was used as an additional statistical response. Based on the process parameters, models were developed using multiple regression modeling for each examined response. These models were then used to optimize the granulation process that provides granules with a Sauter mean diameter of D32 between 300 and 500 microm, an angle of repose smaller than 36 degrees and a granule yield above 90%. Moreover, the values of the tensile strength of the tablets should be between 1.6 and 2.5 N/mm2. The intersections of the response surfaces of each examined substance were compared using contour plots. To achieve the largest "satisfactory zone," the granulations of milled alpha-lactose-monohydrate, dicalcium phosphate, or potato starch should be performed at low inlet air temperatures.

Calcium Phosphates↗
PubMed2004

Mixture of paraquat and linuron formulations examined for genotoxicity in Wistar rats by the in vivo micronucleus test--evaluation by different statistical tests.

The purposes of the present study were the evaluation of the genotoxic effect of mixture of paraquat and linuron commercial formulations. the evaluation of the possible interaction between the two pesticides and the comparison of different statistical tests used for the data analysis. For this purposes the bone marrow micronucleus test was used. Dose levels were determined in the base of the LD50 of each component. According the experimental design, three dose levels of the mixture were administered at groups of five Wistar rats from each sex. Sampling time was 24 h for all groups plus 48 h for the highest dose and the positive control groups. In addition, the formulations were studied separately at two dose levels. Cyclophosphamide was used as positive control. For the statistical analysis of the results different parametric and nonparametric tests were used. The mixture of the two pesticides under the study conditions was not proven to be genotoxic. However, cytotoxicity and no signs of interaction were indicated. Minor declinations between the statistical tests used for data analysis observed.

Administration, Oral↗
PubMed1992

Assessment of noise in a digital image using the join-count statistic and the Moran test.

We assume that the data bits of a pixel in digital images can be divided into signal and noise bits. The signal bits occupy the most significant part of the pixel and the noise bits the least significant part. The signal part of each pixel are correlated while the noise parts are uncorrelated. Two statistical methods, the Moran test and the join-count statistic, are used to examine the noise parts. Images from three digital modalities--computerized tomography, magnetic resonance and computed radiography--are used for the evaluation of the noise bits. A residual image is formed by subtracting the original image from its smoothed version. The noise level in the residual image is then identical to that in the original image. Both statistical tests are then performed on the bit planes of the residual image. The results show that most digital images contain only 8-9 bits of correlated information. Both methods are easy to implement and fast to perform.

Magnetic Resonance Imaging↗
PubMed2002

A non-parametric bootstrap approach for analysing the statistical properties of SPECT and PET images.

Knowledge of the statistical properties of reconstructed single photon emission computed tomography (SPECT) and positron emission tomography (PET) images would be helpful for optimizing acquisition and image processing protocols. We describe a non-parametric bootstrap approach to accurately estimate the statistical properties of SPECT or PET images whatever the noise properties in the projections and the reconstruction algorithm. Using analytical simulations and real PET data, this method is shown to accurately predict the statistical properties, including the variance and covariance, of reconstructed pixel values for both linear (filtered backprojection) and non-linear (ordered subset expectation maximization) reconstruction algorithms.

Algorithms↗
PubMed2002

Effects of temporal modelling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections.

Artefacts can result when reconstructing a dynamic image sequence from inconsistent single photon emission computed tomography (SPECT) projection data acquired by a slowly rotating gantry. The artefacts can lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying volumes of interest on the images. Insufficient sampling and truncation of projections by cone-beam collimators can cause additional artefacts. To overcome these sources of bias in conventional image based dynamic data analysis, we have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modelling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view. In the present work, we perform Monte Carlo simulations to study the effects of the temporal modelling on the statistical variability of the reconstructed spatiotemporal distributions. The simulations utilize fast methods for fully four-dimensional (4D) direct estimation of spatiotemporal distributions and their statistical uncertainties, using a spatial segmentation and temporal B-splines. The simulation results suggest that there is benefit in modelling higher orders of temporal spline continuity. In addition, the accuracy of the time modelling can be increased substantially without unduly increasing the statistical uncertainty, by using relatively fine initial time sampling to capture rapidly changing activity distributions.

Algorithms↗
PubMed2002

Statistical and heuristic image noise extraction (SHINE): a new method for processing Poisson noise in scintigraphic images.

Poisson noise is one of the factors degrading scintigraphic images, especially at low count level, due to the statistical nature of photon detection. We have developed an original procedure, named statistical and heuristic image noise extraction (SHINE), to reduce the Poisson noise contained in the scintigraphic images, preserving the resolution, the contrast and the texture. The SHINE procedure consists in dividing the image into 4 x 4 blocks and performing a correspondence analysis on these blocks. Each block is then reconstructed using its own significant factors which are selected using an original statistical variance test. The SHINE procedure has been validated using a line numerical phantom and a hot spots and cold spots real phantom. The reference images are the noise-free simulated images for the numerical phantom and an extremely high counts image for the real phantom. The SHINE procedure has then been applied to the Jaszczak phantom and clinical data including planar bone scintigraphy, planar Sestamibi scintigraphy and Tl-201 myocardial SPECT. The SHINE procedure reduces the mean normalized error between the noisy images and the corresponding reference images. This reduction is constant and does not change with the count level. The SNR in a SHINE processed image is close to that of the corresponding raw image with twice the number of counts. The visual results with the Jaszczak phantom SPECT have shown that SHINE preserves the contrast and the resolution of the slices well. Clinical examples have shown no visual difference between the SHINE images and the corresponding raw images obtained with twice the acquisition duration. SHINE is an entirely automatic procedure which enables halving the acquisition time or the injected dose in scintigraphic acquisitions. It can be applied to all scintigraphic images, including PET data, and to all low-count photon images.

Algorithms↗
PubMed2005

An application of Bayesian statistical methods to adaptive radiotherapy.

In adaptive radiotherapy, measured patient-specific setup variations are used to modify the patient setup and treatment plan, potentially many times during the treatment course. To estimate the setup adjustments and re-plan the treatment, the measured data are usually processed using Kalman filtering or by computing running averages. We propose, as an alternative, the use of Bayesian statistical methods, which combine a population (prior) distribution of systematic and random setup errors with the measurements to determine a patient-specific (posterior) probability distribution. The posterior distribution can either be used directly in the re-planning of the treatment or in the generation of statistics needed for adjustments. Based on the assumption that day-to-day setup variations are independent and identically distributed Normal distributions, we can efficiently compute parameters of the posterior distribution from parameters of the prior distribution and statistics of the measurements. We illustrate a simple procedure to apply the method in practice to adaptive radiotherapy, allowing for multiple adjustments of treatment parameters during the course of treatment.

Algorithms↗
PubMed2005

EUD-based radiotherapy treatment plan evaluation: incorporating physical and Monte Carlo statistical dose uncertainties.

The purpose of this work is to quantify the impact of dose uncertainty on radiobiologically based treatment plan evaluation. Dose uncertainties are divided into two categories: physical and statistical. Physical dose uncertainty is associated with the systematic and/or random errors incurred during treatment planning and/or delivery. The dose uncertainty associated with Monte Carlo calculated dose distributions is deemed statistical and noted as artificial with respect to the actual delivered dose. We will refer to all dose uncertainties that arise from either calculation or delivery as stochastic. Both physical and statistical dose uncertainties are considered at the intra- and inter-voxel levels. To account for voxel dose uncertainty, we calculate the mean survival fraction (SF) for the random dose deposition. Mathematically, the expression for the mean survival fraction is identical to that used by Niemierko (1997 Med. Phys. 24 103-10) in defining equivalent uniform dose (EUD). To distinguish between spatial and probabilistic dose variations, we define equivalent stochastic dose (ESD) as a voxel dose that gives the mean expected survival fraction for the randomly deposited dose. For a probability density function f(D), that represents the probabilistic voxel dose, SF(ESD) can be calculated by convolving SF(D) with f(D). In the case where the probability density function follows a Gaussian distribution, an analytic expression is derived for SF(ESD). The derived expression is verified using the Monte Carlo method and ESD values calculated with varied radiosensitivities for cases of 60 and 70 Gy at 2 Gy per fraction. The analytic expression is also extended to account for a multi-voxel dose distribution that incorporates a spatial dose heterogeneity. The results show that survival fraction increases with an increased dose uncertainty. This reduction depends on radiobiological parameters attributed to tissue and tumour. For tissue, ESD drops to 55% of the mean physical dose when the dose has a 10% intra- and inter-voxel dose uncertainty and inhomogeneity.

Body Burden↗
PubMed2005

Parallel statistical image reconstruction for cone-beam x-ray CT on a shared memory computation platform.

Statistical reconstruction methods offer possibilities of improving image quality as compared to analytical methods, but current reconstruction times prohibit routine clinical applications. To reduce reconstruction times we have parallelized a statistical reconstruction algorithm for cone-beam x-ray CT, the ordered subset convex algorithm (OSC), and evaluated it on a shared memory computer. Two different parallelization strategies were developed: one that employs parallelism by computing the work for all projections within a subset in parallel, and one that divides the total volume into parts and processes the work for each sub-volume in parallel. Both methods are used to reconstruct a three-dimensional mathematical phantom on two different grid densities. The reconstructed images are binary identical to the result of the serial (non-parallelized) algorithm. The speed-up factor equals approximately 30 when using 32 to 40 processors, and scales almost linearly with the number of cpus for both methods. The huge reduction in computation time allows us to apply statistical reconstruction to clinically relevant studies for the first time.

Algorithms↗
PubMed2006

A statistical test to determine the quality of accelerometer data.

Accelerometer data quality can be inadequate due to data corruption or to non-compliance of the subject with regard to study protocols. We propose a simple statistical test to determine if accelerometer data are of good quality and can be used for analysis or if the data are of poor quality and should be discarded. We tested several data evaluation methods using a group of 105 subjects who wore Motionlogger actigraphs (Ambulatory Monitoring, Inc.) over a 15 day period to assess sleep quality in a study of health outcomes associated with stress among police officers. Using leave-one-out cross-validation and calibration-testing methods of discrimination statistics, error rates for the methods ranged from 0.0167 to 0.4046. We found that the best method was to use the overall average distance between consecutive time points and the overall average mean amplitude of consecutive time points. These values gave us a classification error rate of 0.0167. The average distance between points is a measure of smoothness in the data, and the average mean amplitude between points gave an average reading. Both of these values were then normed to determine a final statistic, K, which was then compared to a cut-off value, K(C), to determine data quality.

Acceleration↗
PubMed2001

Statistical significance of probabilistic sequence alignment and related local hidden Markov models.

The score statistics of probabilistic gapped local alignment of random sequences is investigated both analytically and numerically. The full probabilistic algorithm (e.g., the "local" version of maximum-likelihood or hidden Markov model method) is found to have anomalous statistics. A modified "semi-probabilistic" alignment consisting of a hybrid of Smith-Waterman and probabilistic alignment is then proposed and studied in detail. It is predicted that the score statistics of the hybrid algorithm is of the Gumbel universal form, with the key Gumbel parameter lambda taking on a fixed asymptotic value for a wide variety of scoring systems and parameters. A simple recipe for the computation of the "relative entropy," and from it the finite size correction to lambda, is also given. These predictions compare well with direct numerical simulations for sequences of lengths between 100 and 1,000 examined using various PAM substitution scores and affine gap functions. The sensitivity of the hybrid method in the detection of sequence homology is also studied using correlated sequences generated from toy mutation models. It is found to be comparable to that of the Smith-Waterman alignment and significantly better than the Viterbi version of the probabilistic alignment.

Algorithms↗
PubMed2004

LD-SPatt: large deviations statistics for patterns on Markov chains.

Statistics on Markov chains are widely used for the study of patterns in biological sequences. Statistics on these models can be done through several approaches. Central limit theorem (CLT) producing Gaussian approximations are one of the most popular ones. Unfortunately, in order to find a pattern of interest, these methods have to deal with tail distribution events where CLT is especially bad. In this paper, we propose a new approach based on the large deviations theory to assess pattern statistics. We first recall theoretical results for empiric mean (level 1) as well as empiric distribution (level 2) large deviations on Markov chains. Then, we present the applications of these results focusing on numerical issues. LD-SPatt is the name of GPL software implementing these algorithms. We compare this approach to several existing ones in terms of complexity and reliability and show that the large deviations are more reliable than the Gaussian approximations in absolute values as well as in terms of ranking and are at least as reliable as compound Poisson approximations. We then finally discuss some further possible improvements and applications of this new method.

Computational Biology↗
PubMed2005

The statistical analysis of spatially clustered genes under the maximum gap criterion.

Statistical validation of gene clusters is imperative for many important applications in comparative genomics which depend on the identification of genomic regions that are historically and/or functionally related. We develop the first rigorous statistical treatment of max-gap clusters, a cluster definition frequently used in empirical studies. We present exact expressions for the probability of observing an individual cluster of a set of marked genes in one genome, as well as upper and lower bounds on the probability of observing a cluster of h homologs in a pairwise whole-genome comparison. We demonstrate the utility of our approach by applying it to a whole-genome comparison of E. coli and B. subtilis. Code for statistical tests is available at.

Bacillus subtilis↗
PubMed2005

Why evidence for the fetal origins of adult disease might be a statistical artifact: the "reversal paradox" for the relation between birth weight and blood pressure in later life.

Some researchers have recently questioned the validity of associations between birth weight and health in later life. They argue that these associations might be due in part to inappropriate statistical adjustment for variables on the causal pathway (such as current body size), which creates an artifactual statistical effect known as the "reversal paradox." Computer simulations were conducted for three hypothetical relations between birth weight and adult blood pressure. The authors examined the effect of statistically adjusting for different correlations between current weight and birth weight and between current weight and adult blood pressure to assess their impact on associations between birth weight and blood pressure. When there was no genuine relation between birth weight and blood pressure, adjustment for current weight created an inverse association whose size depended on the magnitude of the positive correlations between current weight and birth weight and between current weight and blood pressure. When there was a genuine inverse relation between birth weight and blood pressure, the association was exaggerated following adjustment for current weight, whereas a positive relation between birth weight and blood pressure could be reversed after adjusting for current weight. Thus, researchers must consider the reversal paradox when adjusting for variables that lie within causal pathways.

Adult↗
PubMed2006

Predicting germination response to temperature. II. Three-dimensional regression, statistical gridding and iterative-probit optimization using measured and interpolated-subpopulation data.

BACKGROUND AND AIMS: Most current thermal-germination models are parameterized with subpopulation-specific rate data, interpolated from cumulative-germination-response curves. The purpose of this study was to evaluate the relative accuracy of three-dimensional models for predicting cumulative germination response to temperature. Three-dimensional models are relatively more efficient to implement than two-dimensional models and can be parameterized directly with measured data. METHODS: Seeds of four rangeland grass species were germinated over the constant-temperature range of 3 to 38 degrees C and monitored for subpopulation variability in germination-rate response. Models for estimating subpopulation germination rate were generated as a function of temperature using three-dimensional regression, statistical gridding and iterative-probit optimization using both measured and interpolated-subpopulation data as model inputs. KEY RESULTS: Statistical gridding is more accurate than three-dimensional regression and iterative-probit optimization for modelling germination rate and germination time as a function of temperature and subpopulation. Optimization of the iterative-probit model lowers base-temperature estimates, relative to two-dimensional cardinal-temperature models, and results in an inability to resolve optimal-temperature coefficients as a function of subpopulation. Residual model error for the three-dimensional model was extremely high when parameterized with measured-subpopulation data. Use of measured data for model evaluation provided a more realistic estimate of predictive error than did evaluation of the larger set of interpolated-subpopulation data. CONCLUSIONS: Statistical-gridding techniques may provide a relatively efficient method for estimating germination response in situations where the primary objective is to estimate germination time. This methodology allows for direct use of germination data for model parameterization and automates the significant computational requirements of a two-dimensional piece-wise-linear model, previously shown to produce the most accurate estimates of germination time.

Elymus↗