Computer-simulated effect of errors in infusion duration and blood sampling times on pharmacokinetic calculations for gentamicin.
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Blood Specimen Collection↗
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[Assessment of occupational exposures to industrial hazardous substances. I. A proposed method based on interday fluctuation of contaminant concentrations for evaluating employee's exposure averages (TWAs)].
Occupational exposures to potentially hazardous substances may vary considerably because of factors such as sampling and analytical errors, and intraday and interday environmental fluctuations in contaminant concentration. Of these factors, day-to-day environmental fluctuations most likely affect daily exposure averages over days, weeks, months or years. A new method based on day-to-day fluctuations of daily exposure averages (geometric standard deviation) was developed for making reliable assessment of the employee's exposure situation. It is assumed that daily exposure averages of a worker are lognormally and independently distributed statistically. Finally, a classification scheme on the basis of n days measurements is presented. 95% upper limit or arithmetic mean of individual exposure averages (8-h TWAs) can be evaluated in comparison with an established standard. The method may provide an approximate estimate because of statistical premise, but it can be utilized for practical purposes, particularly, in case where only one or two days are being monitored. An action level concept based on random sampling and analytical errors and interday variations developed by OSHA/NIOSH, and a sampling and decision scheme based on one-sided tolerance limits proposed by Tuggle (1982) are also discussed.
Data Interpretation, Statistical↗
An examination of methods for sample size recalculation during an experiment.
In designing experiments, investigators frequently can specify an important effect that they wish to detect with high power, without the ability to provide an equally certain assessment of the variance of the response. If the experiment is designed based on a guess of the variance, an under-powered study may result. To remedy this problem, there have been several procedures proposed that obtain estimates of the variance from the data as they accrue and then recalculate the sample size accordingly. One class of procedures is fully sequential in that it assesses after each response whether the current sample size yields the desired power based on the current estimate of the variance. This approach is efficient, but it is not practical or advisable in many situations. Another class of procedures involves only two or three stages of sampling and recalculates the sample size based on the observed variance at designated times, perhaps coinciding with interim efficacy analyses. The two-stage approach can result in substantial oversampling, but it is feasible in many situations, whereas the three-stage approach corrects the problem of oversampling, but is less feasible. We propose a procedure that aims to combine the advantages of both the fully sequential and the two-stage approaches. This quasi-sequential procedure involves only two stages of sampling and it applies to the stopping rule from the fully sequential procedure to data beyond the initial sample which we obtain via multiple imputation. We show through simulations that when the initial sample size is substantially less than the correct sample size, the mean squared error of the final sample size calculated from the quasi-sequential procedure can be considerably less than that from the two-stage procedure. We compare the distributions of these recalculated sample sizes and discuss our findings for alternative procedures, as well.
Anti-HIV Agents↗
Automated measurement of 13C enrichment in carbon dioxide derived from submicromole quantities of L-(1-13C)-leucine.
The 13C enrichment of the carboxyl carbon of leucine was measured by isotope ratio mass spectrometry after conversion to CO2 by reaction with ninhydrin in a Vacutainer and cryogenic purification using the Finnigan MAT Breath Gas Analysis System designed for processing 13C breath test samples. The sources of error which arise with submicromole samples are examined and corrections provided for suboptimal mass spectrometer signals and contamination of the evolved CO2 with CO2 from the reaction medium. The main limitations to the accuracy and precision of the method are not instrumental but arise from the contamination with residual CO2 in the reaction medium, and this sets a lower limit of around 0.25 mumol leucine on the practical sample size. This is an improvement of about five-fold on the previous manual method of CO2 isolation.
Autoanalysis↗
Bilateral recovering of sharp edges on feature-insensitive sampled meshes.
A variety of computer graphics applications sample surfaces of 3D shapes in a regular grid without making the sampling rate adaptive to the surface curvature or sharp features. Triangular meshes that interpolate or approximate these samples usually exhibit relatively big error around the insensitive sampled sharp features. This paper presents a robust general approach conducting bilateral filters to recover sharp edges on such insensitive sampled triangular meshes. Motivated by the impressive results of bilateral filtering for mesh smoothing and denoising, we adopt it to govern the sharpening of triangular meshes. After recognizing the regions that embed sharp features, we recover the sharpness geometry through bilateral filtering, followed by iteratively modifying the given mesh's connectivity to form singlewide sharp edges that can be easily detected by their dihedral angles. We show that the proposed method can robustly reconstruct sharp edges on feature-insensitive sampled meshes.
Algorithms↗
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels and spotted DNA microarrays.
BACKGROUND: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge requires careful examination of the performance of a range of statistical models, as well as empirical examination of the effect of replication on the power to resolve these differences. RESULTS: New models are derived and software is developed for the analysis of microarray ratio data. These models incorporate multiplicative small error terms, and error standard deviations that are proportional to expression level. The fastest and most powerful method incorporates additive small error terms and error standard deviations proportional to expression level. Data from four studies are profiled for the degree to which they reveal statistically significant differences in gene expression. The gene expression level at which there is an empirical 50% probability of a significant call is presented as a summary statistic for the power to detect small differences in gene expression. CONCLUSIONS: Understanding the resolution of difference in gene expression that is detectable as significant is a vital component of experimental design and evaluation. These small differences in gene expression level are readily detected with a Bayesian analysis of gene expression level that has additive error terms and constrains samples to have a common error coefficient of variation. The power to detect small differences in a study may then be determined by logistic regression.
Algorithms↗
Papanicolaou smear sensitivity for adenocarcinoma in situ of the cervix. A study of 34 cases.
The sensitivity of cervical smears for adenocarcinoma in situ (AIS) is not known, nor is it known whether false-negative smears are due to sampling or to screening or interpretive errors. In 16 of 34 patients with AIS, 38 negative smears were reported 2 weeks to 7 years before biopsy. Thirty-one of these negative smears were rescreened, and 17 (55%) were retrospectively diagnosed as abnormal. Ten of the 17 had numerous well-preserved AIS cells: 5 with very small, crowded AIS cells, possibly originally mistaken for endometrial cells, and 5 with large groups in which AIS cells resembled reactive endocervical cells. Four smears were confirmed sampling errors. The sensitivity of cervical smears for AIS was 55% to 72%. Improved sampling of the endocervical canal offers cytologists the opportunity to diagnose AIS. This study demonstrates that this opportunity may not be fully exploited. Small "endometrioid" AIS cells and AIS cells resembling reactive endocervical cells may be mistaken for benign cells, thus decreasing sensitivity.
Adenocarcinoma↗
Optimal allocation of replicates for measurement evaluation studies.
Optimal experimental design is important for the efficient use of modern high-throughput technologies such as microarrays and proteomics. Multiple factors including the reliability of measurement system, which itself must be estimated from prior experimental work, could influence design decisions. In this study, we describe how the optimal number of replicate measures (technical replicates) for each biological sample (biological replicate) can be determined. Different allocations of biological and technical replicates were evaluated by minimizing the variance of the ratio of technical variance (measurement error) to the total variance (sum of sampling error and measurement error). We demonstrate that if the number of biological replicates and the number of technical replicates per biological sample are variable, while the total number of available measures is fixed, then the optimal allocation of replicates for measurement evaluation experiments requires two technical replicates for each biological replicate. Therefore, it is recommended to use two technical replicates for each biological replicate if the goal is to evaluate the reproducibility of measurements.
Computational Biology↗
A preliminary statistical examination of the effects of uncertainty and variability on environmental regulatory criteria for ozone.
Basing the quantitative expression of environmental regulatory standards and associated compliance criteria on statistical principles has recently received attention in Europe, most visibly in a study by the UK Royal Commission on Environmental Pollution. These issues are timely for consideration in the USA, where a recent periodic review of National Ambient Air Quality Standards (NAAQS) has led to revision of the regulatory standards for ambient ozone and particulate matter. Salient statistical issues include accounting for errors of the first and second kind due to sampling and measurement error. These issues appear routine statistically and also may seem absent from regulations, but neither is necessarily the case. This paper is directed towards developing a methodology for examining the problem of dealing with uncertainty and variation in environmental regulations and compliance criteria. Our approach is illustrated through statistical analysis of the (old) 1 hour and the (new) 8 hour standards for ambient ozone, based on intensive monitoring in California's San Joaquin Valley during summer 1990 performed under the SARMAP Project. This paper presents preliminary findings based on quantifying measurement error or precision in terms of small-scale spatial and temporal variability, laying the groundwork for future work.
Air Pollutants↗
Assessment of actual significance levels for covariate effects in NONMEM.
The objectives of this study were to assess the difference between actual and nominal significance levels, as judged by the likelihood ratio test, for hypothesis tests regarding covariate effects using NONMEM, and to study what factors influence these levels. Also, a strategy for obtaining closer agreement between nominal and actual significance levels was investigated. Pharmacokinetic (PK) data without covariate relationships were simulated from a one compartment i.v. bolus model for 50 individuals. Models with and without covariate relationships were then fitted to the data, and differences in the objective function values were calculated. Alterations were made to the simulation settings; the structural and error models, the number of individuals, the number of samples per individual and the covariate distribution. Different estimation methods in NONMEM were also tried. In addition, a strategy for estimating the actual significance levels for a specific data set, model and parameter was investigated using covariate randomization and a real data set. Under most conditions when the first-order (FO) method was used, the actual significance level for including a covariate relationship in a model was higher than the nominal significance level. Among factors with high impact were frequency of sampling and residual error magnitude. The use of the first-order conditional estimation method with interaction (FOCE-INTER) resulted in close agreement between actual and nominal significance levels. The results from the covariate randomization procedure of the real data set were in agreement with the results from the simulation study. With the FO method the actual significance levels were higher than the nominal, independent of the covariate type, but depending on the parameter influenced. When using FOCE-INTER the actual and nominal levels were similar. The most important factors influencing the actual significance levels for the FO method are the approximation of the influence of the random effects in a nonlinear model, a heteroscedastic error structure in which an existing interaction between interindividual and residual variability is not accounted for in the model, and a lognormal distribution of the residual error which is approximated by a symmetric distribution. Estimation with FOCE-INTER and the covariate randomization procedure provide means to achieve agreement between nominal and actual significance levels.
Adult↗
The vitamin A activity of beta-carotene in growing pigs. 1. Effect of a supplementation of a grain soya bean meal diet with vitamin A or beta-carotene on the liver vitamin A storage.
In 3 experiments with a total of 113 growing pigs, supplements of 1,000 to 9,000 IU vitamin A or 2 to 100 mg beta-carotene to vitamin A and beta-carotene free grains soyabean-meal-diets were tested. The liver samples were taken by biopsy or after slaughtering. The error of biopsy sampling was defined in preliminary experiments. The initial liver vitamin A depots were checked by slaughtering of 5 piglets of each group. The vitamin A content was analyzed by the anhydromethod or fluorometrically. In all 3 experiments, the different vitamin or provitamin intake did not influence feed intake and growth at any time. Highly significant linear relations were found between the intake of vitamin A or beta-carotene and the storage in the liver. Due to the higher relative liver weight, younger animals had a lower vitamin A concentration in this organ. Related to the tested beta-carotene dose of 2, 4, 8, 50 and 100 mg/kg feed, a vitamin A activity of 360, 320, 290, 130 and 80 micrograms retinol equivalents per mg beta-carotene was found. The conversion of beta-carotene into vitamin A decreases inversely to the beta-carotene intake. The vitamin A activity of synthetic beta-carotene which is higher than the beta-carotene analyzed in feedstuffs is discussed.
Animal Feed↗
Effect of genotyping error on type-I error rate of affected sib pair studies with genotyped parents.
OBJECTIVE: In affected sib pair studies without genotyped parents the effect of genotyping error is generally to reduce the type I error rate and power of tests for linkage. The effect of genotyping error when parents have been genotyped is unknown. We investigated the type I error rate of the single-point Mean test for studies in which genotypes of both parents are available. METHODS: Datasets were simulated assuming no linkage and one of five models for genotyping error. In each dataset, Mendelian-inconsistent families were either excluded or regenotyped, and then the Mean test applied. RESULTS: We found that genotyping errors lead to an inflated type I error rate when inconsistent families are excluded. Depending on the genotyping-error model assumed, regenotyping inconsistent families has one of several effects. It may produce the same type I error rate as if inconsistent families are excluded; it may reduce the type I error, but still leave an anti-conservative test; or it may give a conservative test. Departures of the type I error rate from its nominal level increase with both the genotyping error rate and sample size. CONCLUSION: We recommend that markers with high error rates either be excluded from the analysis or be regenotyped in all families.
Family↗
Multi-objective genetic algorithm-based sample selection for partial least squares model building with applications to near-infrared spectroscopic data.
In this study, multi-objective genetic algorithms (GAs) are introduced to partial least squares (PLS) model building. This method aims to improve the performance and robustness of the PLS model by removing samples with systematic errors, including outliers, from the original data. Multi-objective GA optimizes the combination of these samples to be removed. Training and validation sets were used to reduce the undesirable effects of over-fitting on the training set by multi-objective GA. The reduction of the over-fitting leads to accurate and robust PLS models. To clearly visualize the factors of the systematic errors, an index defined with the original PLS model and a specific Pareto-optimal solution is also introduced. This method is applied to three kinds of near-infrared (NIR) spectra to build PLS models. The results demonstrate that multi-objective GA significantly improves the performance of the PLS models. They also show that the sample selection by multi-objective GA enhances the ability of the PLS models to detect samples with systematic errors.
Algorithms↗
High-throughput SNP allele-frequency determination in pooled DNA samples by kinetic PCR.
We have developed an accurate, yet inexpensive and high-throughput, method for determining the allele frequency of biallelic polymorphisms in pools of DNA samples. The assay combines kinetic (real-time quantitative) PCR with allele-specific amplification and requires no post-PCR processing. The relative amounts of each allele in a sample are quantified. This is performed by dividing equal aliquots of the pooled DNA between two separate PCR reactions, each of which contains a primer pair specific to one or the other allelic SNP variant. For pools with equal amounts of the two alleles, the two amplifications should reach a detectable level of fluorescence at the same cycle number. For pools that contain unequal ratios of the two alleles, the difference in cycle number between the two amplification reactions can be used to calculate the relative allele amounts. We demonstrate the accuracy and reliability of the assay on samples with known predetermined SNP allele frequencies from 5% to 95%, including pools of both human and mouse DNAs using eight different SNPs altogether. The accuracy of measuring known allele frequencies is very high, with the strength of correlation between measured and known frequencies having an r(2) = 0.997. The loss of sensitivity as a result of measurement error is typically minimal, compared with that due to sampling error alone, for population samples up to 1000. We believe that by providing a means for SNP genotyping up to thousands of samples simultaneously, inexpensively, and reproducibly, this method is a powerful strategy for detecting meaningful polymorphic differences in candidate gene association studies and genome-wide linkage disequilibrium scans.
Animals↗
A test for deviation from island-model population structure.
The neutral island model forms the basis for several estimation models that relate patterns of genetic structure to microevolutionary processes. Estimates of gene flow are often based on this model and may be biased when the model's assumptions are violated. An appropriate test for violations is to compare FST scores for individual loci to a null distribution based on the average FST taken over multiple loci. A parametric bootstrap method is described here based on Wright's beta-distribution to generate null distributions of FST for each locus. These null distributions account for error introduced by sampling populations, individuals and loci, and also biological sources of error, including variable alleles/locus and inbreeding. Confidence limits can be obtained directly from these distributions. Significant deviations from the island model may be the result of selection, deviations from the island model's migration pattern, nonequilibrium conditions, or other deviations from island-model assumptions. Only strong biases are likely to be detected because of the inherently large sampling variation of FST. Nevertheless, a coefficient, Nb, describing bias in the spread of the beta-distribution in units comparable to the gene flow parameter, Nm, can be obtained for each locus. In samples from populations of the butterfly Coenonympha tullia, the loci Idh-1, Mdh-1, Pgi and Pgm showed significantly lower FST than expected.
Animals↗
Sample to sample carryover: a source of analytical laboratory error and its relevance to integrated clinical chemistry/immunoassay systems.
BACKGROUND: Integrated systems that combine clinical chemistry and immunoassay analyzers are used routinely. Sample to sample carryover is an inherent risk and can cause erroneously high patient test results for immunoassays. IVD manufacturers and laboratories must be aware of this phenomenon and guard against it. METHODS: We used a sample carryover protocol that directs the clinical chemistry module to process samples with very high immunoassay analyte concentrations followed by samples with very low concentrations for the same analyte. Low concentration samples were then tested by the immunoassay module to determine if the clinical chemistry module caused primary sample tube to primary sample tube carryover of the immunoassay analyte. RESULTS: Sample carryover was assessed on the Abbott ci8200 for HBsAg, AFP, beta-hCG, and PSA. Observed HBsAg carryover met the design specification of <0.1 ppm. Carryover for the other analytes was <0.1 ppm or below the assay limit of detection. CONCLUSIONS: IVD manufacturers must design integrated systems to minimize primary specimen tube carryover and avoid analytical laboratory error that can impact patient safety. Carryover testing is difficult for clinical laboratories to perform in order to verify system performance. Laboratories must consider the potential for specimen carryover and its impact on results whether moving primary sample tubes between separate analyzers or using an integrated system.
Clinical Chemistry Tests↗
Confidence intervals and sample-size calculations for the sisterhood method of estimating maternal mortality.
The sisterhood method is an indirect method of estimating maternal mortality that has, in comparison with conventional direct methods, the dual advantages of ease of use in the field and smaller sample-size requirements. This report describes how to calculate a standard error to quantify the sampling variability for this method. This standard error can be used to construct confidence intervals and statistical tests and to plan the size of a sample survey that employs the sisterhood method. Statistical assumptions are discussed, particularly in relation to the effective sample size and to effects of extrabinomial variation. In a worked example of data from urban Pakistan, a maternal mortality ratio of 153 (95 percent confidence interval between 96 and 212) deaths per 100,000 live births is estimated.
Age Factors↗
Intelligibility of stops and fricatives in tracheoesophageal speech.
UNLABELLED: Listener accuracy in identifying voiced and voiceless stops and fricatives in tracheoesophageal (TE) and laryngeal speech were compared. Sixteen TE and ten laryngeal speakers produced ten phonemes embedded in a nonsense word in a carrier phrase. Four experienced listeners phonetically transcribed the experimental phonemes. As expected, perceptual error rates were higher for the TE samples for all comparisons completed. The dominant error for laryngeal samples was a misperception of manner of production. The dominant error for TE samples was a perception of voiced for voiceless phonemes. Such voicing misperceptions occurred more frequently for fricatives than stops. Previous studies have implicated the vibratory characteristics of the pharyngoesophageal (PE) segment for the voicing errors in TE speech. However, PE features would not fully explain why stops were less affected than fricatives and why the expected error was reversed for two TE phonemes (perceptions of voiceless for voiced consonants). LEARNING OUTCOMES: (1) As a result of this activity, the participant will be able to identify the most common listener misperceptions of tracheoesophageal speech. (2) As a result of this activity, the participant will be able to discuss possible reasons for the predominant error that occurs.
Aged↗