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PubMed1998

Synthesis of pharmacokinetic parameters of vancomycin via bootstrap methods.

OBJECTIVE: For the adjustment of individual vancomycin dosages, we estimate the important pharmacokinetic quantities half-life, clearance, and volume of distribution. MATERIAL: To obtain reliable information 293 observations from 244 patients were extracted from 23 published studies on vancomycin. Information about vancomycin's pharmacokinetics out of different sources represents an increase in sample size and, therefore, interpretive power. METHODS: Once the whole of the data had been stratified into a small number of homogeneous clusters based on cofactors, different (robust) estimators (mean, median, Winsorized, and trimmed mean) were calculated for the expected value of the pharmacokinetic parameters of vancomycin within the clusters. Measures of the statistical accuracy such as standard error, bias, mean square error, and confidence interval were estimated via bootstrap methods from large bootstrap sample sizes to compare the quality of the estimators. RESULTS: Due to the homogenization of the data all individual estimator functions yield very similar results and the empirical mean works fairly well as an estimate. The most frequently used estimator with the smallest estimated mean square error was the Winsorized mean.

Adult↗

PubMed2026

Identifying Single-Cell Expression Quantitative Trait Loci Using a Bootstrap Penalized Hurdle Model.

BACKGROUND: Expression quantitative trait loci (eQTL) analysis links genetic variants to gene expression levels, helping to uncover how genetic variation contributes to gene regulation. While traditional eQTL analyses rely on bulk RNA-seq data, recent advances in single-cell RNA sequencing (scRNA-seq) have made it possible to detect cell-type-specific eQTLs. However, the inherent sparsity and heterogeneity of scRNA-seq data present major challenges for standard modeling approaches. METHODS: In this paper, we propose a novel statistical framework, Bootstrap Penalized Hurdle regression model (BPHurdle), designed specifically for scRNA-seq data. BPHurdle employs a hurdle modeling framework, where a logistic component accounts for the excess zeros in single-cell expression data, and a Poisson component jointly evaluates the effects of multiple SNPs on positive gene expression levels. RESULTS: Through simulation studies, we show that BPHurdle achieves high accuracy and robustness in identifying regulatory variants. We further demonstrate its utility on a real dataset through a case study focusing on a subset of differentially expressed genes, where it successfully identifies reliable cell-type-specific eQTLs. CONCLUSIONS: Overall, BPHurdle offers an advanced and flexible approach for single-cell eQTL mapping, providing deeper insight into the genetic regulation of gene expression at cellular resolution.

Quantitative Trait Loci↗

PubMed1998

The use of simulation and bootstrap in information-based group sequential studies.

In this paper, we present an information-based design and monitoring procedure which applies to any type of model for any type of group sequential study provided there is a unique parameter of interest one can estimate efficiently. Simulation techniques are described to handle the design phase of this procedure. Since designs depend on potentially unreliable guesses of nuisance parameters, we propose a bootstrap method that uses the information available at the interim analysis times to generate projections and prediction intervals for the time at which the study will be fully powered. A monitoring board can use this information to decide whether a redesign of the trial is warranted. We also show how to use simulation to redesign studies in progress. We illustrate all of these techniques with data from AIDS Clinical Trial Group Protocol 021.

AIDS-Related Opportunistic Infections↗

PubMed1999

Bootstrap methods for adaptive designs.

Adaptive designs generate dependent sequences of random variables that are not exchangeable. Therefore, it is not obvious how to employ a resampling scheme for confidence interval estimation. We propose a simple procedure where observed response rates from an adaptive experiment are input to a simulation program. The program then generates sequences from the adaptive sampling scheme. We compare, via simulation, three bootstrap confidence intervals with the asymptotic confidence interval for two adaptive designs useful for clinical trials. A simple ranking of simulated response rates yields a confidence interval approximation with coverage close to 1-alpha in most cases. The method allows us to incorporate such complexities as staggered entry and delayed response. We give an example of its utility on a clinical trial of fluoxetine in depression.

Antidepressive Agents, Second-Generation↗

PubMed1999

Using the bootstrap for estimation in group sequential designs: an application to a clinical trial for nasopharyngeal cancer.

We investigate a resampling method for bias correction in group sequential designs with censored survival data using logrank testing. The method draws nested bootstrap samples of different sizes from the observed data in order to mimic the large sample independent increment property of statistics resulting from sequential designs. The motivation for this problem came from the very positive results and early termination of a randomized clinical trial for nasopharyngeal cancer co-ordinated by the Southwest Oncology Group.

Antimetabolites, Antineoplastic↗

PubMed1990

Bootstrapping: a tool for clinical research.

The use of the bootstrap sampling technique is applied to the type of data found in clinical research. Confidence intervals are computed for simulated values by use of SAS. By applying this approach, clinical researchers are free to explore topics that do not meet the requirements of traditional statistical analytic methods.

Acquired Immunodeficiency Syndrome↗

PubMed1993

A bootstrap approach to estimating power for linkage heterogeneity.

We examined the power of detecting linkage heterogeneity when the null hypothesis is that all families are linked to one locus (A) and the two alternative hypotheses are either 1) a proportion of the families are linked to locus A and the remaining families are linked to a second locus B or 2) a proportion of the families are linked to locus A or B and a third proportion of the families are unlinked to either locus. The power of detecting linkage heterogeneity is estimated for various proportions of families linked to loci A, B or unlinked to either locus (sampling under the alternative hypothesis). To estimate the significance level, the data set is sampled under the null hypothesis. For sampling under both hypotheses, a bootstrap approach is employed, sampling the simulated pedigrees with replacement. The power to detect linkage heterogeneity is strongest when the recombination fraction is 0 and equal proportions of the families are linked to loci A and B. The power decreases as the recombination fraction increases, the proportion of unlinked families increases and the disparity between the proportion of the families linked to either locus A or B increases. In the data set of 32 Duke Familial Alzheimer Disease families, when equal proportions of families are linked to loci A and B, the power to detect linkage heterogeneity is 0.94 using a likelihood ratio criterion of 10:1. The p value that corresponds to the likelihood ratio of 10:1 is estimated as 0.013 with a 95% confidence interval for p ranging from 0.012 to 0.014.

Aged↗

PubMed2003

Assessing and comparing costs: how robust are the bootstrap and methods based on asymptotic normality?

This article addresses and challenges some common perceptions in the statistical assessment of costs and cost-effectiveness in health economics. Cost data typically exhibit highly skew distributions. Two techniques whose validity does not depend on any specific form of underlying distribution are the bootstrap and methods based on asymptotic normality of sample means. These methods are generally thought to be appropriate for the analysis of cost data. We argue that, even when these methods are technically valid, they may often lead to inefficient and even misleading inferences. It is important to apply methods that recognise the skewness in cost data. We further demonstrate that it may also be important to incorporate relevant prior information in a Bayesian analysis.

Bayes Theorem↗

PubMedDate not supplied

The use of GLIM and the bootstrap in assessing a clinical trial of two drugs.

An approach is described for estimating the dose of a new drug which is equipotent to an established dose of an old drug. The approach is basically that of the parallel-line assay but it can allow for concomitant variables and, by exploiting the facilities available in the statistical computer package GLIM (generalized linear interactive modelling), the approach can be applied when the residuals conform to one of a number of distributions and, with suitable safeguards, to continuous, discrete and even 'scored' responses. In some circumstances, it is necessary to obtain confidence limits by Efron's 'bootstrap' technique. The method is illustrated with results from a trial of two premedicant drugs in children.

Biometry↗

PubMedDate not supplied

Constructing a bootstrap confidence interval for the unknown concentration in radioimmunoassay.

The statistical problem associated with radioimmunoassay is known as calibration or inverse regression. In the current study, we propose a bootstrap procedure aimed at constructing an inverse confidence interval for the univariate calibration problem. The calibration curve is estimated either parametrically or by non-parametric regression. The methods are illustrated by an example.

Calibration↗

PubMed1995

Simple confidence intervals for standardized rates based on the approximate bootstrap method.

This paper presents simple expressions for the confidence intervals of indirect and direct standardized rates, based on the approximate bootstrap confidence (ABC) method of DiCiccio and Efron. For indirect rates, the ABC method compares favourably with the exact methods. An exact method is not available for direct standardized rates. I, therefore, compared the ABC to other simple procedures for confidence intervals, namely: the standard normal, log-normal, and a recent method proposed by Dobson et al. Simulation studies of the coverage properties of these methods for direct standardized rates show that the ABC method performs best, with balanced tail probabilities close to their expected values.

Adolescent↗

PubMed2001

Bootstrap-type confidence intervals for quantiles of the survival distribution.

In this paper we outline and illustrate an easy to program method for analytically calculating both parametric and non-parametric bootstrap-type confidence intervals for quantiles of the survival distribution based on right censored data. This new approach allows for the incorporation of covariates within the framework of parametric models. The procedure is based upon the notion of fractional order statistics and is carried forth using a simple beta transformation of the estimated survival function (parametric or non-parametric). It is the only direct method currently available in the sense that all other methods are based on inverting test statistics or employing confidence intervals for other survival quantities. We illustrate that the new method has favourable coverage probabilities for median confidence intervals as compared to six other competing methods.

Bile Duct Neoplasms↗

PubMed1997

Bootstrapping Word Boundaries: A Bottom-up Corpus-Based Approach to Speech Segmentation

Speech is continuous, and isolating meaningful chunks for lexical access is a nontrivial problem. In this paper we use neural network models and more conventional statistics to study the use of sequential phonological probabilities in the segmentation of an idealized phonological transcription of the London-Lund Corpus; these speech data are representative of genuine conversational English. We demonstrate, first, that the distribution of phonetic segments in English is an important cue to segmentation, and, second, that the distributional information is such that it might allow the infant, beginning with only a sensitivity to the statistics of subsegmental primitives, to bootstrap into a series of increasingly sophisticated segmentation competences, ending with an adult competence. We discuss the relation between the behavior of the models and existing psycholinguistic studies of speech segmentation. In particular, we confirm the utility of the Metrical Segmentation Strategy (Cutler & Norris, 1988) and demonstrate a route by which this utility might be recognized by the infant, without requiring the prior specification of categories like "syllable" or "strong syllable."

Journal Article↗

PubMed2000

Application of bootstrap techniques to physical mapping.

Ordering genetic markers or clones from a genomic library into a physical map is a central problem in genetics. In the presence of errors, there is no efficient algorithm known that solves this problem. Based on a standard heuristic algorithm for it, we present a method to construct a confidence neighborhood for a computed solution. We compute a confidence value for putative local solutions derived from bootstrap replicates of the original solution. In the reliable parts, the confidence neighborhood and the computed solution tend to coincide. In regions that are ill-defined by the data, the neighborhood contains additional reasonable alternatives. This offers the possibility of designing further experiments for the badly defined regions to improve the quality of the physical map. We analyze our approach by a simulation study and by application to a dataset of the genome of the bacterium Xylella fastidiosa.

Algorithms↗

PubMed1998

Biogeography of Sulawesian shrews: testing for their origin with a parametric bootstrap on molecular data.

In order to identify the zoogeographic origin of shrews (genus Crocidura) living on the oceanic island of Sulawesi, 15 taxa from Southeast Asia and 1 from Europe were examined for sequence variation in a segment (617 bp) of the mitochondrial cytochrome b gene. The null hypothesis of a monophyletic origin of all Sulawesian shrews was investigated by a phylogenetic reconstruction using maximum parsimony. According to a parametric bootstrap which simulated sequence evolution for these taxa, the null hypothesis could be rejected as highly unlikely (P < 0.01). Therefore, the molecular phylogeny strongly suggests that overwater colonization of Sulawesi by shrews succeeded on at least two occasions. The first, relatively ancient wave of colonizers radiated and gave rise to a surprizingly diverse assemblage of at least five species which now coexist in perfect sympatry on Sulawesi. The second wave, of more recent origin, gave rise to Crocidura nigripes, a species which retained close genetic affinities with other Malay shrews.

Animals↗

PubMed1994

Estimating errors and confidence intervals for branch lengths in phylogenetic trees by a bootstrap approach.

A method, based on the bootstrap procedure, is proposed for the estimation of branch-length errors and confidence intervals in a phylogenetic tree for which equal rates of substitution among lineages do not necessarily hold. The method can be used to test whether an estimated internodal distance is significantly greater than zero. In the application of the method, any estimator of genetic distances, as well as any tree reconstruction procedure (based on distance matrices), can be used. Also the method is not limited by the number of species involved in the phylogenetic tree. An example of the application of the method in the reconstruction of the phylogenetic tree for the four hominoid species--human, chimpanzee, gorilla, and orangutan--is shown.

Animals↗

PubMedDate not supplied

Biometrical evaluation of bioequivalence trials using a bootstrap individual direct curve comparison method.

Bioequivalence of two medicinal, or veterinary, products is established by comparing the mean of bioavailability measures, such as AUC and Cmax, following administration of the test (T) and reference (R) products. However, the use of these parameters has several drawbacks, e.g. they do not take into consideration the overall pharmacokinetic profile shape. Therefore, concerns have been raised regarding their appropriateness for assessment of bioequivalence. To overcome the limitations of these bioequivalence parameters, direct curve comparison metrics methods were recently proposed on an average basis. In this paper, an individual based direct curve comparison method for assessing bioequivalence is proposed. The bioequivalence of T and R in each subject is evaluated by a new curve comparison metrics delta. The metrics delta is the absolute sum of the difference between two curves. The significance of the metrics for each subject is assessed by bootstrapping. An overall bioequivalence of T and R may be considered if less than 25% of the subjects show statistically different profiles.

Area Under Curve↗

PubMed2000

Factors affecting oral cyclosporin disposition after heart transplantation: bootstrap validation of a population pharmacokinetic model.

OBJECTIVE: To determine factors affecting the population pharmacokinetics of oral cyclosporin (CsA) in cardiac allograft recipients during the first 3 weeks after surgery. METHODS: Data were obtained from routine trough monitoring and from two extra samples drawn during a dosing interval on a randomly selected day. Whole blood CsA concentrations were assayed using high-performance liquid chromatography (HPLC). Approximately equal numbers of patients were prescribed Sandimmun (SAN) or Neoral (NEO) CsA formulations. Parameter values of a one-compartment kinetic model with first-order absorption and elimination were sought together with the inter-patient and intra-patient variances using the NONMEM program. RESULTS: Improved fits resulted from using the following expression in the model to adjust apparent bioavailability as a function of post-operative day (POD): f= 0.2 + 10 x ABS (POD-5)/[(POD + 7) x 60]. The CsA clearance (CL/f) was found to be influenced by current body weight (WT). There was an absorption lag time of about 35 min with SAN, but zero lag time with NEO. Oral bioavailability (f) was increased by about 35% with concomitant diltiazem and about 18% with NEO. The CL/f was 10% higher during the daytime than at night. The final pharmacokinetic model was validated using 200 bootstrap samples of the original data. CONCLUSIONS: Using a validated population modelling approach, it was found that a number of factors influence the pharmacokinetics of CsA during the early postoperative period in cardiac transplant patients. These influences affecting oral bioavailability and clearance may need to be taken into account for maintaining appropriate concentrations of CsA in the bloodstream.

Adolescent↗