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PubMedDate not supplied

Asymptotic variances of QTL estimators with selective DNA pooling.

Investigation on QTL-marker linkage usually requires a great number of observed recombinations, inferred from combined analysis of phenotypes and genotypes. To avoid costly individual genotyping, inferences on QTL position and effects can instead make use of marker allele frequencies. DNA pooling of selected samples makes allele frequency estimation feasible for studies involving large sample sizes. Linkage studies in outbred populations have traditionally exploited half-sib family designs; within the animal production context, half-sibships provide large families that are highly suitable for DNA pooling. Estimators for QTL position and effect have been proposed that make use of information from flanking markers. We present formulas derived by the delta method for the asymptotic variance of these estimators.

Chromosome Mapping↗
PubMed1999

Internal pilot studies II: comparison of various procedures.

The two-stage design involves sample size recalculation using an interim variance estimate. Stein proposed the design in 1945; biostatisticians recently have shown renewed interest in it. Wittes and Brittain proposed a modification aimed at greater efficiency; Gould and Shih proposed a similar procedure, but with a different interim variance estimate based on blinded data. We compare the power of Stein's original test, an idealized version of the Wittes-Brittain test, and a theoretical optimal test which can be approximated in practice. We also compare two procedures that control the conditional type I error rate given the actual final sample size: Gould and Shih's procedure and a newly proposed 'second segment' procedure. The comparison among the first three procedures indicates that the Stein test is, unexpectedly, the test of choice under the original design alternative, whereas the approximate-optimal and Wittes-Brittain procedures appear to have superior power for detecting smaller treatment differences. As between the latter two procedures, the second segment procedure is more powerful when many observations are likely to be taken after the interim resizing, whereas otherwise the Gould-Shih procedure is superior.

Analysis of Variance↗
PubMed2006

Inverse estimation of nonpoint sources of fecal coliform for establishing allowable load for Wye River, Maryland.

An estimation of the nonpoint sources of fecal coliform (FC) has been formulated as an inverse parameter estimation problem, using FC observation data from the receiving waters. An inverse algorithm was integrated into the three-dimensional transport model, HEM-3D. The modified Gauss-Newton method was used for the optimal estimation of the loads. The approach is straightforward and requires less effort in modification of the existing hydrodynamic model. Model experiments were conducted to investigate the feasibility of load estimation in a tidal river. The parameter uncertainty and accuracy associated with load estimation are discussed using data sets with different sampling sizes. The inverse model was applied to the tidal Wye River, Maryland, USA, to estimate FC nonpoint sources and to develop an allowable load for the river to attain water quality standards. The model results suggest that the inverse modeling approach is suitable for estimating FC nonpoint sources. The inverse method not only provides an efficient approach to assess the contribution of nonpoint sources, but has the additional advantage of addressing the problems of the uncertainty and error associated with FC simulation in the estuary using hydrodynamic models.

Feces↗
PubMed1997

Brazilian multicentric study of psychiatric morbidity. Methodological features and prevalence estimates.

BACKGROUND: Psychiatric morbidity studies in developing countries have used diagnostic procedures of low reliability, without a clinical definition of caseness, producing descriptive data with limited application for mental health planning. METHOD: A two-stage cross-sectional design (with a sample size of 6476) was conducted to estimate the prevalence of DSM-III psychiatric diagnoses in three metropolitan areas of Brazil (Brasília, São Paulo and Porto Alegre). All subjects were screened for the presence of psychopathology with a 44-item instrument (the QMPA) and a subsample was selected for a psychiatric interview. RESULTS: Age-adjusted prevalence of cases potentially in need of care ranged from 19% (São Paulo) to 34% (Brasília and Porto Alegre). Anxiety disorders comprised the highest prevalences (up to 18%). Alcoholism yielded the most consistent prevalence levels, around 8% in all sites. Depression showed great variation between areas: from less than 3% (São Paulo and Brasília) to 10% (Porto Alegre). CONCLUSIONS: Overall prevalences were high in comparison with previous studies conducted in Brazil. A female excess of non-psychotic disorders (anxiety, phobias, somatisation and depression) and a male excess for alcoholism were consistently found.

Age Factors↗
PubMed1998

Validity of an estimator of reproductive success.

Lifetime reproductive success is a major component of individual fitness and a central dependent variable for the study of natural selection. For long-lived animals, such as apes or baboons, assessment of lifetime reproductive success requires observations of identified individuals in continuous, long-term studies from which it is difficult and often impossible to obtain an adequate sample of necessary reproductive and survival data. This situation can be alleviated by the availability of a valid measure that uses incomplete reproductive histories to estimate the lifetime reproductive success of individuals. The validity of one such estimator was tested by determining if, after 10.5 years of studying free-ranging female baboons, it predicted lifetime reproductive success obtained from full reproductive histories after 21.5 years. Validity was evaluated for seven criteria of success, ranging from the number of a female's live births to the number of her offspring that reached the age of 72 months. Moderate to good prediction of lifetime reproductive success by the estimator was found for criteria of offspring living to 36 months or more. After 10.5 years, complete reproductive life spans were available for only eight females. Using the estimator, analytic potential, via sample representativeness and size, was improved at 10.5 years by an increase from a sample of eight to between 34 and 62, depending upon the criterion used, and at 21.5 years from 39 to 70. With a valid estimator, the opportunity to study lifetime reproductive success of a long-lived species is substantially improved without having to depend upon rarely available, uninterrupted data collection for 20-60 years.

Animals↗
PubMed2000

Spatial distribution and sampling plans for Thrips palmi (Thysanoptera: Thripidae) infesting fall potato in Korea.

The spatial distribution of adult and immature Thrips palmi Karny on fall potato, Solanum tuberosum L., on Cheju Island, Korea, was studied over a 2-yr period by visually inspecting potato leaves. The majority of thrips collected from the leaves were observed in the top one-third of the plant. The within-field spatial patterns of adults and immature thrips were aggregated. The slopes and intercepts of Taylor's power law did not differ among adults and immature thrips. A fixed-precision-level sampling plan was developed using the parameters from Taylor's power law and was tested with resampling simulations using eight independent data sets. Over a wide range of densities, the simulation demonstrated that actual sampling precision (d = SEM/mean) values at d = 0.25 averaged < 0.24 in all cases. A binomial sampling plan for estimating mean density was developed using an empirical model evaluated at tally thresholds (the minimum number of insects present before a leaf is considered infested) of one, three, five, and eight thrips per leaf. Increasing sampling size had little effect on the precision of the estimated mean regardless of tally threshold (T). However, increasing T had a dramatic effect on precision. The best tally threshold for estimating thrips density based on the applicable density ranges and the precision of the model was T = 5. A binomial sampling plan with a tally threshold of five and a fixed sample size of 30 leaves should be an effective replacement for enumerative counts when thrips average < 10 per leaf.

Animals↗
PubMed2006

Direct determination of the number-weighted mean radius and polydispersity from dynamic light-scattering data.

We compare results for the number-weighted mean radius and polydispersity obtained either by directly fitting number distributions to dynamic light-scattering data or by converting results obtained by fitting intensity-weighted distributions. We find that results from fits using number distributions are angle independent and that converting intensity-weighted distributions is not always reliable, especially when the polydispersity of the sample is large. We compare the results of fitting symmetric and asymmetric distributions, as represented by Gaussian and Schulz distributions, respectively, to data for extruded vesicles and find that the Schulz distribution provides a better estimate of the size distribution for these samples.

Journal Article↗
PubMed2005

Preparation of samples for comparative studies of arthropod chromosomes: visualization, in situ hybridization, and genome size estimation.

The ability to obtain large amounts of genomic sequence for organisms and high throughput technology has led to a change in the thrust of research at the level of chromosomes in animals. In the past chromosomal analysis of animals was focused on gross changes such as inversions, translocations, and deletions for both genetic and evolutionary studies. The advent of in situ hybridization technology and the ability to measure genome content size changed both the precision and the scale of studies addressing chromosomal change as a tool in evolutionary biology. This chapter addresses two of the major areas of change that have occurred in chromosomal studies in the past decade -- examination of more refined and genome enabled structural changes in chromosomes and genome size measure. This chapter describes some of the chromosome structure approaches such as fluorescent in situ hybridization (FISH), comparative genomic hybridization (CGH) and other techniques. As well, advances in Genome size measurement and theory are described herein.

Animals↗
PubMed2003

Genetic diversity and molecular markers of the tropical abalone (Haliotis asinina) in Thailand.

Genetic diversity of abalone in Thailand, Haliotis asinina, H. ovina, and H. varia, was analyzed by polymerase chain reaction (PCR) of 18S and 16S rDNAs, with randomly amplified polymorphic DNA (RAPD) and restriction fragment length polymorphism (RFLP). Species-specific RAPD markers were found in each abalone species. Restriction analysis of 18S (nuclear) ribosomal DNA with Alu I, Taq I, and Hae III and 16S (mitochondrial) rDNA with Bam HI, Eco RI, Hae III, and Alu I gave 12 and 13 digestion patterns, respectively. A total of 49 composite haplotypes were found. A dendogram obtained by the unweighted pair-group method with arithmetic mean, constructed from divergence between pairs of composite haplotypes, revealed reproductively isolated gene pools of these abalone and indicated that H. asinina and H. ovina are genetically closer than H. varia. When H. varia was discovered owing to small sample sizes, geographic heterogeneity analysis and FST estimate indicated clear genetic differentiation between H. ovina originating from the Andaman Sea (west) and the Gulf of Thailand (east, P<0.0001), whereas partial differentiation was observed between the Philippines and the remaining H. asinina samples (P<0.0021). The amplified 16S rDNAs of individuals representing composite haplotypes found in this study were cloned and sequenced. A neighbor-joining tree constructed from sequence divergence of 16S rDNA accurately allocated those sequences according to species origins of abalone. Species-specific PCR based on 16S rDNA polymorphism was successfully developed in H. asinina and H. varia but not in H. ovina.

Animals↗
PubMed2004

Implementation of fast-Fourier-transform-based simulations of extra-large atmospheric phase and scintillation screens.

Fast-Fourier-transform-based simulations of single-layer atmospheric von Kármán phase screens and Kolmogorov scintillation screens up to hundreds of meters in size were implemented and tested for applications with percent range accuracy. The tests included the expected and the observed structure and pupil variance functions; for the phase, the tests also included the Fried turbulence parameter r0 measured by the seeing and by a simulated differential image motion monitor. The standard compensations used to correct the undersampling at low spatial frequencies were improved, and those needed for the high spatial frequencies were determined analytically. The limiting ratios of the screen sampling step to r0 and of the screen size to the pupil aperture were estimated by means of the simulated data. Sample results are shown that demonstrate the performances of the simulations for single-layer Kolmogorov and von Kármán phase screens up to 200 m in size and for Kolmogorov scintillation screens for pupils up to 50 m of aperture.

Journal Article↗
PubMed1996

On planning of samples for linkage analysis: two ways of a sample size reduction.

The sample size required for a given type I and type II errors of linkage decision is determined by using the earlier proposed method of the linkage test power estimation [Ginsburg et al., 1996]. Dependence of the sample size on the heterozygotic genotype penetrance is investigated. Two approaches to sample size reduction are considered: the choice of marker gene and the special extension of analyzed pedigree structures. Their effects are quantitatively evaluated in some illustrative situations. It is shown that a practical reduction in sample size can be achieved only when the added part of a pedigree has a special set of phenotypic characteristics in its members.

Genetic Linkage↗
PubMedDate not supplied

Statistical methods for estimating attributable risk from retrospective data.

This paper extends Levin's measure of attributable risk to adjust for confounding by aetiologic factors other than the exposure of interest. One can estimate this extended measure from case-control data provided either (i) from the control data one can estimate exposure prevalence within each stratum of the confounding factor; or (ii) one has additional information available concerning the confounder distribution and the stratum-specific disease rates. In both cases we give maximum likelihood estimates and their estimated asymptotic variances, and show them to be independent of the sampling design (matched vs. random). Computer simulations investigate the behaviour of these estimates and of three types of confidence intervals when sample size is small relative to the number of confounder strata. The simulations indicate that attributable risk estimates tend to be too low. The bias is not serious except when exposure prevalence is high among controls. In this case the estimates and their standard error estimates are also highly unstable. In general, the asymptotic standard error estimates performed quite well, even in small samples, and even when the true asymptotic standard error was too small. By contrast, the bootstrap estimate tended to be too large. None of the three confidence intervals proved superior in accuracy to the other two. Thus there appears no advantage in using the log-based interval suggested by Walter which is always longer than the simpler symmetric interval.

Adult↗
PubMed2001

A comparison of methods for adaptive sample size adjustment.

In fixed sample size designs, precise knowledge about the magnitude of the outcome variable's variance in the planning phase of a clinical trial is mandatory for an adequate sample size determination. Wittes and Brittain introduced the internal pilot study design that allows recalculation of the sample size during an ongoing trial using the estimated variance obtained from an interim analysis. However, this procedure requires the unblinding of the treatment code. Since unblinding of an ongoing trial should be avoided whenever possible, there should be some benefit of this design compared with blinded sample size recalculation procedures to justify the unveiling of the treatment code. In this paper, we compare several sample size recalculation procedures with and without unblinding. The simulation results indicate that the procedures behave similarly. In particular, breaking of the blind is not required for an efficient sample size adjustment. We also compare these pure sample size adaptation procedures with study designs which additionally allow for early stopping. Evaluation of the cumulative distribution function of the resulting sample sizes shows that the option for early stopping may lead to lower expectation but generally to a higher variability. The procedures are illustrated by an example of a trial in the treatment of depression.

Computer Simulation↗
PubMed2005

Bias-corrected maximum likelihood estimator of the intraclass correlation parameter for binary data.

A popular model to analyse over/under-dispersed proportions is to assume the extended beta-binomial model with dispersion (intraclass correlation) parameter phi and then to estimate this parameter by maximum likelihood. However, it is well known that maximum likelihood estimate (MLE) may be biased when the sample size n or the total Fisher information is small. In this paper we obtain a bias-corrected maximum likelihood (BCML) estimator of the intraclass correlation parameter and compare it, by simulation, in terms of bias and efficiency, with the MLE, an estimator Q(2) based on optimal quadratic estimating equations of Crowder and recommended by Paul et al. and a double extended quasi-likelihood (DEQL) estimator proposed by Lee. The BCML estimator has superior bias and efficiency properties in most instances. Analyses of a set of toxicological data from Paul and a set of medical data pertaining to chromosomal abnormalities among survivors of the atomic bomb in Hiroshima from Otake and Prentice show, in general, much improvement in standard errors of the BCML estimates over the other three estimates.

Animals↗
PubMed2005

A variance estimator for constrained estimates of change in relative categorical frequencies.

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.

Analysis of Variance↗
PubMed2001

Sample size requirement for detecting interference under the chi-square model.

The chi-square model (CHS) of recombination has been studied extensively, in recent years, for its ability of capturing the process and estimating the level of crossover interference. Exploration thus far shows that this model yields much better fits to human genetic data than Haldane's no-interference model, and the explicit level of interference can be easily estimated as well. This paper provides calculations of sample sizes required to detect interference under CHS for a variety of settings. Two data types, fully informative meioses and phase-unknown backcross families, are studied. Under each setting, we calculate the number of meioses/families needed to ensure that the expected log-likelihood difference between the chi(2) interference model and Haldane's no-interference model exceeds a prespecified threshold. It is found that joint consideration of multiple (more than three) markers dramatically reduces the number of meioses/families needed when compared to an analysis based on three-point data, a traditional setting for detecting interference using three-point tests. The results indicate that the numbers of meioses needed to detect interference under CHS are well within the reach of most genetic mapping studies.

Chi-Square Distribution↗
PubMed2002

Statistical inference for a linear function of medians: confidence intervals, hypothesis testing, and sample size requirements.

When the distribution of the response variable is skewed, the population median may be a more meaningful measure of centrality than the population mean, and when the population distribution of the response variable has heavy tails, the sample median may be a more efficient estimator of centrality than the sample mean. The authors propose a confidence interval for a general linear function of population medians. Linear functions have many important special cases including pairwise comparisons, main effects, interaction effects, simple main effects, curvature, and slope. The confidence interval can be used to test 2-sided directional hypotheses and finite interval hypotheses. Sample size formulas are given for both interval estimation and hypothesis testing problems.

Humans↗
PubMed1999

Estimating Confidence Intervals and Sampling Proportions in Two-Stage Prevalence Designs.

In response to Abbott and Volberg's (in press) rejoinder to my epidemiologic note on verification bias and estimation of prevalence rates (Gambino, in press), I provide the formulas for computing confidence intervals for the results of second-stage verification. In addition, I provide the appropriate equation for determining confidence intervals when prevalence is near zero or one. Finally, we present formulas for determining the most efficient sample sizes needed to minimize second-stage variance estimates. These allow the investigator working under a fixed budget to determine the relative value of sampling negative screens to test for false negatives. We close with an observation on the interpretability of evidence.

Journal Article↗