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PubMed2026

dGAMLSS: an exact, distributed algorithm to fit Generalized Additive Models for Location, Scale, and Shape for privacy-preserving population reference charts.

MOTIVATION: There is growing interest in estimating population reference ranges across age and sex to better identify atypical clinically-relevant measurements throughout the lifespan. For this task, the World Health Organization recommends using Generalized Additive Models for Location, Scale, and Shape (GAMLSS), which can model non-linear growth trajectories under complex distributions that address the heterogeneity in human populations.Fitting GAMLSS models requires large, generalizable sample sizes, especially for accurate estimation of extreme quantiles, but obtaining such multi-site data can be challenging due to privacy concerns and practical considerations. In settings where patient data cannot be shared, privacy-preserving distributed algorithms for federated learning can be used, but no such algorithm exists for GAMLSS. RESULTS: We propose distributed GAMLSS (dGAMLSS), a distributed algorithm that can fit GAMLSS models across multiple sites without sharing patient-level data. This includes specific considerations for the fitting of smooth functions at varying levels of communication efficiency. We demonstrate the effectiveness of dGAMLSS in constructing population reference charts across clinical, genomics, and neuroimaging settings and show that dGAMLSS is able to reproduce pooled reference charts and inference down to numerical differences. AVAILABILITY AND IMPLEMENTATION: An R package providing examples of the dGAMLSS algorithm, as well as functions for sharing and aggregating site-specific parameters, is available at https://github.com/hufengling/dGAMLSS.

Algorithms↗
PubMed2000

Sample size calculations for cluster randomised trials. Changing Professional Practice in Europe Group (EU BIOMED II Concerted Action).

OBJECTIVES: Cluster randomised trials, in which groups of individuals are randomised, are increasingly being used in the health field. Adopting a clustered approach has implications for the design of such trials, and sample size calculations need to be inflated to accommodate for the clustering effect. Reliable estimates of intracluster correlation coefficients (ICCs) are required for robust sample size calculations to be made; however, little empirical evidence is available on their likely size, and on factors which influence their magnitude. The aim of this study was to generate empirical estimates of ICCs and to explore factors which may affect their magnitude. METHODS: Empirical estimates of ICCs were calculated for both process variables and patient outcomes from a number of datasets of primary and secondary care implementation studies. RESULTS: Estimates of ICCs varied according to setting and type of outcome. Estimates of ICCs for process variables were higher than those for patient outcomes, and estimates derived from secondary care were higher than those from primary care. ICCs for process variables in primary care were of the order of 0.05-0.15, whilst those in secondary care were of the order of 0.3. Estimates for patient outcomes in primary care were generally lower than 0.05. CONCLUSIONS: Adopting cluster randomisation has implications for the design, size and analysis of clinical trials. This study gives an insight into the potential size of ICCs in primary and secondary care, and provides a practical guide to researchers to aid the planning of future studies in this area.

Cluster Analysis↗
PubMed1997

Determination of mean particle volume, a Monte Carlo simulation.

Either length measurements or area measurements may be made on a sample of profiles for the purpose of estimating the mean volume of a population of convex particles. Diameters of spheres, caliper diameters of ellipsoids and intercept lengths are available length measurements. Profile areas can be evaluated by planimetry or point counting. Either all the available profiles in random sections or point sampled profiles can be utilized. We have applied a Monte Carlo simulation to compare several of the stereologic methods for the estimation of the mean volumes of spheres and ellipsoids. Populations of spherical, prolate ellipsoidal and oblate ellipsoidal particles were subjected to random sectioning and measurement. Diameter, point sampled intercept length, area and point sampled area were measured in the case of the spherical particles. With the ellipsoids, the same measurement excepting diameters were performed. The measurements were converted to volumes by the appropriate equations, and the means, the standard deviations of the means and the 95% confidence intervals were determined for increasing sample sizes. All the methods provide estimates that converge on their theoretical mean volumes. The area measurements and particularly the point sampled area measurement show some advantage over the length measurements, but differences among the methods are small, not entirely consistent over the different cases and unlikely to be significant in most real applications.

Algorithms↗
PubMed2002

Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs.

When a meta-analysis on results from experimental studies is conducted, differences in the study design must be taken into consideration. A method for combining results across independent-groups and repeated measures designs is described, and the conditions under which such an analysis is appropriate are discussed. Combining results across designs requires that (a) all effect sizes be transformed into a common metric, (b) effect sizes from each design estimate the same treatment effect, and (c) meta-analysis procedures use design-specific estimates of sampling variance to reflect the precision of the effect size estimates.

Humans↗
PubMed1996

Rater reliability of fragile X mutation size estimates: a multilaboratory analysis.

Notwithstanding the use of comparable molecular protocols, description and measurement of the fra(X) (fragile X) mutation may vary according to its appearance as a discrete band, smear, multiple bands, or mosaic. Estimation of mutation size may also differ from one laboratory to another. We report on the description of an mutation size estimate for a large sample of individuals tested for the fra(X) pre- or full mutation. Of 63 DNA samples evaluated, 45 were identified previously as fra(X) pre- or full mutations. DNA from 18 unaffected individuals was used as control. Genomic DNA was extracted from peripheral blood, and DNA fragments from each of four laboratories were sent to a single center where Southern blots were prepared and hybridized with the pE5.1 probe. Photographs from autoradiographs were returned to each site, and raters blind to the identity of the specimens were asked to evaluate them. Raters' estimates of mutation size compared favorably with a reference test. Intrarater reliability was good to excellent. Variability in mutation size estimates was comparable across band types. Variability in estimates was moderate, and was significantly correlated with absolute mutation size and band type.

Adolescent↗
PubMed2005

Comparison of three methods to estimate genetic ancestry and control for stratification in genetic association studies among admixed populations.

Population stratification may confound the results of genetic association studies among unrelated individuals from admixed populations. Several methods have been proposed to estimate the ancestral information in admixed populations and used to adjust the population stratification in genetic association tests. We evaluate the performances of three different methods: maximum likelihood estimation, ADMIXMAP and Structure through various simulated data sets and real data from Latino subjects participating in a genetic study of asthma. All three methods provide similar information on the accuracy of ancestral estimates and control type I error rate at an approximately similar rate. The most important factor in determining accuracy of the ancestry estimate and in minimizing type I error rate is the number of markers used to estimate ancestry. We demonstrate that approximately 100 ancestry informative markers (AIMs) are required to obtain estimates of ancestry that correlate with correlation coefficients more than 0.9 with the true individual ancestral proportions. In addition, after accounting for the ancestry information in association tests, the excess of type I error rate is controlled at the 5% level when 100 markers are used to estimate ancestry. However, since the effect of admixture on the type I error rate worsens with sample size, the accuracy of ancestry estimates also needs to increase to make the appropriate correction. Using data from the Latino subjects, we also apply these methods to an association study between body mass index and 44 AIMs. These simulations are meant to provide some practical guidelines for investigators conducting association studies in admixed populations.

Asthma↗
PubMed1999

Who is at risk of what?

If you have calculated the sample size required for an employee survey or an observational study of departmental practices but found that the number of observations required is larger than the number of employees, chances are the error is due to use of approximation formulae. Many of us unknowingly were taught to use approximations that fail to include the finite population correction factor. Depending on the objective of a study and the proportion of a population sampled, it may be necessary to consider this correction factor in order to estimate standard error and sample size accurately.

Cross Infection↗
PubMed2006

An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors.

BACKGROUND: The analysis of large-scale gene expression data is a fundamental approach to functional genomics and the identification of potential drug targets. Results derived from such studies cannot be trusted unless they are adequately designed and reported. The purpose of this study is to assess current practices on the reporting of experimental design and statistical analyses in gene expression-based studies. METHODS: We reviewed hundreds of MEDLINE-indexed papers involving gene expression data analysis, which were published between 2003 and 2005. These papers were examined on the basis of their reporting of several factors, such as sample size, statistical power and software availability. RESULTS: Among the examined papers, we concentrated on 293 papers consisting of applications and new methodologies. These papers did not report approaches to sample size and statistical power estimation. Explicit statements on data transformation and descriptions of the normalisation techniques applied prior to data analyses (e.g. classification) were not reported in 57 (37.5%) and 104 (68.4%) of the methodology papers respectively. With regard to papers presenting biomedical-relevant applications, 41(29.1 %) of these papers did not report on data normalisation and 83 (58.9%) did not describe the normalisation technique applied. Clustering-based analysis, the t-test and ANOVA represent the most widely applied techniques in microarray data analysis. But remarkably, only 5 (3.5%) of the application papers included statements or references to assumption about variance homogeneity for the application of the t-test and ANOVA. There is still a need to promote the reporting of software packages applied or their availability. CONCLUSION: Recently-published gene expression data analysis studies may lack key information required for properly assessing their design quality and potential impact. There is a need for more rigorous reporting of important experimental factors such as statistical power and sample size, as well as the correct description and justification of statistical methods applied. This paper highlights the importance of defining a minimum set of information required for reporting on statistical design and analysis of expression data. By improving practices of statistical analysis reporting, the scientific community can facilitate quality assurance and peer-review processes, as well as the reproducibility of results.

Analysis of Variance↗
PubMed2001

Morphometric testing of structural hypotheses of the supraorbital region in modern humans.

Our understanding of the functional morphology of the primate supraorbital region is based largely on previous morphometric and in vivo mechanical tests of hypotheses in non-human anthropoids. Prior tests of two structural hypotheses explaining morphological variation in the supraorbital region, the craniofacial size hypothesis and the spatial hypothesis, did not fully consider modern humans. We extend these previous findings to include modern humans by conducting morphometric tests of these two hypotheses in a sample of adult Melanesian crania. Morphometric correlates of structural predictions for the craniofacial size and spatial hypotheses were developed and compared to measurements of the supraorbital region via bivariate product-moment correlations. Measurements of the supraorbital region are significantly correlated with a craniofacial size estimate across individuals from this Melanesian sample. This result supports the prediction of the craniofacial size hypothesis that the magnitude of the supraorbital region is proportional to craniofacial size. The predicted link between the degree of neural-orbital disjunction and the magnitude of the supraorbital region, explicated in the spatial hypothesis, receives mixed support in the correlation analysis. These two results agree with previous research indicating that support for the craniofacial size and spatial hypotheses can be found across and within anthropoid primate species, including modern humans. Correlational support for both the craniofacial size and spatial hypotheses suggests multiple factors influence variation in the modern human supraorbital region. Thus, a single hypothesis cannot fully account for modern human variation in this region. The low bivariate correlation coefficients in this study further question whether existing hypotheses can adequately explain morphological variation in the supraorbital region in a primate population sample. Novel functional, structural, behavioral and developmental ideas must be explored if we are to better understand morphological variation in the modern human supraorbital region.

Anthropology, Physical↗
PubMed1994

Computing sample size for receiver operating characteristic studies.

RATIONALE AND OBJECTIVES: Hanley and McNeil (1982) proposed a nonparametric method for computing the standard error of the area under the receiver operating characteristic (ROC) curve. The method has been important in planning the minimum sample size for ROC studies. However, the validity of this method for rating data with various standard deviation ratios has not been investigated. METHODS: A simulation study was conducted to compare the empirical standard error of the area under the curve with Hanley and McNeil's estimate over a range of parameters. An alternative method of computing the standard error based on a binormal distribution is proposed. RESULTS: The method of Hanley and McNeil can lead to underestimation of the minimum sample size. The proposed method provides more appropriate estimates of sample size. CONCLUSIONS: When determining sample size for a study of the area under the ROC curve where rating data are used, the standard error estimator based on the binormal distribution should be used.

Mathematics↗
PubMed1999

Estimating genetic correlations in natural populations.

Information on the genetic correlation between traits provides fundamental insight into the constraints on the evolutionary process. Estimates of such correlations are conventionally obtained by raising individuals of known relatedness in artificial environments. However, many species are not readily amenable to controlled breeding programmes, and considerable uncertainty exists over the extent to which estimates derived under benign laboratory conditions reflect the properties of populations in natural settings. Here, non-invasive methods that allow the estimation of genetic correlations from phenotypic measurements derived from individuals of unknown relatedness are introduced. Like the conventional approach, these methods demand large sample sizes in order to yield reasonably precise estimates, and special precautions need to be taken to eliminate bias from shared environmental effects. Provided the sample consists of at least 20% or so relatives, informative estimates of the genetic correlation are obtainable with sample sizes of several hundred individuals, particularly if supplemental information on relatedness is available from polymorphic molecular markers.

Animals↗
PubMed1996

Intraclass correlation estimates in a school-based smoking prevention study. Outcome and mediating variables, by sex and ethnicity.

Most school-based smoking prevention studies employ designs in which schools or classrooms are assigned to different treatment conditions while observations are made on individual students. This design requires that the treatment effect be assessed against the between-school variance. However, the between-school variance is usually larger than the variance that would be obtained if students were individually randomized to different conditions. Consequently, the power of the test for a treatment effect is reduced, and it becomes difficult to detect important treatment effects. To assess the potential loss of power or to calculate appropriate sample sizes, investigators need good estimates of the intraclass correlations for the variables of interest. The authors calculated intraclass correlations for some common outcome variables in a school-based smoking prevention study, using a three-level model-i.e., students nested within classrooms and classrooms nested within schools. The authors present the intraclass correlation estimates for the entire data set, as well as separately by sex and ethnicity. They also illustrate the use of these estimates in the planning of future studies.

Adolescent↗
PubMed1993

Estimation of the incidence of a rare genetic disease through a two-tier mutation survey.

Recent attempts to detect mutations involving single base changes or small deletions that are specific to genetic diseases provide an opportunity to develop a two-tier mutation-screening program through which incidence of rare genetic disorders and gene carriers may be precisely estimated. A two-tier survey consists of mutation screening in a sample of patients with specific genetic disorders and in a second sample of newborns from the same population in which mutation frequency is evaluated. We provide the statistical basis for evaluating the incidence of affected and gene carriers in such two-tier mutation-screening surveys, from which the precision of the estimates is derived. Sample-size requirements of such two-tier mutation-screening surveys are evaluated. Considering examples of cystic fibrosis (CF) and medium-chain acyl-CoA dehydrogenase deficiency (MCAD), the two most frequent autosomal recessive disease in Caucasian populations and the two most frequent mutations (delta F508 and G985) that occur on these disease allele-bearing chromosomes, we show that, with 50-100 patients and a 20-fold larger sample of newborns screened for these mutations, the incidence of such diseases and their gene carriers in a population may be quite reliably estimated. The theory developed here is also applicable to rare autosomal dominant diseases for which disease-specific mutations are found.

Acyl-CoA Dehydrogenase↗
PubMed2003

A random variance model for detection of differential gene expression in small microarray experiments.

MOTIVATION: Microarray techniques provide a valuable way of characterizing the molecular nature of disease. Unfortunately expense and limited specimen availability often lead to studies with small sample sizes. This makes accurate estimation of variability difficult, since variance estimates made on a gene by gene basis will have few degrees of freedom, and the assumption that all genes share equal variance is unlikely to be true. RESULTS: We propose a model by which the within gene variances are drawn from an inverse gamma distribution, whose parameters are estimated across all genes. This results in a test statistic that is a minor variation of those used in standard linear models. We demonstrate that the model assumptions are valid on experimental data, and that the model has more power than standard tests to pick up large changes in expression, while not increasing the rate of false positives. AVAILABILITY: This method is incorporated into BRB-ArrayTools version 3.0 (http://linus.nci.nih.gov/BRB-ArrayTools.html). SUPPLEMENTARY MATERIAL: ftp://linus.nci.nih.gov/pub/techreport/RVM_supplement.pdf

Algorithms↗
PubMed2005

The effect of vaginal pH on labor induction with vaginal misoprostol.

OBJECTIVE: To estimate the association of vaginal pH on the induction to vaginal delivery interval in labor induction with vaginal misoprostol. METHODS: Women presenting at term with intact membranes for labor induction were recruited. The pH of the vagina was measured during a digital examination of the cervix to determine the Bishop Score. Labor was induced with 25 microg of vaginal misoprostol placed every 6 h until spontaneous rupture of membranes or active labor occurred. The primary outcome was the induction to vaginal delivery interval in the lower pH (< 5) versus higher pH (> or = 5) group. Secondary outcomes assessed maternal and neonatal morbidities. Sample size calculated a priori estimated 120 subjects were required for a power of 95% and a 2-tailed a of 0.05. RESULTS: 120 women met inclusion criteria and had available pH data. There was no difference in the induction to vaginal delivery interval in the lower pH (1455 min) versus higher pH group (1295 minutes, Mean difference 160 [- 147,468] P = .30). No difference was observed for operative delivery rates or neonatal outcomes. CONCLUSION: The pH of the vagina may not affect the length of the induction to vaginal delivery interval in women undergoing labor induction with vaginal misoprostol. Further research is required to determine factors that may influence the efficacy of vaginal misoprostol when used for labor induction.

Administration, Intravaginal↗
PubMedDate not supplied

Sampling hazelnuts for aflatoxin: uncertainty associated with sampling, sample preparation, and analysis.

The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a high-performance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.

Aflatoxins↗
PubMedDate not supplied

Exposure to toxic air contaminants in environmental tobacco smoke: an assessment for California based on personal monitoring data.

The contribution of environmental tobacco smoke (ETS) to the exposure of adult nonsmoking Californians was determined for selected toxic air contaminants (TACs). The assessment was based on published measurements of ETS emission factors and personal exposures to volatile organic compounds. The human exposure studies were conducted in three California areas--Los Angeles, Pittsburgh/Antioch, and Woodland--between 1984 and 1990. We derived unexposed and passive population exposure distributions by randomly sampling the monitoring results for individuals classified according to exposure status (active smoker, passively exposed or unexposed to ETS during monitoring). The differences between the unexposed and passive distributions were used to estimate the ETS-only contribution for exposure to benzene, styrene, o-xylene, and m,p-xylene. Emission factors were then employed to infer the ETS-caused exposure to thirteen other compounds. The estimated arithmetic mean increments of 24-hour exposure attributable to ETS for the nonsmoking Californian population (age > or = 7) exposed to ETS are as follows (results in units of microgram m-3 exposure concentration; results using two different emission factors presented as a range): acetaldehyde 11-15; acetonitrile 7.0; acrylonitrile 0.49; benzene 1.02; 1,3-butadiene 0.75-2.3; 2-butanone 1.4; o-cresol 0.17; m,p-cresol 0.41; ethyl acrylate < 0.015; ethylbenzene 0.49-0.64; formaldehyde 6.5-8.2; n-nitrosodimethylamine 0.0028; phenol 1.4; styrene 0.36; toluene 3.1-3.2; o-xylene 0.77; m,p-xylene 0.99. The 90% confidence limits on these estimates due to the limited sample size in the studies are roughly x/ divided by 6. For four widely studied compounds, ETS is estimated to contribute the following percentages to the total inhalation exposure of all nonsmoking Californians: o-xylene 5%; m,p-xylene 3%; benzene 5%; and styrene 8%.

Adolescent↗
PubMed1995

Parameter estimation of labial movements in speech production: implications for speech motor control.

Central to theories of speech motor control are estimates on magnitudes of lip activity expressed in terms of central tendency, variability, and interrelatedness. In fact, the tenability of each of two competing theories of motor control for speech production rests solely on the observation of the predicted direction of the correlation coefficient (one positive and one negative) that indexes the relationship of concurrent lip activity. Each theory, however, predicts a relationship that is the complete opposite of the relationship predicted by the other. That is, one theory proposes that the labial system functions on the basis of complementary variation, whereas the other assumes positive covariation, or complementary modulation. In apparent contradiction, each prediction has been observed under laboratory conditions. The explanation for this apparent contradiction resides in the small sample sizes upon which each estimate was based. The minimum number of observations that are necessary to achieve accurate estimates of lip displacement parameters has remained unclear. This paper addresses three fundamental questions: (a) how many observations of on-task behavior are necessary to accurately estimate mean and variance values for the magnitude of upper lip displacement in a speech production experiment?, (b) what is the analogous number of observations for estimating the same values of lower lip displacement (together with the mandible) in the same context?, and (c) how many observations are necessary to accurately estimate the correlation coefficient indexing the relationship of lip displacements during the production of speech? Answers to these questions are accomplished through a review of estimator properties, a Monte Carlo computer simulation, and through laboratory observations.(ABSTRACT TRUNCATED AT 250 WORDS)

Humans↗