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PubMed2003

Statistical properties of affected sib-pair linkage tests.

Genetic linkage analysis is a powerful tool for the identification of disease susceptibility loci. Among the most commonly applied genetic linkage strategies are affected sib-pair tests, but the statistical properties of these tests have not been well characterized. Here, we present a study of the distribution of affected sib-pair tests comparing the type I error rate and the power of the mean test and the proportion test, which are the most commonly used, along with a novel exact test. In contrast to existing literature, our findings showed that the mean and proportion tests have inflated type I error rates, especially when used with small samples. We developed and applied corrections to the tests which provide an excellent adjustment to the type I error rate for both small and large samples. We also developed a novel approach to identify the areas of higher power for the mean test versus the proportion test, providing a wider and simpler comparison with fewer assumptions about parameter values than existing approaches require.

Alleles↗
PubMed2005

Biological master games: using biologists' reasoning to guide algorithm development for integrated functional genomics.

We review some powerful new algorithms that build on the intuitive biological interpretation techniques for statistical analysis of functional genomics experiments. Although they were originally designed for transcriptomics, we argue that these algorithms are applicable to any type of -omics study (transcriptomics, proteomics, metabolomics). Rank Products (RP), a strictly non-parametric test statistic to detect differentially regulated elements (genes, proteins, metabolites) in genome-wide screens. RP is particularly powerful for noisy data and low numbers of replicates and makes full use of the availability of a large number of parallel measurements that is typical of modern large-scale experiments. Iterative Group Analysis (iGA), a statistical method that makes the transition from regulated single elements to significant classes of elements, and thus provides an automatic functional annotation of an experiment. Graph-based iGA (GiGA), an extension of iGA that combines experimental data with a broad variety of biological annotations to highlight physiologically relevant regions in a given "evidence graph" (e.g., metabolic networks, signaling pathway diagrams, protein interaction maps). The sequential application of these techniques yields an increasingly abstract interpretation of experimental data that is at the same time quantitative, statistically rigorous, and biologically significant. The results can be used either as helpful tools to guide data visualization and exploration, or as the input for downstream computational applications in a systems biology framework.

Algorithms↗
PubMed1989

A knowledge-based system for data analysis and interpretation.

Traditionally, statistical packages are employed to derive or infer facts about a Universe of Discourse through data analysis and interpretation. It is analysis that serves to transform data into information. Statistical packages provide the users with relatively easy-to-use and powerful mechanics of data analysis, but up to now they do not provide much help with the design and strategies of the analysis. As such, there is a risk of misuse of these packages by statistically inexperienced users. We propose the use of knowledge-based interfaces to support this category of users in statistical evaluations. This paper discusses our experiences from the implementation of a knowledge-based system called MAXITAB. It provides guidance in the processes of data analysis and interpretation and has been programmed as an interface to the statistical package MINITAB.

Data Interpretation, Statistical↗
PubMed1991

Enamel surface roughness and dental pulp response to coaxial carbon dioxide-neodymium: YAG laser irradiation.

The purpose of this study was to evaluate the effect of a coaxial carbon dioxide/neodymium:yttrium aluminium garnet laser beam on enamel surface roughness and the dental pulps of mongrel dogs. In four dogs, four maxillary left posterior teeth were irradiated at 16 cm source-tooth distances. Two teeth were irradiated with 16 W CO2/16 W Nd:YAG and the remaining two with 16 W CO2/40 W Nd:YAG. Two maxillary right teeth were untreated controls. In addition, mandibular premolars were irradiated at the same distance and power levels, extracted, and analysed for surface roughness. Significant differences in surface roughness were found between control samples and either power level, but not between enamel surfaces at the two power levels. Maxillary teeth were removed at 10 days postoperatively, sectioned and stained (H & E). The reaction of pulpal cells to irradiation was scored. Data analysis revealed statistically significant differences between the control and lower power Nd:YAG groups and between the control and higher power Nd:YAG groups. The difference in pulpal response between both laser groups approached significance.

Aluminum Silicates↗
PubMed2004

Adjusting for covariates in variance components QTL linkage analysis.

Variance components modeling has emerged as a powerful method for quantitative trait loci (QTL) linkage analysis. However, the power to detect a gene of minor effect is low. Many complex traits are affected by environmental as well as genetic factors, and one strategy to increase power is to reduce nongenetic phenotypic variance by adjusting for environmental covariates. In this paper, we investigate the power of three approaches to covariate adjustment in variance components linkage analysis: (i) incorporate covariates in the means model, (ii) incorporate covariates in the covariance matrix, and (iii) perform analysis on residual statistics. These approaches are compared to an analysis without adjustment. The results show that in the absence of correlation between the covariate and the QTL effect, adjusting for covariates indeed increases power to detect an underlying QTL. As this correlation increases, however, the power decreases. In the presence of a causal association between QTL and covariates, not adjusting for covariates appeared to be more powerful. The three approaches for adjusting for covariate: residual statistics, the means model, and the covariance model, had equal power to detect a QTL.

Analysis of Variance↗
PubMed2000

Subgroup analysis and other (mis)uses of baseline data in clinical trials.

BACKGROUND: Baseline data collected on each patient at randomisation in controlled clinical trials can be used to describe the population of patients, to assess comparability of treatment groups, to achieve balanced randomisation, to adjust treatment comparisons for prognostic factors, and to undertake subgroup analyses. We assessed the extent and quality of such practices in major clinical trial reports. METHODS: A sample of 50 consecutive clinical-trial reports was obtained from four major medical journals during July to September, 1997. We tabulated the detailed information on uses of baseline data by use of a standard form. FINDINGS: Most trials presented baseline comparability in a table. These tables were often unduly large, and about half the trials inappropriately used significance tests for baseline comparison. Methods of randomisation, including possible stratification, were often poorly described. There was little consistency over whether to use covariate adjustment and the criteria for selecting baseline factors for which to adjust were often unclear. Most trials emphasised the simple unadjusted results and covariate adjustment usually made negligible difference. Two-thirds of the reports presented subgroup findings, but mostly without appropriate statistical tests for interaction. Many reports put too much emphasis on subgroup analyses that commonly lacked statistical power. INTERPRETATION: Clinical trials need a predefined statistical analysis plan for uses of baseline data, especially covariate-adjusted analyses and subgroup analyses. Investigators and journals need to adopt improved standards of statistical reporting, and exercise caution when drawing conclusions from subgroup findings.

Bias↗
PubMed2002

On the properties of stochastic intermittency in rainfall processes.

In this work we propose a mixed approach to deal with the modelling of rainfall events, based on the analysis of geometrical and statistical properties of rain intermittency in time, combined with the predictability power derived from the analysis of no-rain periods distribution and from the binary decomposition of the rain signal. Some recent hypotheses on the nature of rain intermittency are reviewed too. In particular, the internal intermittent structure of a high resolution pluviometric time series covering one decade and recorded at the tipping bucket station of the University of Genova is analysed, by separating the internal intermittency of rainfall events from the inter-arrival process through a simple geometrical filtering procedure. In this way it is possible to associate no-rain intervals with a probability distribution both in virtue of their position within the event and their percentage. From this analysis, an invariant probability distribution for the no-rain periods within the events is obtained at different aggregation levels and its satisfactory agreement with a typical extreme value distribution is shown.

Environmental Monitoring↗
PubMed2006

Inferential, robust non-negative matrix factorization analysis of microarray data.

MOTIVATION: Modern methods such as microarrays, proteomics and metabolomics often produce datasets where there are many more predictor variables than observations. Research in these areas is often exploratory; even so, there is interest in statistical methods that accurately point to effects that are likely to replicate. Correlations among predictors are used to improve the statistical analysis. We exploit two ideas: non-negative matrix factorization methods that create ordered sets of predictors; and statistical testing within ordered sets which is done sequentially, removing the need for correction for multiple testing within the set. RESULTS: Simulations and theory point to increased statistical power. Computational algorithms are described in detail. The analysis and biological interpretation of a real dataset are given. In addition to the increased power, the benefit of our method is that the organized gene lists are likely to lead better understanding of the biology. AVAILABILITY: An SAS JMP executable script is available from http://www.niss.org/irMF

Algorithms↗
PubMed2006

Comparison of methods incorporating quantitative covariates into affected sib pair linkage analysis.

For complex traits, it may be possible to increase the power to detect linkage if one takes advantage of covariate information. Several statistics have been proposed that incorporate quantitative covariate information into affected sib pair (ASP) linkage analysis. However, it is not clear how these statistics perform under different gene-environment (G x E) interactions. We compare representative statistics to each other on simulated data under three biologically-plausible G x E models. We also compared their performance with a model-free method and with quantitative trait locus (QTL) linkage approaches. The statistics considered here are: (1) mixture model; (2) general conditional-logistic model (LODPAL); (3) multinomial logistic regression models (MLRM); (4) extension of the maximum-likelihood-binomial approach (MLB); (5) ordered-subset analysis (OSA); and (6) logistic regression modeling (COVLINK). In all three G x E models, most of these six statistics perform better when using the covariate C1 associated with a G x E interaction effect than when using the environmental risk factor C2 or the random noise covariate C3. Compared with a model-free method without covariates (S(all)), the mixture model performs the best when using C1, with the high-to-low OSA method also performing quite well. Generally, MLB is the least sensitive to covariate choice. However, most of these statistics do not provide better power than S(all). Thus, while inclusion of the "correct" covariate can lead to increased power, careful selection of appropriate covariates is vital for success.

Analysis of Variance↗
PubMed1990

How to use continuous quality improvement theory and statistical quality control tools in a multispecialty clinic.

The management philosophy of continuous quality improvement (CQI) and the tools of statistical quality control (SQC) have the potential for advancing quality management in medicine as they have in industry. The authors report their favorable experience with the approach and explain how to adapt CQI principles and SQC charts and graphs, citing examples from their participation in a quality improvement effort in a multispecialty clinic serving a large hospital. The coupling of statistical techniques with modern approaches to outcome analysis may provide powerful tools not only for quality assurance and assessment but also for technology evaluation and resource allocation.

Data Collection↗
PubMed2004

The Baumgartner-Weiss-Schindler test for the detection of differentially expressed genes in replicated microarray experiments.

MOTIVATION: An important application of microarray experiments is to identify differentially expressed genes. Because microarray data are often not distributed according to a normal distribution nonparametric methods were suggested for their statistical analysis. Here, the Baumgartner-Weiss-Schindler test, a novel and powerful test based on ranks, is investigated and compared with the parametric t-test as well as with two other nonparametric tests (Wilcoxon rank sum test, Fisher-Pitman permutation test) recently recommended for the analysis of gene expression data. RESULTS: Simulation studies show that an exact permutation test based on the Baumgartner-Weiss-Schindler statistic B is preferable to the other three tests. It is less conservative than the Wilcoxon test and more powerful, in particular in case of asymmetric or heavily tailed distributions. When the underlying distribution is symmetric the differences in power between the tests are relatively small. Thus, the Baumgartner-Weiss-Schindler is recommended for the usual situation that the underlying distribution is a priori unknown. AVAILABILITY: SAS code available on request from the authors.

Algorithms↗
PubMed1997

Y-chromosome effects on Drosophila geotaxis interact with genetic or cytoplasmic background.

Previously, all of the major fruit fly, Drosophila melanogaster, chromosomes (I, II and III) have been shown to be associated with geotaxis, but the Y chromosome has not. Using two methods (back-crossing and chromosome substitution), Y chromosomes from lines that have evolved stable, extreme expressions of geotaxis were placed into different genetic and cytoplasmic backgrounds to test the resulting males for geotaxis. The results of the back-crossing do not support the interpretation of Y-chromosome effects on geotaxis. These tests do not have sufficient statistical power, however, to detect small genetic effects. In the chromosome substitution experiment, the geotaxis-line Y chromosomes were placed into high- and low-selected lines, Canton-S and Champaign wild-type backgrounds. The results of the chromosome substitution experiment provide evidence for a Y-chromosome effect on geotaxis in selected geotaxis lines, but not in wild-type stock, backgrounds. These results suggest that the Y chromosome has a small effect on geotaxis, whose detection depends on genetic and/or cytoplasmic background. The implications of these results are discussed for behaviour genetic analysis of D. melanogaster and for issues of statistical power in detecting small genetic effects.

Animals↗
PubMed2003

Intersection tests for single marker QTL analysis can be more powerful than two marker QTL analysis.

BACKGROUND: It has been reported in the quantitative trait locus (QTL) literature that when testing for QTL location and effect, the statistical power supporting methodologies based on two markers and their estimated genetic map is higher than for the genetic map independent methodologies known as single marker analyses. Close examination of these reports reveals that the two marker approaches are more powerful than single marker analyses only in certain cases. Simulation studies are a commonly used tool to determine the behavior of test statistics under known conditions. We conducted a simulation study to assess the general behavior of an intersection test and a two marker test under a variety of conditions. The study was designed to reveal whether two marker tests are always more powerful than intersection tests, or whether there are cases when an intersection test may outperform the two marker approach.We present a reanalysis of a data set from a QTL study of ovariole number in Drosophila melanogaster. RESULTS: Our simulation study results show that there are situations where the single marker intersection test equals or outperforms the two marker test. The intersection test and the two marker test identify overlapping regions in the reanalysis of the Drosophila melanogaster data. The region identified is consistent with a regression based interval mapping analysis. CONCLUSION: We find that the intersection test is appropriate for analysis of QTL data. This approach has the advantage of simplicity and for certain situations supplies equivalent or more powerful results than a comparable two marker test.

Animals↗
PubMed1995

Influence of power tool-related parameters on the response of finger flexor muscles.

Surface electromyography (EMG) and statistical analysis techniques were applied to investigate the response of finger flexor muscles to hand-transmitted vibration in all the three orthogonal directions. The trends in measured data were examined to derive the influence of variations in the tool-related parameters. Single-factor and multi-factor statistical analyses were performed to establish the significance of influence of different individual and coupled power tool-related parameters. The analysis of variance (ANOVA) results indicated that the vibration direction, acceleration and grip force influence the EMG of finger flexor muscles in a significant manner (P < 0.001), while the effect of vibration frequency was observed to be insignificant (P > 0.9). The electrical activity measured under different vibratory test conditions was observed to be 1.5-6.0 times higher than that measured under the static loads. The increase in electrical activity of the finger flexor muscles with an increase in the grip force was observed to be most significant under static as well as dynamic loading conditions.

Analysis of Variance↗
PubMedDate not supplied

Reproducibility of central venous pressures in supine and lateral positions: a pilot evaluation of the phlebostatic axis in critically ill patients.

OBJECTIVE: To determine if the phlebostatic axis (PA) can be used to obtain reproducible central venous pressures (CVP) in laterally positioned critically ill patients. DESIGN: A quasi-experimental study design was used. The outcome variable was central venous pressure. The explanatory variables were position (supine, 30 degrees right lateral, 30 degrees left lateral) and transducer leveling procedure (supine PA, upper PA, dependent PA). Each subject was used as his or her own control. SETTING: General intensive care unit of a 929 bed metropolitan teaching hospital in New South Wales, Australia. SUBJECTS: A convenience sample of 25 critically ill patients (15 men and 10 women) with an average age of 59.6 years +/- 15.2. METHOD: Each subject's baseline CVP range was collected over a 25-minute period in a supine position. CVP measurements were then obtained in the left and right lateral positions (initial lateral position alternated for each subsequent subject). When the subject was lateral, three CVP readings corresponding to the three transducer leveling procedures were taken. DATA ANALYSIS: One-way repeated measures analysis of variance (one for each leveling procedure) were performed. Clinical significance was deemed evident when the lateral CVP measurement exceeded the baseline range. RESULTS: Statistically significant changes were associated with the upper PA (p < 0.001) and the dependent PA (p < 0.001). Only the supine PA yielded statistically nonsignificant changes in CVP (p = 0.073). However, power analysis indicated that the results were not conclusive (power = 0.520). Clinical significance was determined in 100% and 92% of subjects in the left lateral and right lateral positions, respectively, when using the upper PA whereas the dependent PA yielded clinical significance in all (100%) subjects. Clinical significance was seen in 46% and 42% of subjects for the left lateral and right lateral positions, respectively, when the supine PA was used. CONCLUSION: Of the three leveling procedures, the supine PA yielded the most reproducible CVP measures. However, further studies are required before the supine PA can be recommended as a valid and reliable transducer position for CVP measurement in laterally positioned patients.

Adult↗
PubMed2004

Epidemiologic approaches to identifying environmental causes of birth defects.

Epidemiology can be used to elucidate environmental causes of birth defects. This paper discusses 1) different types of environmental causes; 2) the difficulties in comparing the prevalence of birth defects between populations, including the need for a population base and the implications of prenatal diagnosis; 3) the main study designs for observational epidemiological studies and the various sources of bias; 4) how statistical power can be increased by meta-analysis or multicentric studies, and improved grouping of birth defects into etiologically more homogeneous subgroups; 5) the distinction between association and causation; 6) the interpretation of clusters in time and space in relation to local environmental causes; and 7) the potential of genetic epidemiology to help elucidate environmental causes. While further research continues into the environmental causes of birth defects, the epidemiologic evidence base for policy making and clinical practice is poor in many areas. The epidemiologic approach is important not only to elucidate environmental causes but also to assess the implementation of existing research into policy and practice for the prevention of birth defects.

Adult↗
PubMed1981

Introduction to sample size determination and power analysis for clinical trials.

The importance of sample size evaluation in clinical trials is reviewed and a general method is presented from which specific equations are derived for sample size determination or the analysis of power for a wide variety os statistical procedures. The method is discussed and illustrated in relation to the t test, tests for proportions, tests of survival time, and tests for correlations as they commonly occur in clinical trials. Most of the specific equations reduce to a simple general form for which tables are presented.

Clinical Trials as Topic↗