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PubMedDate not supplied

Nonparametric tests for linkage with dependent sib pairs.

Sib pair tests for linkage to a quantitative trait or affection status are examined by simulation. A sibship of size s contributes only s-1 independent sib pairs but all s(s-1)/2 pairs are needed for an efficient test. Redundancy increases with sibship size. Using simulated data on the null hypothesis of no linkage, we have considered equal and unequal weights. Unequal weights lose power as measured by the equivalent number of observations, and goodness of fit to the theoretical distribution is degraded. The Fisher z(r) test with equally weighted pairs is more reliable than any t(r) test based on conjectured degrees of freedom, but significance levels must be established by simulation if the number of pairs is small or redundancy is large. An approach to parametric analysis through nuisance parameters is discussed.

Alleles↗
PubMed2003

Proving non-inferiority or equivalence of two treatments with dichotomous endpoints using exact methods.

Since the early work of RA Fisher, exact methods have been recognized as important tools in data analysis because they provide valid statistical inference even with small sample sizes, or with sparse or skewed data. With the recent advance of computational power and the availability of commercial software packages, exact methods have gained substantial popularity over the past two decades. However, most of these exact methods have been devoted to testing classical null hypotheses of no differences, and until recently little was known about exact methods dealing with non-inferiority or equivalence hypotheses. The presence of nuisance parameters in testing non-inferiority/equivalence hypotheses presents a special challenge for exact methods because of the intense computational requirement. In this paper, we review exact methods available for proving non-inferiority or equivalence of two treatments with a dichotomous endpoint. First, we present the general methodology for conducting exact tests for non-inferiority or equivalence; we then discuss several unconditional and conditional methods available for constructing hypothesis tests and confidence intervals based on three commonly used measures, namely, the difference, relative risk, and odds ratio of two independent proportions or rates. Finally, we illustrate with several examples the application of these exact methods in analysing and planning non-inferiority or equivalence trials.

Biomedical Research↗
PubMed2006

An integrated-likelihood method for estimating genetic differentiation between populations.

The aim of this article is to develop an integrated-likelihood (IL) approach to estimate the genetic differentiation between populations. The conventional maximum-likelihood (ML) and pseudolikelihood (PL) methods that use sample counts of alleles may cause severe underestimations of FST, which means overestimations of theta=4Nm, when the number of sampling localities is small. To reduce such bias in the estimation of genetic differentiation, we propose an IL method in which the mean allele frequencies over populations are regarded as nuisance parameters and are eliminated by integration. To maximize the IL function, we have developed two algorithms, a Monte Carlo EM algorithm and a Laplace approximation. Our simulation studies show that the method proposed here outperforms the conventional ML and PL methods in terms of unbiasedness and precision. The IL method was applied to real data for Pacific herring and African elephants.

Algorithms↗
PubMed2004

Applications of Bayesian statistical methods in microarray data analysis.

Microarray technology allows one to measure gene expression levels simultaneously on the whole-genome scale. The rapid progress generates both a great wealth of information and challenges in making inferences from such massive data sets. Bayesian statistical modeling offers an alternative approach to frequentist methodologies, and has several features that make these methods advantageous for the analysis of microarray data. These include the incorporation of prior information, flexible exploration of arbitrarily complex hypotheses, easy inclusion of nuisance parameters, and relatively well developed methods to handle missing data. Recent developments in Bayesian methodology generated a variety of techniques for the identification of differentially expressed genes, finding genes with similar expression profiles, and uncovering underlying gene regulatory networks. Bayesian methods will undoubtedly become more common in the future because of their great utility in microarray analysis.

Bayes Theorem↗
PubMed2004

Simultaneous confidence intervals for ratios with applications to the comparison of several treatments with a control.

OBJECTIVES: In this article, we illustrate and compare exact simultaneous confidence sets with various approximate simultaneous confidence intervals for multiple ratios as applied to many-to-one comparisons. Quite different datasets are analyzed to clarify the points. METHODS: The methods are based on existing probability inequalities (e.g., Bonferroni, Slepian and Sidak), estimation of nuisance parameters and re-sampling techniques. Exact simultaneous confidence sets based on the multivariate t-distribution are constructed and compared with approximate simultaneous confidence intervals. RESULTS: It is found that the coverage probabilities associated with the various methods of constructing simultaneous confidence intervals (for ratios) in manyto-one comparisons depend on the ratios of the coefficient of variation for the mean of the control group to the coefficient of variation for the mean of the treatments. If the ratios of the coefficients of variations are less than one, the Bonferroni corrected Fieller confidence intervals have almost the same coverage probability as the exact simultaneous confidence sets. Otherwise, the use of Bonferroni intervals leads to conservative results. CONCLUSIONS: When the ratio of the coefficient of variation for the mean of the control group to the coefficient of variation for the mean of the treatments are greater than one (e.g., in balanced designs with increasing effects), the Bonferroni simultaneous confidence intervals are too conservative. Therefore, we recommend not using Bonferroni for this kind of data. On the other hand, the plug-in method maintains the intended confidence coefficient quite satisfactorily; therefore, it can serve as the best alternative in any case.

Abdominal Pain↗
PubMed1989

Some methodological issues in statistical estimation of air pollution and health.

This paper introduces a new method for estimating a dose-response relationship from spatially averaged time series of air pollution and health data. Because time is perceived as a nuisance parameter to be eliminated, least-squares regression and traditional time series methodology (e.g., spectral analysis Box-Jenkins methods) are rejected in favor of a nonparametric estimation procedure based on observing health effects in times of nearly equal pollution. The method requires estimating the ratio of two density functions and avoids problems of aggregation, linearity and normality. In spite of the formal tests described, the procedure seems most useful at present as a data analytic and data display device rather than as an inferential tool.

Air Pollution↗
PubMed1993

Conditional regression analysis of the exposure-disease odds ratio using known probability-of-exposure values.

Conditional inference methods are proposed for the odds ratio between binary exposure and disease variables when only the probability of exposure is known for each study subject. We develop a conditional likelihood approach that removes nuisance parameters and permits inferences to be made about important parameters in log odds ratio regression models. We also discuss a heuristic procedure based on estimating the (unknown) number of truly exposed individuals; this procedure provides a simple framework for interpreting our likelihood-based statistics, and leads to a Mantel-Haenszel-type estimator and a goodness-of-fit test. As an example of the use of this methodology, we present an analysis of some genetic data of Swift et al. (1976, Cancer Research 36, 209-215).

Adult↗
PubMed1993

Sequential equivalence testing and repeated confidence intervals, with applications to normal and binary responses.

We propose group sequential tests of the equivalence of two treatments based on ideas related to repeated confidence intervals. These tests adapt readily to unpredictable group sizes, to the possibility of continuing even though a boundary has been crossed, and to nonnormal observations. In comparing two binomial distributions, the required sample size depends strongly on the average success probability and an adaptive choice of group size is needed to produce an efficient test meeting specified error probability constraints. A special case is the experiment where interim analyses are performed, not for the purpose of early termination but simply to adjust the sample size so that nominal error rates will be guaranteed, despite the presence of a nuisance parameter.

Binomial Distribution↗
PubMed1996

The assessment of individual and population bioequivalence.

We develop a statistical methodology for the assessment of individual bioequivalence when a crossover design is invoked. The location parameters for our model consist of population-averaged parameters for formulation, population-averaged parameters for nuisance effects (sequence, period, carryover, etc.), and subject-specific parameters for formulation. We do not impose any distributional assumptions other than the existence of first- and second-order moments. We derive unbiased estimators for all of the parameters in the model and construct subject-specific bioequivalence scores which exclude the effects of the nuisance parameters. We assess individual bioequivalence by constructing distribution-free tolerance intervals based on the sample of bioequivalence scores.

Calcium Channel Blockers↗
PubMed1993

Small-sample confidence sets for the MTD in a phase I clinical trial.

Properties of procedures for interval estimation of the maximum tolerable dose (MTD) in a Phase I clinical trial are examined, using a two-stage stochastic sampling scheme (Storer, 1989) as a paradigm for development. Although the likelihood function for the data arising from such a scheme is identical to one arising under a conditional binomial sampling assumption, intervals based on the exact distribution of the usual large-sample statistics under this assumption do not offer improvement over unadjusted intervals. However, consideration of the distribution of these statistics based on the true stochastic sampling scheme can lead to the construction of intervals with correct coverage probabilities that do not depend on the true values of the model parameters. Membership in the confidence set can be evaluated by Monte Carlo simulation at a restricted maximum likelihood estimate of the nuisance slope parameter, despite upward bias in its estimation from the up-and-down sampling scheme. The lack of information in the small-sample setting is reflected in a large proportion of confidence intervals that include infinite values for the MTD, especially when the dose-response curve is shallow. Intervals based on a likelihood ratio criterion perform best in this regard.

Algorithms↗
PubMed2025

Simultaneous inference for generalized linear models with unmeasured confounders.

Tens of thousands of simultaneous hypothesis tests are routinely performed in genomic studies to identify differentially expressed genes. However, due to unmeasured confounders, many standard statistical approaches may be substantially biased. This paper investigates the large-scale hypothesis testing problem for multivariate generalized linear models in the presence of confounding effects. Under arbitrary confounding mechanisms, we propose a unified statistical estimation and inference framework that harnesses orthogonal structures and integrates linear projections into three key stages. It begins by disentangling marginal and uncorrelated confounding effects to recover the latent coefficients. Subsequently, latent factors and primary effects are jointly estimated through lasso-type optimization. Finally, we incorporate projected and weighted bias-correction steps for hypothesis testing. Theoretically, we establish the identification conditions of various effects and non-asymptotic error bounds. We show effective Type-I error control of asymptotic-tests as sample and response sizes approach infinity. Numerical experiments demonstrate that the proposed method controls the false discovery rate by the Benjamini-Hochberg procedure and is more powerful than alternative methods. By comparing single-cell RNA-seq counts from two groups of samples, we demonstrate the suitability of adjusting confounding effects when significant covariates are absent from the model.

Hidden variables↗
PubMed2006

Secondary analysis of case-control data.

We extend the discussion of Lee et al. and others on methods for performing secondary analyses of case-control sampled data and carry out an extensive investigation of efficiency and robustness. We find that, with the exception of the 'analyse-the-controls-only' strategy for populations in which cases are rare, ad hoc methods in common usage often lead to extremely misleading conclusions and that it is not possible to tell in advance when this will happen. Weighted likelihood and semi-parametric maximum likelihood methods are justified theoretically. We find that semi-parametric maximum likelihood can be as much as twice as efficient as the weighted method, but is subject to bias in estimating parameters of interest when the nuisance models this method requires have been mis-specified. The weighted method needs no nuisance models and thus is robust in this regard, but we cannot tell when it is going to be very inefficient without sophisticated modelling as through the SPML method. Practitioners should routinely use both methods and will often have to weigh up the practical consequences of severe inefficiency and lack of robustness in the context of their enquiries.

Bias↗
PubMed1990

The comparison of a fibrogenic and two nonfibrogenic dusts by bronchoalveolar lavage.

Analysis of bronchoalveolar lavage fluid (BALF) appears to be a sensitive approach to characterizing an acute inflammatory response within the lung. More work, however, is needed to determine if analyses of BALF endpoints can predict chronic responses (i.e., fibrosis). The objective of the present study was to compare the dose and temporal pulmonary response of a known fibrogenic agent, silica, and two known nonfibrogenic agents, aluminum oxide and titanium dioxide. Animals were instilled with silica (0, 0.2, 1.0, or 5.0 mg/100 g body wt), titanium dioxide (1.0 or 5 mg/100 g body wt), aluminium oxide (1.0 or 5.0 mg/100 g body wt) or saline. Animals (n = 5/group) were terminated 1, 7, 14, 28, and 63 days following instillation, and the BALF was characterized by biochemical and cellular assays. Histopathological changes were determined at 60 days after exposure. The biochemical results demonstrated BALF levels of lactate dehydrogenase (LDH), beta-glucuronidase (BG), N-acetylglucosaminidase (NAG), and total protein (TP) increased in a dose-related fashion at the earlier time points for all test materials, with the magnitude of change being greatest for silica. The temporal response for these parameters was significantly different for the two classes of materials. With time, the response for the fibrogenic dust steadily increased, while the levels for the nonfibrogenic dusts decreased toward normal values during the 2-month study period. Of the cellular changes, total cell numbers, neutrophils, and lymphocyte numbers were the most sensitive markers of the pulmonary response. As shown with the biochemical parameters, the cellular response to silica increased with time while that of the nuisance dusts did not. It was also found that, similar to inhalation studies, high doses of a nuisance dust may result in toxicity/inflammation. This toxicity at high dose levels emphasizes the importance of choosing relevant doses when comparing potentially fibrogenic and nonfibrogenic dusts. In conclusion, the persistent and progressive changes seen in the biochemical (LDH, TP, BG, NAG) and cellular parameters (total cells, neutrophils and lymphocytes) following silica administration correlated with the fibrotic response which occurred after exposure to this material. The less dramatic and transient changes seen with aluminum oxide and titanium dioxide correlated with the inert nature of these nuisance dusts. The results of this study indicate evaluation of BALF may provide a means to predict the chronic pulmonary response to a material.

Acetylglucosaminidase↗
PubMed2002

Analysis of clustered binary outcomes using within-cluster paired resampling.

Conditional logistic regression (CLR) is useful for analyzing clustered binary outcome data when interest lies in estimating a cluster-specific exposure parameter while treating the dependency arising from random cluster effects as a nuisance. CLR aggregates unmeasured cluster-specific factors into a cluster-specific baseline risk and is invalid in the presence of unmodeled heterogeneous covariate effects or within-cluster dependency. We propose an alternative, resampling-based method for analyzing clustered binary outcome data, within-cluster paired resampling (WCPR), which allows for within-cluster dependency not solely due to baseline heterogeneity. For example, dependency may be in part caused by heterogeneity in response to an exposure across clusters due to unmeasured cofactors. When both CLR and WCPR are valid, our simulations suggest that the two methods perform comparably. When CLR is invalid, WCPR continues to have good operating characteristics. For illustration, we apply both WCPR and CLR to a periodontal data set where there is heterogeneity in response to exposure across clusters.

Adult↗
PubMed2006

Effects of prosodic emotional intensity on activation of associative auditory cortex.

Functional magnetic resonance imaging was used to investigate hemodynamic responses to adjectives pronounced in happy and angry intonations of varying emotional intensity. In separate sessions, participants judged the emotional valence of either intonation or semantics. To disentangle effects of emotional prosodic intensity from confounding acoustic parameters, mean and variability of volume and fundamental frequency of each stimulus were included as nuisance variables in the statistical models. A linear dependency between hemodynamic responses and emotional intensity of happy and angry intonations was found in the bilateral superior temporal sulcus during both tasks, indicating that increases of hemodynamic responses in this region are elicited by both positive and negative prosody independent of low-level acoustic properties and task instructions.

Acoustic Stimulation↗
PubMed2001

Synthetic estimators with moderating influence: the carry-over in cross-over trials revisited.

A general approach to combining alternative estimators of a parameter is described and applied to the analysis of 2x2 cross-over trials in which the treatment effect is of principal interest and carry-over is a nuisance feature. The approach requires prior information about the carry-over. Although modest information is sufficient, more information is rewarded by greater efficiency. The combination, or synthetic, estimator exhibits a moderating influence: its mean squared error is a flat function of the carry-over effect in the range of its feasible values, and for the largest feasible carry-over effect it is superior to either of the originally considered estimators. An extension of the approach is outlined and two other applications in medical research discussed. Although the method can be regarded as Bayesian in spirit, we focus on its resampling (frequentist) properties.

Biometry↗
PubMed1994

Risk assessment: good for health?

Risk assessment is a scientific endeavour on which risk management can be based and policy priorities can be set. Of prime importance is the choice of risk attributes and the health indicators to focus upon. Problem ranking and priority setting depend strongly on that choice. In the current risk policy of The Netherlands' Ministry of the Environment 'individual risk' is defined as the probability of dying due to one year's exposure to a certain agent or activity. If this approach is applied to the indoor environment, strong mitigation measures should be taken concerning NO2, radon and particulate matter to improve the percentage of 'healthy homes'. However, risk is more than the chance to die. Therefore some more parameters should be used to characterize the indoor environment, like chemical and biological mixtures from outside and inside and activities of inhabitants. Important health indicators like irreversible/reversible physiological effects and nuisance should be taken into account. Risk has to tell us about the possibility of health damage, about the nature of health damage and about the uncertainty in both.

Air Pollution, Indoor↗
PubMed1990

Endocrine and renal effects of nifedipine gastrointestinal therapeutic system in patients with essential hypertension. Results of a multicenter trial. The Modern Approach to the Treatment of Hypertension Study Group.

Use of thiazide diuretics and beta-blockers in the treatment of hypertension may result in metabolic derangements and/or disturbances in the parameters of renal function, which offset the benefits of blood pressure reduction by adversely affecting other cardiovascular risk factors, particularly in special patient groups such as the elderly or those with concomitant diseases. Newer agents including calcium channel blockers, which exert potent antihypertensive effects without adversely affecting metabolic parameters unfavorably, are used with increasing frequency in hypertensive patients, but their clinical utility has been limited by the need for multiple daily dosing with attendant fluctuations in plasma levels thought to be associated with nuisance side effects and possible gaps in therapeutic protection. The Modern Approach to the Treatment of Hypertension (MATH) trial was conducted to determine the efficacy and safety of the new once-daily nifedipine gastrointestinal therapeutic system (GITS) formulation in a large cohort of mild-to-moderate hypertensive patients overall, and to identify specific effects of therapy in the presence of complicating factors such as diabetes and obesity. A total of 1155 patients from 127 centers were treated with nifedipine GITS in the MATH trial, including 157 diabetic (fasting plasma glucose greater than 120 mg/dL or on hypoglycemic therapy) and 747 nondiabetic patients. There were 458 obese patients (body mass index [BMI] greater than 30), 489 overweight patients (BMI greater than or equal to 25 less than or equal to 30), and 206 patients of normal weight (BMI less than 25).(ABSTRACT TRUNCATED AT 250 WORDS)

Aged↗