Biomedical subjects

Joseph L Gastwirth

Publications and source records attributed to Joseph L Gastwirth.

11 recordsLinked to original sources

PubMed2006

On estimation of the variance in Cochran-Armitage trend tests for genetic association using case-control studies.

The Cochran-Armitage trend test has been used in case-control studies for testing genetic association. As the variance of the test statistic is a function of unknown parameters, e.g. disease prevalence and allele frequency, it must be estimated. The usual estimator combining data for cases and controls assumes they follow the same distribution under the null hypothesis. Under the alternative hypothesis, however, the cases and controls follow different distributions. Thus, the power of the trend tests may be affected by the variance estimator used. In particular, the usual method combining both cases and controls is not an asymptotically unbiased estimator of the null variance when the alternative is true. Two different estimates of the null variance are available which are consistent under both the null and alternative hypotheses. In this paper, we examine sample size and small sample power performance of trend tests, which are optimal for three common genetic models as well as a robust trend test based on the three estimates of the variance and provide guidelines for choosing an appropriate test.

Case-Control Studies↗

PubMed2005

Robust genomic control for association studies.

Population-based case-control studies are a useful method to test for a genetic association between a trait and a marker. However, the analysis of the resulting data can be affected by population stratification or cryptic relatedness, which may inflate the variance of the usual statistics, resulting in a higher-than-nominal rate of false-positive results. One approach to preserving the nominal type I error is to apply genomic control, which adjusts the variance of the Cochran-Armitage trend test by calculating the statistic on data from null loci. This enables one to estimate any additional variance in the null distribution of statistics. When the underlying genetic model (e.g., recessive, additive, or dominant) is known, genomic control can be applied to the corresponding optimal trend tests. In practice, however, the mode of inheritance is unknown. The genotype-based chi (2) test for a general association between the trait and the marker does not depend on the underlying genetic model. Since this general association test has 2 degrees of freedom (df), the existing formulas for estimating the variance factor by use of genomic control are not directly applicable. By expressing the general association test in terms of two Cochran-Armitage trend tests, one can apply genomic control to each of the two trend tests separately, thereby adjusting the chi (2) statistic. The properties of this robust genomic control test with 2 df are examined by simulation. This genomic control-adjusted 2-df test has control of type I error and achieves reasonable power, relative to the optimal tests for each model.

Case-Control Studies↗

PubMed2005

Using the Peters--Belson method to measure health care disparities from complex survey data.

The Peters-Belson (PB) method uses regression to assess wage discrimination and can also be used to analyse disparities for a variety of health care issues, e.g. cancer screening. The PB method estimates the proportion of an overall disparity that is not explained by the covariates in the regression, e.g. education, which may be due to discrimination. This method first fits a regression model with individual-level covariates to the majority/advantaged group and then uses the fitted model to estimate the expected values for minority-group members had they been members of the majority group. The data on disparities in health care available to biomedical researchers differ from data used in legal cases as it is often obtained from large-scale studies or surveys with complex sample designs involving stratified multi-stage cluster sampling. Sample surveys with a large representative sample of various racial/ethnic groups and the extensive collection of important social-demographic variables provide excellent sources of data for assessing disparity for a wide range of health behaviours. We extend the PB method for multiple logistic and linear regressions of simple random samples to weighted data from complex designed survey samples. Because of the weighting and complex sample designs, we show how to apply the Taylor linearization method and delete-one-group jackknife methods to obtain estimates of standard errors for the estimated disparity. Data from the 1998 National Health Interview Survey on racial differences in cancer screening among women is used to illustrate the PB method.

Adult↗

PubMed2005

Bayesian inference for prevalence and diagnostic test accuracy based on dual-pooled screening.

We propose a useful protocol for the problem of screening populations for low-prevalence characteristics such as HIV or drugs. Current HIV screening of blood that has been donated for transfusion involves the testing of individual blood units with an inexpensive enzyme-linked immunosorbent assay test and follow-up with a more accurate and more expensive western blot test for only those units that tested positive. Our cost-effective pooling strategy would enhance current methods by making it possible to accurately estimate the sensitivity and specificity of the initial screening test, and the proportion of defective units that have passed through the system. We also provide a method of estimating the distribution of prevalences for the characteristic throughout the population or subpopulations of interest.

AIDS Serodiagnosis↗

PubMed2005

Sensitivity analysis for trend tests: application to the risk of radiation exposure.

Trend tests are used to assess the relationship between multiple level treatment X and binary response R. In observational studies, however, there may be a confounder U that is associated with treatment X and causally related to response R. When the data for the confounder U are not observed, an approach for assessing the sensitivity of test results to U is provided. Its use is illustrated by examining data from a study of mutation rate after the Chernobyl accident.

Chernobyl Nuclear Accident↗

PubMed2005

Genomic control for association studies under various genetic models.

Case-control studies are commonly used to study whether a candidate allele and a disease are associated. However, spurious association can arise due to population substructure or cryptic relatedness, which cause the variance of the trend test to increase. Devlin and Roeder derived the appropriate variance inflation factor (VIF) for the trend test and proposed a novel genomic control (GC) approach to estimate VIF and adjust the test statistic. Their results were derived assuming an additive genetic model and the corresponding VIF is independent of the candidate allele frequency. We determine the appropriate VIFs for recessive and dominant models. Unlike the additive test, the VIFs for the optimal tests for these two models depend on the candidate allele frequency. Simulation results show that, when the null loci used to estimate the VIF have allele frequencies similar to that of the candidate gene, the GC tests derived for recessive and dominant models remain optimal. When the underlying genetic model is unknown or the null loci and candidate gene have quite different allele frequencies, the GC tests derived for the recessive or dominant models cannot be used while the GC test derived for the additive model can be.

Biometry↗

PubMed2004

A note on appropriate use of statistical tests of mutation rates from ordered groups.

Recently it was found that the frequency of familial dysautonomia (FD) carriers in Ashkenazi Jews (AJ) was higher in AJ of Polish descent compared to AJ of non-Polish descent. The study population was classified into groups ranging from no to full Polish origin. The statistical procedure used to compare the frequencies of FD carriers did not incorporate this intrinsic ordering of individuals by degree of Polish ancestry. In this paper we describe a test designed to utilize this information and show that it is more powerful than the standard test of equality of proportions. In particular, the p value of the trend test on their data is noticeably lower (0.003) than 0.012 found by the standard test, providing stronger evidence for a relationship between allele frequency and Polish descent.

Data Interpretation, Statistical↗

PubMed2004

Understanding the factors underlying disparities in cancer screening rates using the Peters-Belson approach: results from the 1998 National Health Interview Survey.

BACKGROUND: Cancer screening rates vary substantially by race and ethnicity. We applied the Peters-Belson approach, often used in wage discrimination studies, to analyze disparities in cancer screening rates between different groups using the 1998 National Health Interview Survey. METHODS: A regression model predicting the probability of getting screened is fit to the majority group and then used to estimate the expected values for minority group members had they been members of the majority group. The average difference between the observed and expected values for a minority group is the part of the disparity that is not explained by the covariates. RESULTS: The observed disparities in colorectal cancer screening (5.88%) and digital rectal screening (8.54%) between white and black men were explained fully by the difference in their covariate distributions. Only half of the disparity in the observed screening rates (13.54% for colorectal and 17.47% for digital rectal) between white and Hispanic men was explained by the difference in covariates between the groups. The entire disparity observed in mammography screening rates for black and Hispanic women (2.71% and 6.53%, respectively) compared with white women was explained by the difference in covariate distributions. CONCLUSIONS: We found that the covariates that explain the disparity in screening rates between the white and the black population do not explain the disparity between the white and the Hispanic population. Knowing how much of a health disparity is explained by measured covariates can be used to develop more effective interventions and policies to eliminate disparity.

Adult↗

PubMed2003

The use of the 'reverse Cornfield inequality' to assess the sensitivity of a non-significant association to an omitted variable.

Unlike randomized experimental studies, investigators do not have control over the treatment assignment in observational studies. Hence, the treated and control (non-treated) groups may have widely different distributions of unobserved covariates. Thus, if observational data are analysed as if they had arisen from a controlled study, the analyses are subject to potential bias. Sensitivity analysis is a technique for assessing whether the inference drawn from a study could be altered by a moderate 'imbalance', between the distribution of the covariates in different groups. In this paper, we examine the sensitivity analysis of the test of proportions in 2 x 2 tables from a new perspective: 'could a non-significant result have occurred because the treated group has a higher prevalence of an unobserved risk factor?'. The study was motivated by an analysis of the studies concerning with the possible effect of spermicide use on birth defects that were cited in a legal decision.

Analysis of Variance↗

PubMed2003

Efficiency robust tests for mapping quantitative trait loci using extremely discordant sib pairs.

In 1972, Haseman and Elston proposed a pioneering regression method for mapping quantitative trait loci using randomly selected sib pairs. Recently, the statistical power of their method was shown to be increased when extremely discordant sib pairs are ascertained. While the precise genetic model may not be known, prior information that constrains IBD probabilities is often available. We investigate properties of tests that are robust against model uncertainty and show that the power gain from further constraining IBD probabilities is marginal. The additional linkage information contained in the trait values can be incorporated by combining the Haseman-Elston regression method and a robust allele sharing test.

Chromosome Mapping↗

PubMed2002

Efficiency of DNA pooling to estimate joint allele frequencies and measure linkage disequilibrium.

Pooling DNA samples can yield efficient estimates of the prevalence of genetic variants. We extend methods of analyzing pooled DNA samples to estimate the joint prevalence of variants at two or more loci. If one has a sample from the general population, one can adapt the method for joint prevalence estimation to estimate allele frequencies and D, the measure of linkage disequilibrium. The parameter D is fundamental in population genetics and in determining the power of association studies. In addition, joint allelic prevalences can be used in case-control studies to estimate the relative risks of disease from joint exposures to the genetic variants. Our methods allow for imperfect assay sensitivity and specificity. The expected savings in numbers of assays required when pooling is utilized compared to individual testing are quantified.

Alleles↗