DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups

Medical researchers endeavor to identify potentially useful biomarkers to develop markerbased screening assays for disease diagnosis and prevention. Useful summary measures which properly evaluate the discriminative ability of diagnostic markers are critical for this purpose. Literature and existing software, for example, R packages nicely cover summary measures for diagnostic markers used for the binary case (e.g., healthy vs. diseased). An intermediate population at an early disease stage usually exists between the healthy and the fully diseased population in many disease processes. Supporting utilities for threegroup diagnostic tests are highly desired and important for identifying patients at the early disease stage for timely treatments. However, application packages which provide summary measures for three ordinal groups are currently lacking. This paper focuses on two summary measures of diagnostic accuracy—volume under the receiver operating characteristic surface and the extended Youden index, with three diagnostic groups. We provide the R package DiagTest3Grp to estimate, under both parametric and nonparametric assumptions, the two summary measures and the associated variances, as well as the optimal cut-points for disease diagnosis. An omnibus test for multiple markers and a Wald test for two markers, on independent or paired samples, are incorporated to compare diagnostic accuracy across biomarkers. Sample size calculation under the normality assumption can be performed in the R package to design future diagnostic studies. A real world application evaluating the diagnostic accuracy of neuropsychological markers for Alzheimer’s disease is used to guide readers through step-by-step implementation of DiagTest3Grp to demonstrate its utility

WAVELET NONPARAMETRIC REGRESSION WITH DEPENDENT DATA

Estimation of the regression function has many applications in agriculture and industry. Usually, the regression function is assumed a known functional form which depends on unknown parameters. Nonparametric regression theory makes no such assumption and often uses some kernel functions to form the so-called Watson Nadaraya type estimators. Such estimators were extensively studied by Watson (1964), Nadaraya (1964, 1989) and Collomb (1981, 1985). When the data are independent, these estimators have nice asymptotic convergence properties. When the data are dependent, Gyorfi et al (1989) gave some large sample properties for the Watson-Nadaraya estimators. In this paper, the recently developed theory of wavelet will be used to estimate the regression function when the data are dependent. Large sample properties for the wavelet estimator will be proved, and the wavelet smoothing will be compared with the other well known nonparametric smoothing methods

Availability and Reliability Analysis of Computer Software Systems Considering Maintenance and Security Issues

Ph.DDOCTOR OF PHILOSOPH

Test Of Homogeneity For Umbrella Alternatives In Dose-Response Relationship For Poisson Variables

This article concerns the testing and estimation of a dose-response effect in medical studies. We study the statistical test of homogeneity against umbrella alternatives in a sequence of Poisson distributions associated with an ordered dose variable. We propose a test similar to Cochran-Armitage’s trend test and study the asymptotic null distribution and the power of the test. We also propose an estimator to the vertex point when the umbrella pattern is confirmed and study the performance of the estimator. A real data set pertaining to the number of visible revertant colonies associated with different doses of test agents in an in vitro mutagenicity assay is used to demonstrate the test and estimation process

Genetic and Pharmacological Factors That Influence Reproductive Aging in Nematodes

Age-related degenerative changes in the reproductive system are an important aspect of aging, because reproductive success is the major determinant of evolutionary fitness. Caenorhabditis elegans is a prominent organism for studies of somatic aging, since many factors that extend adult lifespan have been identified. However, mechanisms that control reproductive aging in nematodes or other animals are not well characterized. To use C. elegans to measure reproductive aging, we analyzed mated hermaphrodites that do not become sperm depleted and monitored the duration and level of progeny production. Mated hermaphrodites display a decline of progeny production that culminates in reproductive cessation before the end of the lifespan, demonstrating that hermaphrodites undergo reproductive aging. To identify factors that influence reproductive aging, we analyzed genetic, environmental, and pharmacological factors that extend lifespan. Dietary restriction and reduced insulin/insulin-like growth factor signaling delayed reproductive aging, indicating that nutritional status and a signaling pathway that responds to environmental stress influence reproductive aging. Cold temperature delayed reproductive aging. The anticonvulsant medicine ethosuximide, which affects neural activity, delayed reproductive aging, indicating that neural activity can influence reproductive aging. Some of these factors decrease early progeny production, but there is no consistent relationship between early progeny production and reproductive aging in strains with an extended lifespan. To directly examine the effects of early progeny production on reproductive aging, we used sperm availability to modulate the level of early reproduction. Early progeny production neither accelerated nor delayed reproductive aging, indicating that reproductive aging is not controlled by use-dependent mechanisms. The implications of these findings for evolutionary theories of aging are discussed

Estimating correlation between multivariate longitudinal data in the presence of heterogeneity

Abstract Background Estimating correlation coefficients among outcomes is one of the most important analytical tasks in epidemiological and clinical research. Availability of multivariate longitudinal data presents a unique opportunity to assess joint evolution of outcomes over time. Bivariate linear mixed model (BLMM) provides a versatile tool with regard to assessing correlation. However, BLMMs often assume that all individuals are drawn from a single homogenous population where the individual trajectories are distributed smoothly around population average. Methods Using longitudinal mean deviation (MD) and visual acuity (VA) from the Ocular Hypertension Treatment Study (OHTS), we demonstrated strategies to better understand the correlation between multivariate longitudinal data in the presence of potential heterogeneity. Conditional correlation (i.e., marginal correlation given random effects) was calculated to describe how the association between longitudinal outcomes evolved over time within specific subpopulation. The impact of heterogeneity on correlation was also assessed by simulated data. Results There was a significant positive correlation in both random intercepts (ρ = 0.278, 95% CI: 0.121–0.420) and random slopes (ρ = 0.579, 95% CI: 0.349–0.810) between longitudinal MD and VA, and the strength of correlation constantly increased over time. However, conditional correlation and simulation studies revealed that the correlation was induced primarily by participants with rapid deteriorating MD who only accounted for a small fraction of total samples. Conclusion Conditional correlation given random effects provides a robust estimate to describe the correlation between multivariate longitudinal data in the presence of unobserved heterogeneity (NCT00000125)

Genome-wide identification and evolution of ATP-binding cassette transporters in the ciliate Tetrahymena thermophila: A case of functional divergence in a multigene family

<p>Abstract</p> <p>Background</p> <p>In eukaryotes, ABC transporters that utilize the energy of ATP hydrolysis to expel cellular substrates into the environment are responsible for most of the efflux from cells. Many members of the superfamily of ABC transporters have been linked with resistance to multiple drugs or toxins. Owing to their medical and toxicological importance, members of the ABC superfamily have been studied in several model organisms and warrant examination in newly sequenced genomes.</p> <p>Results</p> <p>A total of 165 ABC transporter genes, constituting a highly expanded superfamily relative to its size in other eukaryotes, were identified in the macronuclear genome of the ciliate <it>Tetrahymena thermophila</it>. Based on ortholog comparisons, phylogenetic topologies and intron characterizations, each highly expanded ABC transporter family of <it>T</it>. <it>thermophila </it>was classified into several distinct groups, and hypotheses about their evolutionary relationships are presented. A comprehensive microarray analysis revealed divergent expression patterns among the members of the ABC transporter superfamily during different states of physiology and development. Many of the relatively recently formed duplicate pairs within individual ABC transporter families exhibit significantly different expression patterns. Further analysis showed that multiple mechanisms have led to functional divergence that is responsible for the preservation of duplicated genes.</p> <p>Conclusion</p> <p>Gene duplications have resulted in an extensive expansion of the superfamily of ABC transporters in the <it>Tetrahymena </it>genome, making it the largest example of its kind reported in any organism to date. Multiple independent duplications and subsequent divergence contributed to the formation of different families of ABC transporter genes. Many of the members within a gene family exhibit different expression patterns. The combination of gene duplication followed by both sequence divergence and acquisition of new patterns of expression likely plays a role in the adaptation of <it>Tetrahymen </it>a to its environment.</p

Mated progeny production is a biomarker of aging in Caenorhabditis elegans

The relationships between reproduction and aging are important for understanding the mechanisms of aging and evaluating evolutionary theories of aging. To investigate the effects of progeny production on reproductive and somatic aging, we conducted longitudinal studies of Caenorhabditis elegans hermaphrodites. For mated wild-type animals that were not sperm limited and survived past the end of the reproductive period, high levels of cross-progeny production were positively correlated with delayed reproductive and somatic aging. In this group of animals, individuals that generated more cross progeny also reproduced and lived longer than individuals that generated fewer cross progeny. These results indicate that progeny production does not accelerate reproductive or somatic aging. This longitudinal study demonstrated that cumulative cross progeny production through day four is an early-stage biomarker that is a positive predictor of longevity. Furthermore, in mated animals, high levels of early cross progeny production were positively correlated with high levels of late cross progeny production, indicating that early progeny production does not accelerate reproductive aging. The relationships between progeny production and aging were further evaluated by comparing self-fertile hermaphrodites that generated relatively few self progeny with mated hermaphrodites that generated many cross progeny. The timing of age-related somatic degeneration was similar in these groups, suggesting progeny production does not accelerate somatic aging. These studies rigorously define relationships between progeny production, reproductive aging, and somatic aging and identify new biomarkers of C. elegans aging. These results indicate that some mechanisms or pathways control age-related degeneration of both reproductive and somatic tissues in C. elegans

Measuring Overall Heterogeneity in Meta-Analyses: Application to CSF Biomarker Studies in Alzheimer’s Disease

The interpretations of statistical inferences from meta-analyses depend on the degree of heterogeneity in the meta-analyses. Several new indices of heterogeneity in meta-analyses are proposed, and assessed the variation/difference of these indices through a large simulation study. The proposed methods are applied to biomakers of Alzheimer’s disease