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At least 91 records · Page 5Linked to original sources
PubMed2003

How robust are health plan quality indicators to data loss? A Monte Carlo simulation study of pediatric asthma treatment.

OBJECTIVES: (1) To test the robustness of a health plan quality indicator (QI) for persistent asthma to various forms of data loss and (2) to assess the implications of the findings for other health plan quality measures. DATA SOURCES/STUDY SETTINGS: Maryland Medicaid fee-for-service (FFS) claims. Children with asthma (n = 5,804) were selected from Medicaid enrollment records and medical and pharmacy FFS claims filed between June 1996 and December 1997. STUDY DESIGN: A variant of a HEDIS measure for treatment of persistent asthma (the percent of asthma patients filling two or more rescue medications who also filled a controller medication) was selected to test the robustness of proportion-based QIs to loss of data. Data loss was simulated through a series of Monte Carlo experiments. DATA COLLECTION/EXTRACTION METHODS: Merged FFS medical and prescription claims. PRINCIPAL FINDINGS: The asthma QI measure was highly robust to systematic and random data loss. The measure declined by less than 2 percent in the presence of up to a 35 percent data loss. Redundancy in the numerator of the QI significantly increased the robustness of the measure to data loss. CONCLUSIONS: A HEDIS-related QI measure for persistent asthma is robust to data loss. The findings suggest that other proportion-based quality indicators, particularly those in which plan members have multiple opportunities to meet the numerator criterion, are likely to reflect true levels of health plan quality in the face of incomplete data capture.

Adolescent↗
PubMedDate not supplied

Simulation/optimization modeling for robust pumping strategy design.

A new simulation/optimization modeling approach is presented for addressing uncertain knowledge of aquifer parameters. The Robustness Enhancing Optimizer (REO) couples genetic algorithm and tabu search as optimizers and incorporates aquifer parameter sensitivity analysis to guide multiple-realization optimization. The REO maximizes strategy robustness for a pumping strategy that is optimal for a primary objective function (OF), such as cost. The more robust a strategy, the more likely it is to achieve management goals in the field, even if the physical system differs from the model. The REO is applied to trinitrotoluene and Royal Demolition Explosive plumes at Umatilla Chemical Depot in Oregon to develop robust least cost strategies. The REO efficiently develops robust pumping strategies while maintaining the optimal value of the primary OF-differing from the common situation in which a primary OF value degrades as strategy reliability increases. The REO is especially valuable where data to develop realistic probability density functions (PDFs) or statistically derived realizations are unavailable. Because they require much less field data, REO-developed strategies might not achieve as high a mathematical reliability as strategies developed using many realizations based upon real aquifer parameter PDFs. REO-developed strategies might or might not yield a better OF value in the field.

Computer Simulation↗
PubMed1994

Robust adaptive microphone array processing for hearing aids: realistic speech enhancement.

The problem of combining the outputs of an array of microphones as a single input for a hearing aid is investigated. Emphasis is placed on the conservative prediction of realistically achievable performance gains provided by the array over a single microphone. Performance improvement is measured as a change in the speech reception threshold (SRT) between single microphone and multimicrophone conditions. Consistent with previous work, predictions of this change in SRT using intelligibility averaged gain, [symbol: see text] are shown to be good. Consequently, this measure is used, along with changes in signal-to-noise ratios (SNRs), to evaluate array performance. The results presented include the effects of acoustic headshadow, small room reverberation, microphone placement uncertainty, and desired speaker location uncertainty. It is in this context that realistic predictions of speech enhancement provided by robust adaptive microphone array processors are discussed. Performance improvements are demonstrated relative to the "best" single microphone in the array for three types of spatial filters: Fixed, robust block processed, and robust adaptive. The performance of the robust block processed arrays is shown to be attainable with adaptive implementations. One fundamental criterion employed in robust beamformer design directly limits the amount of cancellation of the desired signal that can occur.

Adult↗
PubMed2006

The APL test: extension to general nuclear families and haplotypes and examination of its robustness.

OBJECTIVE: The Association in the Presence of Linkage test (APL) is a powerful statistical method that allows for missing parental genotypes in nuclear families. However, in its original form, the statistic does not easily extend to mixed nuclear family structures nor to multiple-marker haplotypes. Furthermore, the robustness of APL in practice has not been examined. Here we present a generalization of the APL model and examination of its robustness under a variety of non-standard scenarios. METHODS: The generalization is made possible by incorporating a bootstrap variance estimator instead of the original robust variance estimator. This allows for use of more than two affected siblings. Haplotype analysis was accomplished by combining estimation of haplotype phase into the EM algorithm. Computer simulation was used to examine robustness of the APL to departures from test assumptions. RESULTS: The extended APL tests both single-marker and multiple-marker haplotypes and shows more power than other association methods. Simulation results showed that the single-marker APL test is robust to the departure from HWE. For the haplotype test, violation of the HWE assumption can inflate type I error. We also evaluated general guidelines for the validity of APL with rare alleles and rare haplotypes. Software for the APL test is available from http://www.chg.duke.edu/research/apl.html.

Computer Simulation↗
PubMed1999

Impact of robustness of program implementation on outcomes of clients in dual diagnosis programs.

Three types of treatment-behavioral skills training, a 12-step recovery model, and intensive case management-provided to 132 clients at four facilities were identified as being robustly or not robustly implemented, depending on whether core elements of these treatments were emphasized. Outcomes and costs of services to clients were examined over 18 months. Clients receiving robustly implemented behavioral skills training had significantly higher psychosocial functioning and lower costs for supportive services than those receiving nonrobustly implemented training. Clients receiving robustly implemented case management also exhibited significantly higher psychosocial functioning and lower costs for intensive services than those in the nonrobust intervention. To be effective, dual diagnosis programs should better manage the robustness of implementation of planned interventions.

Adolescent↗
PubMedDate not supplied

Robust multivariate methods in laboratory techniques and in assisting medical diagnosis.

The usefulness of robust multivariate methods in medical applications, for example, the indirect estimation of total lung capacity by robust regression and the assistance of medical diagnosis in obstructive airways disease using robust discriminant functions, is discussed. The results of robust methods that consist in downweighting the influence of the multivariate outliers are compared with the outcomes of classical procedures. The advantages of modern robust algorithms are proved in the present study. It is planned to include the methods in the system for the computerized consulting unit for respiratory diseases that is being set up in Wrocław.

Algorithms↗
PubMed2005

Quantifying the robustness of a broth-based Escherichia coli O157:H7 growth model in ground beef.

The robustness of a microbial growth model must be assessed before the model can be applied to new food matrices; therefore, a methodology for quantifying robustness was developed. A robustness index (RI) was computed as the ratio of the standard error of prediction to the standard error of calibration for a given model, where the standard error of calibration was defined as the root mean square error of the growth model against the data (log CFU per gram versus time) used to parameterize the model and the standard error of prediction was defined as the root mean square error of the model against an independent data set. This technique was used to evaluate the robustness of a broth-based model for aerobic growth of Escherichia coli 0157:H7 (in the U.S Department of Agriculture Agricultural Research Service Pathogen Modeling Program) in predicting growth in ground beef under different conditions. Comparison against previously published data (132 data sets with 1,178 total data points) from experiments in ground beef at various experimental conditions (4.8 to 45 degrees C and pH 5.5 to 5.9) yielded RI values ranging from 0.11 to 2.99. The estimated overall RI was 1.13. At temperatures between 15 and 40 degrees C, the RI was close to and smaller than 1, indicating that the growth model is relatively robust in that temperature range. However, the RI also was related (P < 0.05) to temperature. By quantifying the predictive accuracy relative to the expected accuracy, the RI could be a useful tool for comparing various models under different conditions.

Animals↗
PubMed2006

Robustness of validation criteria in the College of American Pathologists Interlaboratory Comparison Program in Cervicovaginal Cytology.

CONTEXT: Field validation of slides used in gynecologic cytology proficiency testing has surfaced as an important issue. Although the precision of diagnoses in peer-reviewed educational programs has been examined, the robustness of the validation criteria for specific types of interpretations used in proficiency testing has not been previously studied. OBJECTIVE: To evaluate the robustness of validation criteria for slides entering an educational slide program. DESIGN: We reviewed the results of the College of American Pathologists Interlaboratory Comparison Program in Cervicovaginal Cytology and compared the robustness of validation criteria for different reference diagnoses, using a total of 16,948 circulating slides. RESULTS: Validation criteria could be divided into 2 significantly different groups. The criteria for herpes, Trichomonas, squamous cell carcinoma, and adenocarcinoma were significantly more robust than the diagnoses of unsatisfactory; negative for intraepithelial lesion and malignancy, not otherwise specified; low-grade squamous intraepithelial lesion; and high-grade squamous intraepithelial lesion (P < .001). CONCLUSIONS: The validation criteria used in the College of American Pathologists Interlaboratory Comparison Program in Cervicovaginal Cytology show 2 different levels of robustness or redundancy. These results have implications for the design of fair proficiency tests. Proficiency testing can be designed with the necessary number of reviews needed for slide validation.

Clinical Competence↗
PubMed2005

Robusticity and osteoarthritis at the trapeziometacarpal joint in a Bronze Age population from Tell Abraq, United Arab Emirates.

Osteoarthritis (OA) is a progressive disease of the joints and can cause pain, reduced range of motion and strength, and ultimately loss of function at affected joints. Osteoarthritis often occurs at sites where biomechanical stress is acutely severe or moderate but habitual over the course of a lifetime. Skeletal remains from an Umm an-Nar tomb at Tell Abraq, United Arab Emirates (ca. 2300 BC), were recovered and represented over 300 individuals of all ages. The remains were disarticulated, commingled, and mostly fragmented. An analysis of 650 well-preserved adult metacarpal and carpal bones, from the tomb's western chamber, revealed that over 53% of the trapeziometacarpal joint facets showed signs of OA varying from mild to severe. The first and second metacarpals and trapezium bones were sided and evaluated for OA at the trapeziometacarpal joint articulations. Osteoarthritis was detected on 53% of the first metacarpals, 40% of the second metacarpals, and 57% of the trapezium bones. All specimens appeared enlarged, and the first metacarpals were assessed for sexual identification and robusticity. Eighty-five percent of the bones were probable males, and more than 80% of them had a robusticity index of 60 or higher. A strong correlation was found between OA, sex, and robusticity. High levels of OA and robusticity at the thumb suggest that the people of Tell Abraq were habitually involved in biomechanically challenging work with their hands.

Biomechanical Phenomena↗
PubMed2002

The nature of robustness in development.

A trait is robust to a genetic or environmental variable if its variation is weakly correlated with variation in that variable. The source of robustness lies in the fact that the developmental processes that give rise to complex traits are nonlinear. A consequence of this nonlinearity is that not all genes are equally correlated with the trait whose ontogeny they control. Here we explore how developmental mechanisms determine and alter the correlation structure between genes and the traits that they control. A formula is developed by which the correlation of a gene or environmental variable with a trait can be calculated if the mechanism that gives rise to the trait is known. The nature of robustness and the ways in which robustness can evolve are discussed in the context of the problems that arise in the analysis of inherently nonlinear systems.

Alleles↗
PubMed1998

Registration of MR/MR and MR/SPECT brain images by fast stochastic optimization of robust voxel similarity measures.

This paper describes a robust, fully automated algorithm to register intrasubject 3D single and multimodal images of the human brain. The proposed technique accounts for the major limitations of the existing voxel similarity-based methods: sensitivity of the registration to local minima of the similarity function and inability to cope with gross dissimilarities in the two images to be registered. Local minima are avoided by the implementation of a stochastic iterative optimization technique (fast simulated annealing). In addition, robust estimation is applied to reject outliers in case the images show significant differences (due to lesion evolution, incomplete acquisition, non-Gaussian noise, etc.). In order to evaluate the performance of this technique, 2D and 3D MR and SPECT human brain images were artificially rotated, translated, and corrupted by noise. A test object was acquired under different angles and positions for evaluating the accuracy of the registration. The approach has also been validated on real multiple sclerosis MR images of the same patient taken at different times. Furthermore, robust MR/SPECT image registration has permitted the representation of functional features for patients with partially complex seizures. The fast simulated annealing algorithm combined with robust estimation yields registration errors that are less than 1 degree in rotation and less than 1 voxel in translation (image dimensions of 128(3)). It compares favorably with other standard voxel similarity-based approaches.

Algorithms↗
PubMed2007

Biological robustness in complex host-pathogen systems.

Infectious diseases are still the number one killer of human beings. Even in developed countries, infectious diseases continue to be a major health threat. This article explores a conceptual framework for understanding infectious diseases in the context of the complex dynamics between microbe and host, and explores theoretical strategies for anti-infectives. The central pillar of this conceptual framework is that biological robustness is a fundamental property of systems that is closely interlinked with the evolution of symbiotic host-pathogen systems. There are specific architectural features of such robust yet evolvable systems and interpretable trade-offs between robustness, fragility, resource demands, and performance. This concept applies equally to both microbes and host. Pathogens have evolved to exploit the host using various strategies as well as effective escape mechanisms. Modular pathogenicity islands (PAI) derived from horizontal gene transfer, highly variable surface molecules, and a range of other countermeasures enhance the robustness of a pathogen against attacks from the host immune system. The host has likewise evolved complex defensive mechanisms to protect itself against pathogenic threats, but the host immune system includes several trade-offs that can be exploited by pathogens and induces undesirable inflammatory reactions. Due to the complexity of the dynamics emerging from the interactions of multiple microbes and a host, effective counter-measures require an in-depth understanding of system dynamics as well as detailed molecular mechanisms of the processes that are involved.

Adaptation, Biological↗
PubMed2005

Robust and self-tuning blood flow control during extracorporeal circulation in the presence of system parameter uncertainties.

Three different discrete controllers were designed and tuned to be used in conjunction with a rotary blood pump during cardiopulmonary heart-lung support. The controllers were designed to operate in both steady and pulsatile modes. The system and methods were tested in a circulatory haemodynamic simulator. To guarantee stable control of the non-linear circulatory system in the presence of patient parameter uncertainties, a proportional plus integral (PI) and an H infinity controller were robustly tuned, using a non-linear time-varying model. (H infinity refers to the Hardy space, the set of bounded functions, analytic in the right half plane. The H infinity controller is the solution to the H infinity norm optimisation problem.) A self-tuning general predictive controller (GPC), together with an adaptive Kalman filter (KF) estimator, was compared with the two robustly tuned controllers. The closed-loop blood flow control circuit was set up in simulation routines first. The blood flow controllers were validated in a circulatory hydrodynamic simulator (MOCK) combined with a rotary blood pump. Parameters of the system simulator were changed continuously, and the controllers were tested over a wide range of different operating points. Disturbances in the form of discontinuous additive parameter uncertainties were applied. The closed-loop systems remained robustly stable. The robustly tuned H infinity controller showed the best control performance, in contrast to the GPC controller, which was near instability in regions of strongly varying non-linear system gain. Compared with the H infinity controller, the PI controller showed slightly worse behaviour, but the closed-loop response was acceptable, even in regions of strongly varying non-linear system gain and during pulsatile perfusion. The rotary blood pump could provide stationary and pulsatile perfusion under control conditions. Controlled variables were hereby mean blood flow, pulsatility index and heart rate. All three controllers were developed for an arterial mean flow of 0-6 l min(-1) and a heart rate of up to 70 beats per minute. Pulsatile closed-loop perfusion could provide up to 30 mmHg pressure variation in the simulated ascending aorta at a mean flow of 3 l min(-1).

Aorta↗
PubMed1997

Cell communities and robustness in development.

The robustness of patterning events in development is a key feature that must be accounted for in proposed models of these events. When considering explicitly cellular systems, robustness can be exhibited at different levels of organization. Consideration of two widespread patterning mechanisms suggests that robustness at the level of cell communities can result from variable development at the level of individual cells; models of these mechanisms show how interactions between participating cells guarantee community-level robustness. Cooperative interactions enhance homogeneity within communities of like cells and the sharpness of boundaries between communities of distinct cells, while competitive interactions amplify small inhomogeneities within communities of initially equivalent cells, resulting in fine-grained patterns of cell specialization.

Animals↗
PubMed1996

Hinge estimators of location: robust to asymmetry.

Robust estimators have been developed and tested for symmetric distributions via simulation studies. The primary objective of these robust estimators was to show that these estimators had a higher efficiency than the sample mean over these symmetric distributions. Little attention has been given to how these estimators perform on data that are from asymmetric distributions or from distributions that have inherent anomalies-so called 'messy data'. This study is intended to supplement previous studies by examining the behavior of several robust estimators over asymmetric distributions. The objective is to demonstrate several adaptive 'asymmetric' robust estimators which utilize sample selector statistics to identify the underlying distribution and to demonstrate the efficiency of these adaptive estimators. From a methodology point rather than a theoretical basis, reasonable alternatives should be available. In the asymmetric data distributions faced on a daily basis, estimators that adapt themselves to the data may be formulated and used. We recommend the use of the following algorithm in examining data sets: (a) compute the ancillary statistics-skewness and tail-length to classify the data distribution; (b) analyze each data set using at least one alternative estimator to the usual XM; (c) if the results are similar, report the XM analysis; (d) if the results are dissimilar, report the alternative analysis and the reasons for using the alternative analysis (i.e. t-tests based on a T alpha, HQ1, HQ2, or SK5).

Algorithms↗
PubMed2005

Optimisation and robustness analysis of a hydrophobic interaction chromatography step.

Process development, optimisation and robustness analysis for chromatography separations are often entirely based on experimental work and generic knowledge. The present study proposes a method of gaining process knowledge and assisting in the robustness analysis and optimisation of a hydrophobic interaction chromatography step using a model-based approach. Factorial experimental design is common practice in industry today for robustness analysis. The method presented in this study can be used to find the critical parameter variations and serve as a basis for reducing the experimental work. In addition, the calibrated model obtained with this approach is used to find the optimal operating conditions for the chromatography column. The methodology consists of three consecutive steps. Firstly, screening experiments are performed using a factorial design. Secondly, a kinetic-dispersive model is calibrated using gradient elution and column load experiments. Finally, the model is used to find optimal operating conditions and a robustness analysis is conducted at the optimal point. The process studied in this work is the separation of polyclonal IgG from BSA using hydrophobic interaction chromatography.

Adsorption↗
PubMed2006

Model based robustness analysis of an ion-exchange chromatography step.

Process development, optimization and robustness analysis for chromatographic separation are often entirely based on experimental work and generic knowledge. This paper describes a model-based approach that can be used to gain process knowledge and assist in the robustness analysis of an ion-exchange chromatography step using a model-based approach. A kinetic dispersive model, where the steric mass action model accounts for the adsorption is used to describe column performance. Model calibration is based solely on gradient elution experiments at different gradients, flow rates, pH and column loads. The position and shape of the peaks provide enough information to calibrate the model and thus single-component experiments can be avoided. The model is calibrated to the experiments and the confidence intervals for the estimated parameters are used to account for the model error throughout the analysis. The model is used to predict the result of a robustness analysis conducted as a factorial experiment and to design a robust pooling approach. The confidence intervals are used in a "worst case" approach where the parameters for the components are set at the edge of their confidence intervals to create a worst case for the removal of impurities at each point in the factorial experiment. The pooling limit was changed to ensure product quality at every point in the factorial analysis. The predicted purities and yields were compared to the experimental results to ensure that the prediction intervals cover the experimental results.

Chromatography, Ion Exchange↗
PubMed2006

A robust approach for iterative contaminant source location and release history recovery.

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.

Environmental Restoration and Remediation↗