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At least 775 records · Page 43Linked to original sources
PubMed1993

Expected social utility of life time in the presence of a chronic disease.

Interventive action aimed at reducing the incidence of an irreversible chronic noncommunicable disease in a population has various effects. Hopefully, it increases total longevity in the population and it causes the disease to develop later in time in a smaller portion of the population. In this paper a statistical model is built by which these effects can be estimated. A three dimensional probability density function that underlies this model is changed by the interventive action. It is shown how a three dimensional utility function can be defined to appropriately judge this change.

Cardiovascular Diseases↗
PubMed2002

Estimating degradation in real time and accelerated stability tests with random lot-to-lot variation: a simulation study.

The effect of different lot-to-lot variability levels on the prediction of stability are studied based on two statistical models for estimating degradation in real time and accelerated stability tests. Lot-to-lot variability is considered as random in both models, and is attributed to two sources-variability at time zero, and variability of degradation rate. Real-time stability tests are modeled as a function of time while accelerated stability tests as a function of time and temperatures. Several data sets were simulated, and a maximum likelihood approach was used for estimation. The 95% confidence intervals for the degradation rate depend on the amount of lot-to-lot variability. When lot-to-lot degradation rate variability is relatively large (CV > or = 8%) the estimated confidence intervals do not represent the trend for individual lots. In such cases it is recommended to analyze each lot individually.

Algorithms↗
PubMed1995

Real-time functional magnetic resonance imaging.

A recursive algorithm suitable for functional magnetic resonance imaging (FMRI) calculations is presented. The correlation coefficient of a time course of images with a reference time series, with the mean and any linear trend projected out, may be computed with 22 operations per voxel, per image; the storage overhead is four numbers per voxel. A statistical model for the FMRI signal is presented, and thresholds for the correlation coefficient are derived from it. Selected images from the first real-time functional neuroimaging experiment (at 3 Tesla) are presented. Using a 50-MHz workstation equipped with a 14-bit analog-to-digital converter, each echo planar image was acquired, reconstructed, correlated, thresholded, and displayed in pseudocolor (highlighting active regions in the brain) within 500 ms of the RF pulse.

Algorithms↗
PubMed1997

Estimating test-retest reliability in functional MR imaging. II: Application to motor and cognitive activation studies.

Functional magnetic resonance imaging (fMRI) using blood oxygenation contrast has rapidly spread into many application areas. In this paper, a new statistical model is used to evaluate the reliability of fMRI activation in a finger opposition motor paradigm for both within-session and between-session data and in a working memory paradigm for between-session data. A slice prescription procedure for between-session reproducibility is introduced. Estimates are made for the probabilities of correctly and falsely classifying voxels as active or inactive and receiver operator characteristic curves are generated. In the motor paradigm, estimated between-session reliability was found to be somewhat reduced relative to within-session reliability; however, this includes additional sources of variation and may not reflect intrinsically lower reliability. After matching false-positive classification probabilities, between-session reliability was found to be nearly identical for both motor and cognitive activation paradigms.

Brain↗
PubMed2005

Cross-subject comparison of principal diffusion direction maps.

Diffusion tensor imaging (DTI) data differ fundamentally from most brain imaging data in that values at each voxel are not scalars but 3 x 3 positive definite matrices also called diffusion tensors. Frequently, investigators simplify the data analysis by reducing the tensor to a scalar, such as fractional anisotropy (FA). New statistical methods are needed for analyzing vector and tensor valued imaging data. A statistical model is proposed for the principal eigenvector of the diffusion tensor based on the bipolar Watson distribution. Methods are presented for computing mean direction and dispersion of a sample of directions and for testing whether two samples of directions (e.g., same voxel across two groups of subjects) have the same mean. False discovery rate theory is used to identify voxels for which the two-sample test is significant. These methods are illustrated in a DTI data set collected to study reading ability. It is shown that comparison of directions reveals differences in gross anatomic structure that are invisible to FA.

Algorithms↗
PubMed2004

A computational method for assessing peptide- identification reliability in tandem mass spectrometry analysis with SEQUEST.

High-throughput protein identification in mass spectrometry is predominantly achieved by first identifying tryptic peptides by a database search and then by combining the peptide hits for protein identification. One of the popular tools used for the database search is SEQUEST. Peptide identification is carried out by selecting SEQUEST hits above a specified threshold, the value of which is typically chosen empirically in an attempt to separate true identifications from false ones. These SEQUEST scores are not normalized with respect to the composition, length and other parameters of the peptides. Furthermore, there is no rigorous reliability estimate assigned to the protein identifications derived from these scores. Hence, the interpretation of SEQUEST hits generally requires human involvement, making it difficult to scale up the identification process for genome-scale applications. To overcome these limitations, we have developed a method, which combines a neural network and a statistical model, for normalizing SEQUEST scores, and also for providing a reliability estimate for each SEQUEST hit. This method improves the sensitivity and specificity of peptide identification compared to the standard filtering procedure used in the SEQUEST package, and provides a basis for estimating the reliability of protein identifications.

Algorithms↗
PubMed2003

Regression analysis of incomplete medical cost data.

The accumulation of medical cost over time for each subject is an increasing stochastic process defined up to the instant of death. The stochastic structure of this process is complex. In most applications, the process can only be observed at a limited number of time points. Furthermore, the process is subject to right censoring so that it is unobservable after the censoring time. These special features of the medical cost data, especially the presence of death and censoring, pose major challenges in the construction of plausible statistical models and the development of the corresponding inference procedures. In this paper, we propose several classes of regression models which formulate the effects of possibly time-dependent covariates on the marginal mean of cost accumulation in the presence of death or on the conditional means of cost accumulation given specific survival patterns. We then develop estimating equations for these models by combining the approach of generalized estimating equations for longitudinal data with the inverse probability of censoring weighting technique. The resultant estimators are shown to be consistent and asymptotically normal with simple variance estimators. Simulation studies indicate that the proposed inference procedures behave well in practical situations. An application to data taken from a large cancer study reveals that the Medicare enrollees who are diagnosed with less aggressive ovarian cancer tend to accumulate medical cost at lower rates than those with more aggressive disease, but tend to have higher lifetime costs because they live longer.

Aged↗
PubMed2003

Quality control and the identification of vaccine responders using ELISA-derived antibody data.

First vaccines are traditionally licensed after showing favourable results from phase III efficacy trials. Subsequent competing vaccines, however, have been licensed primarily on the basis of immunogenicity data rather than clinical efficacy. Focusing on pneumococcal vaccines where optical densities are measured and serum antibody concentrations are 'estimated' (from a statistical model) using an immunoglobulin (IgG) enzyme-linked immunosorbent assay (ELISA), the focus of this paper will centre on two highly related issues: the determination of an upper limit for quality control used in the assay methodology (let us call it the maximum tolerated limit or MTL) and the identification of vaccine responders. The goal is to show that these two issues are inter-related, so that investigators could reduce misclassification which would interfere with the eventual comparison of immunogenicity results.

Antibodies, Bacterial↗
PubMed2003

A competing-risks nomogram for sarcoma-specific death following local recurrence.

The majority of staging systems focus on the definition of stage, and, therefore, prediction of prognosis. In the current era of clinical trial research, it has become apparent that the clinical stage alone is not sufficient to assess patient risk of treatment failure. As the number of biological markers increases, our ability to partition the traditional disease classification system improves, and our ability to predict patient success continues to increase. One approach to quantifying individual patient risk is through the nomogram. Nomograms are graphical representations of statistical models, which provide the probability of treatment outcome based on patient-specific covariates. We will focus on the use of the nomogram when the response variable is time to failure and there are multiple, possibly dependent, competing causes of failure. In this setting, estimation of the failure probability through direct application of the Cox proportional hazards model provides the probability of failure (for example, death from cancer) assuming failure from a dependent competing cause will not occur. In many clinical settings this is an unrealistic assumption. The purpose of this study is to illustrate the use of the conditional cumulative incidence function for providing a patient-specific prediction of the probability of failure in the setting of competing risks. A competing risks nomogram is produced to estimate the probability of death due to sarcoma for patients who have already developed a local recurrence of their initially treated soft-tissue sarcoma.

Adolescent↗
PubMed2006

A framework to monitor environment-induced major genes for developmental trajectories: implication for a prenatal cocaine exposure study.

Whether there are specific genes involved in response to different environmental agents and how such genes regulate developmental trajectories during lifetime are of fundamental importance in health, clinical and pharmaceutical research. In this article, we present a novel statistical model for monitoring environment-induced genes of major effects on longitudinal outcomes of a trait. This model is derived within the maximum likelihood framework, incorporated by mathematical aspects of growth and developmental processes. A typical structural model is implemented to approximate time-dependent covariance matrices for the longitudinal trait. This model allows for a number of biologically meaningful hypothesis tests regarding the effects of major genes on overall growth trajectories or particular stages of development. It can be used to test whether and how major genetic effects are expressed differently under altered environmental agents. In a well-designed case-control study, our model has been employed to detect cocaine-dependent genes that affect growth trajectories for head circumference during childhood. The detected gene triggers significant effects on growth curves in both cocaine-exposed (case) and unexposed groups (control), but with different extents. Significant genotype-environment interactions due to this so-called environment-sensitive gene are promising for further studies toward its genomic mapping using polymorphic molecular markers.

Adult↗
PubMed1989

Cholesterol-based personal risk assessment in coronary heart disease.

Using data from the National Health and Nutrition Examination Survey (NHANES II) 1976-1980, we demonstrate how cross-sectional total serum cholesterol surveillance data can be used by an individual to assess current and future personal cholesterol risk status. We propose statistical models, based on a person's current measured cholesterol level and the relationship between cross-sectional age and cholesterol percentile estimates, that will allow prediction of future cholesterol levels or the age at which specified cholesterol risk levels will be reached if no cholesterol-altering intervention is taken. These models incorporate the observed variation in the NHANES II data and expected intraperson biological variation and intralaboratory analytical variation. We illustrate the adequacy of the models using data from the longitudinal Framingham Study.

Adult↗
PubMed1990

Randomized consent designs for clinical trials: an update.

Randomized consent designs were introduced to make it easier for physicians to enter patients in randomized clinical trials. Physician reluctance to participate in randomized clinical trials is often a reflection that the physician-patient relationship could be compromised if the physician makes known to the patient his/her inability to select a preferred therapy. Clinical trials having a no-treatment control or placebo amplify this concern. This paper reviews the main ideas of randomized consent designs (single and double) and the statistical model underlying the analysis, and presents some recent experiences.

Informed Consent↗
PubMed1990

Estimation of parasitic infection dynamics when detectability is imperfect.

The simultaneous estimation of infection rate, cure rate and detectability of parasitic infections is considered. A new method for this estimation based on a simple statistical model assuming constant transition rates between parasite states is proposed. Repeated observations on the infection status of the same individuals is required for this method. A maximum likelihood approach is used for parameter estimation and the calculation of standard errors of the estimates. The method is illustrated by a longitudinal study of the presence of Giardia lamblia infection in Kenyan children.

Feces↗
PubMed1993

The design of observer agreement studies with binary assessments.

We discuss the design of observer agreement studies with binary assessments, with particular emphasis on the need for adequate sample size and the use of replicate observations. First, we present a method and tables for determining the sample size required for ensuring a desired precision for the estimate of the probability of disagreement between two observers. Second, for studies including replicate observations, we present a statistical model that allows estimation of the magnitude of within- and between-observer variation. We then derive sample sizes guaranteeing a specified precision for these estimates, present tables of these sample sizes and give examples of their use.

Confidence Intervals↗
PubMedDate not supplied

A method for evaluating needle exchange programmes.

This paper details a statistical method for evaluating needle exchange programmes. The approach relies only on needle exchange operations data and the results of HIV tests conducted on needles. We develop statistical models describing the needle infection process and how needle exchange interrupts this process. The method is illustrated using 20 months of data collected in conjunction with the evaluation of New Haven, Connecticut's needle exchange programme, and the results suggest that needle-borne HIV transmission among participating clients has been reduced by at least 33 per cent.

Connecticut↗
PubMed1993

Risk assessment in immunotoxicology. II. Relationships between immune and host resistance tests.

We have reported on the design and content of a screening battery using a "tier" approach for detecting potential immunotoxic compounds in mice (Luster et al., Fundam. Appl. Toxicol., 10, 2-19, 1988). The data base generated from these studies, which consists of over 50 selected compounds, has been collected and analyzed in an attempt to improve future testing strategies and provide information to aid in developing future quantitative risk assessment for immunotoxicity. In a recent study it was shown that as few as two or three immune parameters were needed to predict immunotoxicants in mice (Luster et al., Fundam. Appl. Toxicol., 18, 200-210, 1992). In particular, enumeration of lymphocyte populations and quantitation of the T-dependent antibody response were particularly beneficial. Furthermore, commonly employed apical measures (e.g., leukocyte counts, lymphoid organ weights) were fairly insensitive. The present analyses focus on the use of this data base to develop statistical models that examine the qualitative and quantitative relationship(s) between the immune function and host resistance tests. The conclusion derived from these analyses are: (1) A good correlation exists between changes in the immune tests and altered host resistance in that there were no instances where host resistance was altered without affecting an immune test(s). However, in some instances immune changes occurred without corresponding changes in host resistance. (2) No single immune test could be identified which was fully predictive for altered host resistance, although most assays were relatively good indicators (i.e., > 70%). Several others, such as proliferative response to lipopolysaccharide and leukocyte counts, were found to be relatively poor indicators for host resistance changes. (3) The ability to resist infectious agent challenge is dependent upon the degrees of immunosuppression and the quantity of infectious agent administered. (4) Logistic and standard regression modeling using one extensive chemical data set from the immunosuppressive agent, cyclophosphamide, indicated that most immune function-host resistance relationships followed linear rather than linear-quadratic (threshold-like) models. For most of the relationships this could not be confirmed using a large chemical data set and, thus, a more mechanistically based approach for modeling will need to be developed. (5) Using this limited data set, methods were developed for modeling the precise quantitative relationships between changes in selected immune tests and host resistance tests.

Animals↗
PubMed1999

The critical relationship between the timing of stimulus presentation and data acquisition in blocked designs with fMRI.

This paper concerns the experimental design and statistical models employed by fMRI activation studies which block presentation of linguistic stimuli. In particular, we note that the relationship between the timing of stimulus presentation and data acquisition can have a substantial impact on the ability to detect activations in critical language areas, even when the stimuli are presented in blocks. Using a blocked word rhyming paradigm and repeated investigations on a single subject, activation was observed in Broca's area (left inferior frontal cortex) and Wernicke's area (left posterior temporoparietal cortex) when (i) the timing of data acquisition was distributed throughout the peristimulus time and (ii) an event-related analysis was used to model the phasic nature of the hemodynamic response within each block of repeated word stimuli. In contrast, when the timing of data acquisition relative to stimulus presentation was fixed, activation was detected in Broca's area but not consistently in Wernicke's area. Our results indicate that phasic responses to stimuli occur even in a blocked design and that the sampling and proper modeling of these responses can have profound effects on their detection. Specifically, distributed sampling over peristimulus time is essential in order to detect small activations particularly when they are transient. These findings are likely to generalize to the detection of transient signals in any cognitive paradigm.

Brain Mapping↗