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Biomedical subjects

R E Kass

Publications and source records attributed to R E Kass.

11 recordsLinked to original sources
PubMed2001

Shrinkage estimators for covariance matrices.

Estimation of covariance matrices in small samples has been studied by many authors. Standard estimators, like the unstructured maximum likelihood estimator (ML) or restricted maximum likelihood (REML) estimator, can be very unstable with the smallest estimated eigenvalues being too small and the largest too big. A standard approach to more stably estimating the matrix in small samples is to compute the ML or REML estimator under some simple structure that involves estimation of fewer parameters, such as compound symmetry or independence. However, these estimators will not be consistent unless the hypothesized structure is correct. If interest focuses on estimation of regression coefficients with correlated (or longitudinal) data, a sandwich estimator of the covariance matrix may be used to provide standard errors for the estimated coefficients that are robust in the sense that they remain consistent under misspecification of the covariance structure. With large matrices, however, the inefficiency of the sandwich estimator becomes worrisome. We consider here two general shrinkage approaches to estimating the covariance matrix and regression coefficients. The first involves shrinking the eigenvalues of the unstructured ML or REML estimator. The second involves shrinking an unstructured estimator toward a structured estimator. For both cases, the data determine the amount of shrinkage. These estimators are consistent and give consistent and asymptotically efficient estimates for regression coefficients. Simulations show the improved operating characteristics of the shrinkage estimators of the covariance matrix and the regression coefficients in finite samples. The final estimator chosen includes a combination of both shrinkage approaches, i.e., shrinking the eigenvalues and then shrinking toward structure. We illustrate our approach on a sleep EEG study that requires estimation of a 24 x 24 covariance matrix and for which inferences on mean parameters critically depend on the covariance estimator chosen. We recommend making inference using a particular shrinkage estimator that provides a reasonable compromise between structured and unstructured estimators.

Analysis of Variance↗
PubMed2001

A spike-train probability model.

Poisson processes usually provide adequate descriptions of the irregularity in neuron spike times after pooling the data across large numbers of trials, as is done in constructing the peristimulus time histogram. When probabilities are needed to describe the behavior of neurons within individual trials, however, Poisson process models are often inadequate. In principle, an explicit formula gives the probability density of a single spike train in great generality, but without additional assumptions, the firing-rate intensity function appearing in that formula cannot be estimated. We propose a simple solution to this problem, which is to assume that the time at which a neuron fires is determined probabilistically by, and only by, two quantities: the experimental clock time and the elapsed time since the previous spike. We show that this model can be fitted with standard methods and software and that it may used successfully to fit neuronal data.

Animals↗
PubMed2000

Nonconjugate Bayesian analysis of variance component models.

We consider the usual normal linear mixed model for variance components from a Bayesian viewpoint. With conjugate priors and balanced data, Gibbs sampling is easy to implement; however, simulating from full conditionals can become difficult for the analysis of unbalanced data with possibly nonconjugate priors, thus leading one to consider alternative Markov chain Monte Carlo schemes. We propose and investigate a method for posterior simulation based on an independence chain. The method is customized to exploit the structure of the variance component model, and it works with arbitrary prior distributions. As a default reference prior, we use a version of Jeffreys' prior based on the integrated (restricted) likelihood. We demonstrate the ease of application and flexibility of this approach in familiar settings involving both balanced and unbalanced data.

Algorithms↗
PubMed2000

Neuronal activity in macaque supplementary eye field during planning of saccades in response to pattern and spatial cues.

The aim of this study was to determine whether neuronal activity in the macaque supplementary eye field (SEF) is influenced by the rule used for saccadic target selection. Two monkeys were trained to perform a variant of the memory-guided saccade task in which any of four visible dots (rightward, upward, leftward, and downward) could be the target. On each trial, the cue identifying the target was either a spot flashed in superimposition on the target (spatial condition) or a foveally presented digitized image associated with the target (pattern condition). Trials conforming to the two conditions were interleaved randomly. On recording from 439 SEF neurons, we found that two aspects of neuronal activity were influenced by the nature of the cue. 1) Activity reflecting the direction of the impending response developed more rapidly following spatial than following pattern cues. 2) Activity throughout the delay period tended to be higher following pattern than following spatial cues. We consider these findings in relation to the possible involvement of the SEF in processes underlying attention, arousal, response-selection, and motor preparation.

Analysis of Variance↗
PubMed1997

Response latency and verbal complexity: stochastic models of individual differences in children with specific language impairments.

Within-subject statistical modeling techniques were employed to investigate individual differences in the extent to which two possible indicators of processing time predicted changes in utterance complexity during spontaneous discourse for 10 children ages 7;1 to 10;1 with specific language impairments (SLI) who differed in receptive language abilities. The two indicators of processing time that were modeled were response latency and the use of a specific discourse marker (Verbal Pause) that provided children with additional time to respond. Longer response latencies were not a strong predictor of increased utterance length for any of the children. However, results indicated that children with better receptive skills used substantially more verbal pauses than children with both expressive and receptive deficits and that the use of these pauses was a strong predictor of increased utterance length for children with better comprehension skills.

Adult↗
PubMed1996

Differential age-related loss of pigmented locus coeruleus neurons in suicides, alcoholics, and alcoholic suicides.

We previously reported fewer locus coeruleus (LC) neurons in both suicide victims and alcoholics than among a group of nonpsychiatric controls. In the present paper we examine the rate of decline in the number of LC neurons with age, looking for possible differential rates among suicide victims, alcoholics, and controls. We also compare these groups with a group of alcoholics who died by suicide, and consider the effects of sex, race, and postmortem interval. LC neuron counts were obtained from a total of 32 subjects. In all groups, the number of neurons decreased with age, but by roughly age 40 the average LC count among the three suicide and/or alcoholic groups was lower than among controls. The rate of LC neuron loss was greater among suicides than among controls, but the rate of loss among alcoholics who were at least 30 years old was the same as that among the controls. Our group of alcoholic suicides had counts that were statistically indistinguishable from those of suicides. Differences among groups appear to be most pronounced in the middle third of the LC. Further studies are needed to determine the mechanisms of noradrenergic neuron loss and whether it is associated with an underlying major depression in suicide victims, or acquired after a period of excessive alcohol consumption.

Adolescent↗
PubMed1989

Family functioning and metabolic control of school-aged children with IDDM.

The relationship of two aspects of family life to metabolic control were examined as part of a longitudinal study of school-aged children with newly diagnosed insulin-dependent diabetes mellitus (IDDM). Glycosylated hemoglobin level was the primary index of metabolic control; weight-adjusted insulin dosage served as an indirect index. Neither the quality of family life nor aspects of the parents' marriage predicted the child's metabolic control over the next 3-4 mo, and they were also unrelated to concurrent weight-adjusted insulin dosage. Longitudinal data spanning a 6-yr period of the child's diabetes also failed to reveal an association between aspects of family life and metabolic control. The significance of the findings are discussed in light of the sample's characteristics and possible methodological constraints.

Adult↗
PubMed1987

Fitting nonlinear models with ARMA errors to biological rhythm data.

Many behavioural and physiological processes are periodic with a period of approximately 24 hours. For descriptive purposes, linear regression using a simple sinusoid with a fixed 24 hour period is sometimes an adequate tool for analysing data from such processes. Inference based on regression models under the assumption of independent and identically distributed errors, however, can often mislead seriously. In this paper we present a general class of models for fitting biological rhythms, with use of higher-order harmonic terms of one or more unknown fundamentals and ARMA processes for the errors. We describe the procedures for model specification and estimation and give the theoretical justification for these procedures. Analysis of a series of human core body temperature illustrates the methodology.

Biometry↗