Myron Katzoff

Reliability and Prevalence of Physical Performance Examination Assessing Mobility and Balance in Older Persons in the US: Data from the Third National Health and Nutrition Examination Survey

OBJECTIVE: This report provides reliability and prevalence estimates by sex, age, and race/ethnicity of an observed physical performance examination (PPE) assessing mobility and balance.

Out-of-Sample Fusion in Risk Prediction

The probability that mortality from certain causes exceeds high thresholds is addressed. An out-of-sample fusion method is presented where an original real data sample is fused or combined with independent computer-generated samples in the estimation of exceedance probabilities assuming a density ratio model. Since the size of the combined sample of real and artificial data is larger than that of the real sample, the fused sample produces short confidence intervals relative to traditional methods. Numerical results show that the method maintains good coverage even for some misspecified cases.

Bayesian inference for a stratified categorical variable allowing all possible category choices

In many sample surveys, there are items that require respondents to make at least one choice. For example, in the Kansas Farm Survey (conducted by the Department of Animal Sciences at Kansas State University), livestock farmers in Kansas were asked ‘What are your primary sources of veterinary information?’. According to the level of education, the sources are professional consultant, veterinarian, state or local extension service, magazines, and feed companies and representatives, and the farmers were allowed to pick as many sources that apply. We assume that each farmer made all his/her choices (i.e., there are no nonrespondents) and the number of farmers with none of these choices is unknown. The proportions of individuals with each of the choices are of interest because these proportions can give information about which source is mostly used by the farmers. However, the analyses of such survey data are complex because an individual is allowed to make at least one choice, the number of individuals with none of these choices is unknown or not reported, and the categorical table with mutually exclusive categories can be sparse. We use a simple Bayesian product multinomial-Dirichlet model to fit the count data both within and across education levels. We estimate the proportions of individuals with each choice, show how to select the best choice, and show using the Bayes factor how to test that these proportions are the same over different levels of farmers’ education. Our Bayesian procedure is simple, and essentially uses a sampling based method with independent samples, not dependent samples as in a Markov chain.

Approaches to Modeling the Concentration Field for Adaptive Sampling of Contaminants during Site Decontamination

1 National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, WSieber@cdc.gov 2 National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, JBennett@cdc.gov 3 National Center for Health Statistics, Centers for Disease Control and Prevention, AWouhib@cdc.gov 4 National Center for Health Statistics, Centers for Disease Control and Prevention, JGonzalez@cdc.gov 5 National Center for Health Statistics, Centers for Disease Control and Prevention, MKatzoff@cdc.gov 6 National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, SShulman@cdc.gov

Coherence Structure and Its Application in Mortality Forecasting

Interaction terms expressed as products of covariates may prove useful in regression problems. A graphical method is presented for identifying potentially useful interaction and related covariates in modeling mortality time series using lagged coherence, a nonlinear extension of the squared coherence, and its residual coherence offshoot. The identified covariates are tested for their significance within a regression model using quasi-likelihood and log link.