A Technical Guide to C-SIDE (Software for Intake Distribution Estimation). Dietary Assessment Research Series Report 9

The computer software package C-SIDE estimates usual intake distributions for nutrients and foods using statistical methodology developed at lows State University. An accompanying user\u27s guide explains how to use C-SIDE to obtain estimates of usual intake distributions. This technical manual provides a detailed description of the statistical methodology itself, and is the first document to fully describe every step of the method

Combining Information from Two Surveys to Estimate County-Level Prevalence Rates of Cancer Risk Factors and Screening

Cancer surveillance requires estimates of the prevalence of cancer risk factors and screening for small areas such as counties. Two popular data sources are the Behavioral Risk Factor Surveillance System (BRFSS), a telephone survey conducted by state agencies, and the National Health Interview Survey (NHIS), an area probability sample survey conducted through face-to-face interviews. Both data sources have advantages and disadvantages. The BRFSS is a larger survey, and almost every county is included in the survey; but it has lower response rates as is typical with telephone surveys, and it does not include subjects who live in households with no telephones. On the other hand, the NHIS is a smaller survey, with the majority of counties not included; but it includes both telephone and non-telephone households and has higher response rates. A preliminary analysis shows that the distributions of cancer screening and risk factors are different for telephone and non-telephone households. Thus, information from the two surveys may be combined to address both nonresponse and noncoverage errors. A hierarchical Bayesian approach that combines information from both surveys is used to construct county-level estimates. The proposed model incorporates potential noncoverage and nonresponse biases in the BRFSS as well as complex sample design features of both surveys. A Markov Chain Monte Carlo method is used to simulate draws from the joint posterior distribution of unknown quantities in the model based on the design-based direct estimates and county-level covariates. Yearly prevalence estimates at the county level for 49 states, as well as for the entire state of Alaska and the District of Columbia, are developed for six outcomes using BRFSS and NHIS data from the years 1997-2000. The outcomes include smoking and use of common cancer screening procedures. The NHIS/BRFSS combined county-level estimates are substantially different from those based on BRFSS alone

The political left rolls with the good and the political right confronts the bad: connecting physiology and cognition to preferences

We report evidence that individual-level variation in people’s physiological and attentional responses to aversive and appetitive stimuli are correlated with broad political orientations. Specifically, we find that greater orientation to aversive stimuli tends to be associated with right-of-centre and greater orientation to appetitive (pleasing) stimuli with left-of-centre political inclinations. These findings are consistent with recent evidence that political views are connected to physiological predispositions but are unique in incorporating findings on variation in directed attention that make it possible to understand additional aspects of the link between the physiological and the political

The Political Left Rolls with the Good; The Political Right Confronts the Bad: Physiology and Cognition in Politics

We report evidence that individual-level variation in people\u27s physiological and attentional responses to aversive and appetitive stimuli are correlated with broad political orientations. Specifically, we find that greater orientation to aversive stimuli tends to be associated with right-of-centre and greater orientation to appetitive (pleasing) stimuli with left-of-centre political inclinations. These findings are consistent with recent evidence that political views are connected to physiological predispositions but are unique in incorporating findings on variation in directed attention that make it possible to understand additional aspects of the link between the physiological and the political

The political left rolls with the good and the political right confronts the bad: connecting physiology and cognition to preferences

We report evidence that individual-level variation in people’s physiological and attentional responses to aversive and appetitive stimuli are correlated with broad political orientations. Specifically, we find that greater orientation to aversive stimuli tends to be associated with right-of-centre and greater orientation to appetitive (pleasing) stimuli with left-of-centre political inclinations. These findings are consistent with recent evidence that political views are connected to physiological predispositions but are unique in incorporating findings on variation in directed attention that make it possible to understand additional aspects of the link between the physiological and the political

A new multivariate measurement error model with zero-inflated dietary data, and its application to dietary assessment

In the United States the preferred method of obtaining dietary intake data is the 24-hour dietary recall, yet the measure of most interest is usual or long-term average daily intake, which is impossible to measure. Thus, usual dietary intake is assessed with considerable measurement error. Also, diet represents numerous foods, nutrients and other components, each of which have distinctive attributes. Sometimes, it is useful to examine intake of these components separately, but increasingly nutritionists are interested in exploring them collectively to capture overall dietary patterns. Consumption of these components varies widely: some are consumed daily by almost everyone on every day, while others are episodically consumed so that 24-hour recall data are zero-inflated. In addition, they are often correlated with each other. Finally, it is often preferable to analyze the amount of a dietary component relative to the amount of energy (calories) in a diet because dietary recommendations often vary with energy level. The quest to understand overall dietary patterns of usual intake has to this point reached a standstill. There are no statistical methods or models available to model such complex multivariate data with its measurement error and zero inflation. This paper proposes the first such model, and it proposes the first workable solution to fit such a model. After describing the model, we use survey-weighted MCMC computations to fit the model, with uncertainty estimation coming from balanced repeated replication.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS446 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org