Estimating and approximating prevalence trends

Estimating the prevalence of breast cancer using a disease model: data problems and trends

BACKGROUND: Health policy and planning depend on quantitative data of disease epidemiology. However, empirical data are often incomplete or are of questionable validity. Disease models describing the relationship between incidence, prevalence and mortality are used to detect data problems or supplement missing data. Because time trends in the data affect their outcome, we compared the extent to...

Optimal causal inference: estimating stored information and approximating causal architecture.

We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences i...

Estimating Prevalence & Costs

Estimating trends in the prevalence of problematic cocaine use (1999-2008).

OBJECTIVE To examine trends in the prevalence of problematic cocaine use in a large city and describe the problems encountered when estimating these trends using capture-recapture techniques based on secondary data METHODS We used clinical data on accident and emergency department episodes at four university hospitals in Barcelona (Spain) between 1999 and 2008 (3 capture periods per year). Us...

Estimating Prevalence from Complex Surveys

iii ACKNOWLEDGEMENTS This project would not have been possible without the support of many people. Many thanks are due to my advisor, Ed J. Stanek III, for his patience and guidance throughout. I would also like to extend my gratitude to the members of my committee, Rachel Volberg and Jing Qian, for their helpful comments and suggestions. Thanks are also due to Martha Zorn for her support in al...