Adjusting Self-Reported Attitudinal Data for Mischievous Respondents

Self-adjusting Data Structures for External Memory String Access

A Self-adjusting Indexing Structure for Spatial Data

This paper introduces a spatial indexing structure that adjusts itself so as to provide faster access to spatially referenced data most in demand. The structure is a hybrid of a splay tree and a quadtree. The quadtree is a well-known spatial data structure that successively segments a spatial data area into quadrants, preserving the spatial arrangement of the data. Access to data is based on a ...

A Self-adjusting Data Structure for Multidimensional Point Sets

A data structure is said to be self-adjusting if it dynamically reorganizes itself to adapt to the pattern of accesses. Efficiency is typically measured in terms of amortized complexity, that is, the average running time of an access over an arbitrary sequence of accesses. The best known example of such a data structure is Sleator and Tarjan’s splay tree. In this paper, we introduce a self-adju...

Consistency and Recanting of Ever-Smoking Status Reported by Self and Proxy Respondents One Year Apart.

The study examined consistency of reports concerning current and prior smoking behaviors. Data came from the 2002-2003 Tobacco Use Supplement to the Current Population Survey, where the current smoking behaviors and smoking history were reported by self- and proxy-respondents on two occasions, one year apart. The ever-smoking status is reported consistently, overall: Kappa coefficient is 0.78 w...

Adjusting the obesity thresholds for self-reported BMI in Ireland: a cross-sectional analysis

OBJECTIVE To investigate the optimal adjustment to be made to obesity thresholds when using self-reported body mass index (BMI). DESIGN A cross-sectional study. SETTING Data from the Survey of Lifestyle, Attitudes and Nutrition in Ireland, a nationally representative dataset using the Geodirectory (a listing of all residential addresses in Ireland compiled by the postal service) as the samp...