Quantitative Projects
Bootstrap for the Correlation Coefficient
Investigators: Padilla, De Los Reyes
The project examines the applicability of bootstrap methods for estimating confidence intervals for the mutagenic distribution of the correlation coefficient.
Bootstrap Reliability
Investigators: Padilla
This project examines the use of Bootstrap methods for developing reliability estimates for measurement instruments (personality inventories, assessments, etc.) in the social/behavioral sciences.
Bootstrap Correction for Attenuation
Investigators: Padilla, Veprinsky
This project investigates the applicability of bootstrap methods to correcting correlation attenuation caused by measurement error.
Measurement Error Correction in Linear Models
Investigators: Padilla, Chaganty
This project examines the use of missing data methodology in correcting data with measurement in statistical linear models.
Measurement Error Correction in Genetic Association Studies
Investigators: Padilla
This project examines the potential for missing data methodology in providing solutions to admixture measurement error in genetic association studies.