Director: Miguel A. Padilla, Ph.D.
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.
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
This project examines the potential for missing data methodology in providing solutions to admixture measurement error in genetic association studies.
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