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.

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