Measurement of latent constructs is one of the most challenging tasks in psychological research. Unlike physical variables, latent constructs are not directly observable but are inferred through individuals' responses to a set of items often referred to as measurement instruments, tests, surveys, or assessments. For decades, exploratory factor analysis (EFA) has remained a first-choice statistical tool for many researchers when measuring latent constructs. Despite its popularity, EFA fails to produce results that are replicable. An alternative but less popular model is the Rasch model which creates interval-level measurements from categorical data by relating respondents' abilities or trait levels to item difficulties. This study assessed the precision and stability of EFA and Rasch models in the measurement of latent constructs. Four measurement instruments were employed to collect data from 631 college students in the United States. EFA and Rasch analyses were conducted with different sample sizes, racial groups, and genders. Results from the empirical analyses did not support EFA assumption of equal intervals. Additionally, different EFA procedures produced different results. Also, item difficulties influenced the extraction of latent factors in EFA. While EFA failed to produce consistent results under different conditions, Rasch model produced stable results across different sample sizes, racial groups, and genders. Given the shortfalls of EFA, the Rasch model should be considered for the development and validation of measurement instruments as well as the creation of interval-level data for parametric statistical analyses. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]