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Raykov, Tenko; Marcoulides, George A.; Li, Tenglong – Educational and Psychological Measurement, 2018
This note extends the results in the 2016 article by Raykov, Marcoulides, and Li to the case of correlated errors in a set of observed measures subjected to principal component analysis. It is shown that when at least two measures are fallible, the probability is zero for any principal component--and in particular for the first principal…
Descriptors: Factor Analysis, Error of Measurement, Correlation, Reliability
Greifer, Noah – ProQuest LLC, 2018
There has been some research in the use of propensity scores in the context of measurement error in the confounding variables; one recommended method is to generate estimates of the mis-measured covariate using a latent variable model, and to use those estimates (i.e., factor scores) in place of the covariate. I describe a simulation study…
Descriptors: Evaluation Methods, Probability, Scores, Statistical Analysis
Sekercioglu, Güçlü – International Online Journal of Education and Teaching, 2018
An empirical evidence for independent samples of a population regarding measurement invariance implies that factor structure of a measurement tool is equal across these samples; in other words, it measures the intended psychological trait within the same structure. In this case, the evidence of construct validity would be strengthened within the…
Descriptors: Factor Analysis, Error of Measurement, Factor Structure, Construct Validity
Mashiku, Alinda K. – ProQuest LLC, 2013
The current Situational Space Awareness (SSA) is faced with a huge task of tracking the increasing number of space objects. The tracking of space objects requires frequent and accurate monitoring for orbit maintenance and collision avoidance using methods for statistical orbit determination. Statistical orbit determination enables us to obtain…
Descriptors: Statistical Analysis, Space Sciences, Probability, Prediction
Lee, Sik-Yum; Song, Xin-Yuan; Lu, Bin – Multivariate Behavioral Research, 2007
This article proposes an intuitive approach for predictive discriminant analysis with mixed continuous, dichotomous, and ordered categorical variables that are defined via an underlying multivariate normal distribution with a threshold specification. The classification rule is based on the comparison of the observed data logarithm probability…
Descriptors: Factor Analysis, Discriminant Analysis, Probability, Monte Carlo Methods
Chan, Y. C.; Lam, Gladys L. T.; Chun, P. K. R.; So, Moon Tong Ernest – Child Abuse & Neglect: The International Journal, 2006
Objectives: To evaluate whether or not the original six-factor structure of the Child Abuse Potential (CAP) Inventory suggested by [Milner, J. S. (1986). "The Child Abuse Potential Inventory: Manual" (2nd ed.). DeKalb, IL: Psytec. Inc.] can be confirmed with data from a group of Chinese mothers in Hong Kong. Method: Eight hundred and…
Descriptors: Measures (Individuals), Factor Structure, Child Abuse, Mothers
Sterba, Sonya; Egger, Helen L.; Angold, Adrian – Journal of Child Psychology and Psychiatry, 2007
Background: The appropriateness of the "Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition" (DSM-IV) nosology for classifying preschool mental health disturbances continues to be debated. To inform this debate, we investigate whether preschool psychopathology shows differentiation along diagnostically specific lines…
Descriptors: Check Lists, Hyperactivity, Construct Validity, Psychopathology