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Rhemtulla, Mijke; Jia, Fan; Wu, Wei; Little, Todd D. – International Journal of Behavioral Development, 2014
We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…
Descriptors: Data Analysis, Error of Measurement, Models, Longitudinal Studies
Pampaka, Maria; Hutcheson, Graeme; Williams, Julian – International Journal of Research & Method in Education, 2016
Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation
Lucas, Richard E.; Donnellan, M. Brent – Social Indicators Research, 2012
Life satisfaction is often assessed using single-item measures. However, estimating the reliability of these measures can be difficult because internal consistency coefficients cannot be calculated. Existing approaches use longitudinal data to isolate occasion-specific variance from variance that is either completely stable or variance that…
Descriptors: Life Satisfaction, Measurement, Error of Measurement, Reliability
Lin, Johnny Cheng-Han – ProQuest LLC, 2013
Many methods exist for imputing missing data but fewer methods have been proposed to test the missing data mechanism. Little (1988) introduced a multivariate chi-square test for the missing completely at random data mechanism (MCAR) that compares observed means for each pattern with expectation-maximization (EM) estimated means. As an alternative,…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Probability
Hertzog, Christopher; Lindenberger, Ulman; Ghisletta, Paolo; Oertzen, Timo von – Psychological Methods, 2006
We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris…
Descriptors: Multivariate Analysis, Models, Sample Size, Reliability
Millsap, Roger E. – 1986
A component analytic method for analyzing multivariate longitudinal data is presented that does not make strong assumptions about the structure of the data. Central to the method are the facts that components are derived as linear composites of the observed or manifest variables and that the components must provide an adequate representation of…
Descriptors: Comparative Analysis, Computer Software, Cross Sectional Studies, Error of Measurement
Kaufman, Phillip; Bradbury, Denise – National Center for Education Statistics, 1992
The National Education Longitudinal Study of 1988 (NELS:88) is a large-scale, national longitudinal study designed and sponsored by the National Center for Education Statistics (NCES), with support from other government agencies. Beginning in the spring of 1988 with a cohort of eighth graders (25,000) attending public and private schools across…
Descriptors: At Risk Students, Longitudinal Studies, Statistical Analysis, Demography