NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 8 results Save | Export
Peer reviewed Peer reviewed
Reinartz, Werner J.; Echambadi, Raj; Cin, Wynne W. – Multivariate Behavioral Research, 2002
Tested empirically the applicability of a method developed by S. Mattson for generating data on latent variables with controlled skewness and kurtosis of the observed variables. Monte Carlo simulation results suggest that Mattson's method appears to be a good approach to generate data with defined levels of skewness and kurtosis. (SLD)
Descriptors: Computer Simulation, Monte Carlo Methods, Structural Equation Models
Peer reviewed Peer reviewed
Direct linkDirect link
Schmitt, J. Eric; Mehta, Paras D.; Aggen, Steven H.; Kubarych, Thomas S.; Neale, Michael C. – Multivariate Behavioral Research, 2006
Ordered latent class analysis (OLCA) can be used to approximate unidimensional latent distributions. The main objective of this study is to evaluate the method of OLCA in detecting non-normality of an unobserved continuous variable (i.e., a common factor) used to explain the covariation between dichotomous item-level responses. Using simulation,…
Descriptors: Probability, Sample Size, Effect Size, Depression (Psychology)
Peer reviewed Peer reviewed
Rasmussen, Jeffrey Lee – Multivariate Behavioral Research, 1988
A Monte Carlo simulation was used to compare the Mahalanobis "D" Squared and the Comrey "Dk" methods of detecting outliers in data sets. Under the conditions investigated, the "D" Squared technique was preferable as an outlier removal statistic. (SLD)
Descriptors: Comparative Analysis, Computer Simulation, Data Analysis, Monte Carlo Methods
Peer reviewed Peer reviewed
Harrop, John W.; Velicer, Wayne F. – Multivariate Behavioral Research, 1985
Computer generated data representative of 16 Auto Regressive Integrated Moving Averages (ARIMA) models were used to compare the results of interrupted time-series analysis using: (1) the known model identification, (2) an assumed (l,0,0) model, and (3) an assumed (3,0,0) model as an approximation to the General Transformation approach. (Author/BW)
Descriptors: Computer Simulation, Data Analysis, Mathematical Models, Matrices
Peer reviewed Peer reviewed
Cohen, Jacob; Nee, John C. M. – Multivariate Behavioral Research, 1990
The analysis of contingency tables via set correlation allows the assessment of subhypotheses involving contrast functions of the categories of the nominal scales. The robustness of such methods with regard to Type I error and statistical power was studied via a Monte Carlo experiment. (TJH)
Descriptors: Computer Simulation, Monte Carlo Methods, Multivariate Analysis, Power (Statistics)
Peer reviewed Peer reviewed
Kaplan, David – Multivariate Behavioral Research, 1988
The impact of misspecification on the estimation, testing, and improvement of structural equation models was assessed via a population study in which a prototypical latent variable model was misspecified. Results provide insights into the maximum likelihood estimator versus a limited two-stage least squares estimator in LISREL. (TJH)
Descriptors: Computer Simulation, Computer Software, Demography, Error of Measurement
Peer reviewed Peer reviewed
Kuusinen, Jorma; Leskinen, Esko – Multivariate Behavioral Research, 1988
Covariance structure modeling by LISREL was used in an analysis of relations between intellectual ability, as measured by the Finnish version of the Illinois Test of Psycholinguistic Abilities (ITPA), and achievement in reading, writing, foreign language, and mathematics in longitudinal data on 234 Finnish school children. The validity of the ITPA…
Descriptors: Academic Achievement, Computer Simulation, Computer Software, Intelligence Tests
Peer reviewed Peer reviewed
Farley, John U.; Reddy, Srinivas K. – Multivariate Behavioral Research, 1987
In an experiment manipulating artificial data in a factorial design, model misspecification and varying levels of error in measurement and in model structure are shown to have significant effects on LISREL parameter estimates in a modified peer influence model. (Author/LMO)
Descriptors: Analysis of Variance, Computer Simulation, Error of Measurement, Estimation (Mathematics)