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Huang, Po-Hsien; Weng, Li-Jen – Multivariate Behavioral Research, 2012
A procedure for estimating the reliability of test scores in the context of ecological momentary assessment (EMA) was proposed to take into account the characteristics of EMA measures. Two commonly used test scores in EMA were considered: the aggregated score (AGGS) and the within-person centered score (WPCS). Conceptually, AGGS and WPCS represent…
Descriptors: Reliability, Scores, Correlation, Computation
Ferrari, Pier Alda; Barbiero, Alessandro – Multivariate Behavioral Research, 2012
The increasing use of ordinal variables in different fields has led to the introduction of new statistical methods for their analysis. The performance of these methods needs to be investigated under a number of experimental conditions. Procedures to simulate from ordinal variables are then required. In this article, we deal with simulation from…
Descriptors: Data, Statistical Analysis, Sampling, Simulation
Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W. – Multivariate Behavioral Research, 2010
Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…
Descriptors: Models, Graphs, Factor Analysis, Correlation
Deboeck, Pascal R. – Multivariate Behavioral Research, 2010
The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common…
Descriptors: Computation, Calculus, Statistical Analysis, Statistical Bias
Malone, Patrick S.; Lamis, Dorian A.; Masyn, Katherine E.; Northrup, Thomas F. – Multivariate Behavioral Research, 2010
The gateway drug model is a popular conceptualization of a progression most substance users are hypothesized to follow as they try different legal and illegal drugs. Most forms of the gateway hypothesis are that "softer" drugs lead to "harder," illicit drugs. However, the gateway hypothesis has been notably difficult to…
Descriptors: Drug Use, Models, Statistical Analysis, Computer Software
Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient
Krishnamoorthy, K.; Xia, Yanping – Multivariate Behavioral Research, 2008
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
Descriptors: Statistical Analysis, Intervals, Sample Size, Testing
Peer reviewedTakane, Yoshio; Hwang, Heungsun – Multivariate Behavioral Research, 2002
Proposes a method for generalized constrained canonical correlation analysis (GCCANO) that incorporates external information on both rows and columns of data matrices. In this method, each set of variables is first decomposed into the sum of several submatrices according to the external information, and then canonical correlation analysis is…
Descriptors: Correlation, Matrices, Statistical Analysis
Peer reviewedJoe, George W.; Woodward, J. Arthur – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Matrices, Sampling, Statistical Analysis
Peer reviewedCliff, Norman – Multivariate Behavioral Research, 1996
It is argued that ordinal statistical methods are often more appropriate than their more common counterparts because conclusions will be unaffected by monotonic transformation of the variables; they are more statistically robust when used appropriately; and they often correspond more closely to the researcher's goals. (SLD)
Descriptors: Correlation, Research Design, Statistical Analysis, Transformations (Mathematics)
Peer reviewedHumphreys, Lloyd G.; Montanelli, Richard G. – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Factor Analysis, Matrices, Sampling
Peer reviewedHall, Charles E. – Multivariate Behavioral Research, 1974
Descriptors: Analysis of Variance, Comparative Analysis, Correlation, History
Peer reviewedCramer, Elliot M. – Multivariate Behavioral Research, 1974
Descriptors: Correlation, Multiple Regression Analysis, Predictor Variables, Statistical Analysis
Peer reviewedMendoza, Jorge L.; And Others – Multivariate Behavioral Research, 1978
Four testing procedures for establishing the number of non-zero population roots in canonical analysis are investigated. Results of a Monte Carlo study indicate that three well-established procedures were effective, and a new procedure designed to correct a supposed flaw in the other procedures was ineffective. (JKS)
Descriptors: Correlation, Hypothesis Testing, Monte Carlo Methods, Multivariate Analysis
Peer reviewedDunlap, William P.; Cornwell, John M. – Multivariate Behavioral Research, 1994
The fundamental problems that ipsative measures impose for factor analysis are shown analytically. Normative and ipsative correlation matrices are used to show that the factor pattern induced by ipsativity will overwhelm any factor structure seen with normative factor analysis, making factor analysis not interpretable. (SLD)
Descriptors: Correlation, Factor Analysis, Factor Structure, Matrices
Peer reviewedThorndike, Robert M. – Multivariate Behavioral Research, 1976
In their Monte Carlo study of canonical analysis, Barcikowski and Stevens evaluated the relative stability of canonical weights and loadings. This paper identifies some weaknesses in their study, suggests directions for future research in this area, and discusses interpretation of canonical analysis both in development and in cross-validation. For…
Descriptors: Correlation, Measurement Techniques, Monte Carlo Methods, Multivariate Analysis
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