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Jo, Booil – Psychological Methods, 2008
This article links the structural equation modeling (SEM) approach with the principal stratification (PS) approach, both of which have been widely used to study the role of intermediate posttreatment outcomes in randomized experiments. Despite the potential benefit of such integration, the 2 approaches have been developed in parallel with little…
Descriptors: Structural Equation Models, Monte Carlo Methods, Inferences, Outcomes of Treatment
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Klein Entink, Rinke H.; Kuhn, Jorg-Tobias; Hornke, Lutz F.; Fox, Jean-Paul – Psychological Methods, 2009
In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of…
Descriptors: Psychological Studies, Monte Carlo Methods, Markov Processes, Educational Assessment
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Jo, Booil; Asparouhov, Tihomir; Muthen, Bengt O.; Ialongo, Nicholas S.; Brown, C. Hendricks – Psychological Methods, 2008
Cluster randomized trials (CRTs) have been widely used in field experiments treating a cluster of individuals as the unit of randomization. This study focused particularly on situations where CRTs are accompanied by a common complication, namely, treatment noncompliance or, more generally, intervention nonadherence. In CRTs, compliance may be…
Descriptors: Individual Characteristics, Intervention, Statistical Inference, Inferences
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Cole, David A.; Martin, Nina C.; Steiger, James H. – Psychological Methods, 2005
The latent trait-state-error model (TSE) and the latent state-trait model with autoregression (LST-AR) represent creative structural equation methods for examining the longitudinal structure of psychological constructs. Application of these models has been somewhat limited by empirical or conceptual problems. In the present study, Monte Carlo…
Descriptors: Structural Equation Models, Computation, Longitudinal Studies, Monte Carlo Methods
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Markon, Kristian E.; Krueger, Robert F. – Psychological Methods, 2006
Distinguishing between discrete and continuous latent variable distributions has become increasingly important in numerous domains of behavioral science. Here, the authors explore an information-theoretic approach to latent distribution modeling, in which the ability of latent distribution models to represent statistical information in observed…
Descriptors: Statistical Distributions, Modeling (Psychology), Behavioral Sciences, Information Theory
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Charles, Eric P. – Psychological Methods, 2005
The correction for attenuation due to measurement error (CAME) has received many historical criticisms, most of which can be traced to the limited ability to use CAME inferentially. Past attempts to determine confidence intervals for CAME are summarized and their limitations discussed. The author suggests that inference requires confidence sets…
Descriptors: Error of Measurement, Error Correction, Intervals, Inferences
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Chan, Wai; Chan, Daniel W.-L. – Psychological Methods, 2004
The standard Pearson correlation coefficient is a biased estimator of the true population correlation, ?, when the predictor and the criterion are range restricted. To correct the bias, the correlation corrected for range restriction, r-sub(c), has been recommended, and a standard formula based on asymptotic results for estimating its standard…
Descriptors: Computation, Intervals, Sample Size, Monte Carlo Methods
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Serlin, Ronald C.; Harwell, Michael R. – Psychological Methods, 2004
It is well-known that for normally distributed errors parametric tests are optimal statistically, but perhaps less well-known is that when normality does not hold, nonparametric tests frequently possess greater statistical power than parametric tests, while controlling Type I error rate. However, the use of nonparametric procedures has been…
Descriptors: Multiple Regression Analysis, Monte Carlo Methods, Nonparametric Statistics, Error Patterns
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Lanza, Stephanie T.; Collins, Linda M.; Schafer, Joseph L.; Flaherty, Brian P. – Psychological Methods, 2005
Latent class analysis (LCA) provides a means of identifying a mixture of subgroups in a population measured by multiple categorical indicators. Latent transition analysis (LTA) is a type of LCA that facilitates addressing research questions concerning stage-sequential change over time in longitudinal data. Both approaches have been used with…
Descriptors: Markov Processes, Monte Carlo Methods, Evaluation Methods, Evaluation Research
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Field, Andy P. – Psychological Methods, 2005
One conceptualization of meta-analysis is that studies within the meta-analysis are sampled from populations with mean effect sizes that vary (random-effects models). The consequences of not applying such models and the comparison of different methods have been hotly debated. A Monte Carlo study compared the efficacy of Hedges and Vevea's…
Descriptors: Meta Analysis, Correlation, Effect Size, Models
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Hipp, John R.; Bauer, Daniel J. – Psychological Methods, 2006
Finite mixture models are well known to have poorly behaved likelihood functions featuring singularities and multiple optima. Growth mixture models may suffer from fewer of these problems, potentially benefiting from the structure imposed on the estimated class means and covariances by the specified growth model. As demonstrated here, however,…
Descriptors: Monte Carlo Methods, Maximum Likelihood Statistics, Computation, Case Studies
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Huedo-Medina, Tania B.; Sanchez-Meca, Julio; Marin-Martinez, Fulgencio; Botella, Juan – Psychological Methods, 2006
In meta-analysis, the usual way of assessing whether a set of single studies is homogeneous is by means of the Q test. However, the Q test only informs meta-analysts about the presence versus the absence of heterogeneity, but it does not report on the extent of such heterogeneity. Recently, the I[squared] index has been proposed to quantify the…
Descriptors: Meta Analysis, Intervals, Monte Carlo Methods, Comparative Analysis
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Furlow, Carolyn F.; Beretvas, S. Natasha – Psychological Methods, 2005
Three methods of synthesizing correlations for meta-analytic structural equation modeling (SEM) under different degrees and mechanisms of missingness were compared for the estimation of correlation and SEM parameters and goodness-of-fit indices by using Monte Carlo simulation techniques. A revised generalized least squares (GLS) method for…
Descriptors: Rejection (Psychology), Monte Carlo Methods, Least Squares Statistics, Correlation
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