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Showing 166 to 180 of 367 results Save | Export
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Hafdahl, Adam R.; Williams, Michelle A. – Psychological Methods, 2009
In 2 Monte Carlo studies of fixed- and random-effects meta-analysis for correlations, A. P. Field (2001) ostensibly evaluated Hedges-Olkin-Vevea Fisher-[zeta] and Schmidt-Hunter Pearson-r estimators and tests in 120 conditions. Some authors have cited those results as evidence not to meta-analyze Fisher-[zeta] correlations, especially with…
Descriptors: Monte Carlo Methods, Computer Software, Statistical Analysis, Correlation
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Murphy, Daniel L.; Pituch, Keenan A. – Journal of Experimental Education, 2009
The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…
Descriptors: Sample Size, Computation, Evaluation Methods, Longitudinal Studies
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de Winter, J. C. F.; Dodou, D.; Wieringa, P. A. – Multivariate Behavioral Research, 2009
Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…
Descriptors: Sample Size, Factor Analysis, Enrollment, Evaluation Methods
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Kessel, Robert; Lucke, Robert L. – Journal of the Experimental Analysis of Behavior, 2008
Shull, Gaynor and Grimes advanced a model for interresponse time distribution using probabilistic cycling between a higher-rate and a lower-rate response process. Both response processes are assumed to be random in time with a constant rate. The cycling between the two processes is assumed to have a constant transition probability that is…
Descriptors: Statistical Analysis, Probability, Monte Carlo Methods, Simulation
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Froelich, Amy G.; Habing, Brian – Applied Psychological Measurement, 2008
DIMTEST is a nonparametric hypothesis-testing procedure designed to test the assumptions of a unidimensional and locally independent item response theory model. Several previous Monte Carlo studies have found that using linear factor analysis to select the assessment subtest for DIMTEST results in a moderate to severe loss of power when the exam…
Descriptors: Test Items, Monte Carlo Methods, Form Classes (Languages), Program Effectiveness
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Capizzo, M. C.; Sperandeo-Mineo, R. M.; Zarcone, M. – European Journal of Physics, 2008
We present a pedagogic approach aimed at modelling electric conduction in semiconductors in order to describe and explain some macroscopic properties, such as the characteristic behaviour of resistance as a function of temperature. A simple model of the band structure is adopted for the generation of electron-hole pairs as well as for the carrier…
Descriptors: Teaching Methods, Science Instruction, Laboratory Equipment, Science Experiments
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Woods, Carol M. – Applied Psychological Measurement, 2008
In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters. In extant Monte Carlo evaluations of RC-IRT, the item response function (IRF) used to fit the data is the same one used to generate the data. The present simulation study examines RC-IRT when the IRF is imperfectly…
Descriptors: Simulation, Item Response Theory, Monte Carlo Methods, Comparative Analysis
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Peralta, Luis; Farinha, Ana Catarina; Rego, Florbela – European Journal of Physics, 2008
X-ray fluorescence is a non-destructive technique that allows elemental composition analysis. In this paper we describe a prescription to obtain the elemental composition of homogeneous coins, like 50 cent Euro coins, and how to get the quantitative proportions of each element with the help of Monte Carlo simulation. Undergraduate students can…
Descriptors: Undergraduate Students, Monte Carlo Methods, Chemistry, Science Laboratories
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Cohen, Allan S.; Kane, Michael T.; Kim, Seock-Ho – Applied Psychological Measurement, 2001
Discusses reasons why increasing the number of replications in Monte Carlo simulation studies is not necessary for satisfactory levels of precision and offers guidelines in the context of error tolerance analysis for determining how much precision is needed. (SLD)
Descriptors: Monte Carlo Methods, Simulation
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Argoti, A.; Fan, L. T.; Cruz, J.; Chou, S. T. – Chemical Engineering Education, 2008
The stochastic simulation of chemical reactions, specifically, a simple reversible chemical reaction obeying the first-order, i.e., linear, rate law, has been presented by Martinez-Urreaga and his collaborators in this journal. The current contribution is intended to complement and augment their work in two aspects. First, the simple reversible…
Descriptors: Chemistry, Equations (Mathematics), Probability, Science Instruction
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Alsawalmeh, Yousef M.; Feldt, Leonard S. – Applied Psychological Measurement, 1999
Developed an approximate statistical test for the hypothesis of equality between the Spearman-Brown extrapolations of two independent values of Cronbach's alpha reliability coefficient. Monte Carlo simulations demonstrate that the procedure effectively controls Type I error. (SLD)
Descriptors: Monte Carlo Methods, Reliability, Simulation
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Zhang, Bo; Ohland, Matthew W. – Applied Measurement in Education, 2009
One major challenge in using group projects to assess student learning is accounting for the differences of contribution among group members so that the mark assigned to each individual actually reflects their performance. This research addresses the validity of grading group projects by evaluating different methods that derive individualized…
Descriptors: Monte Carlo Methods, Validity, Student Evaluation, Evaluation Methods
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Fox, J.-P.; Wyrick, Cheryl – Journal of Educational and Behavioral Statistics, 2008
The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…
Descriptors: Item Response Theory, Models, Markov Processes, Monte Carlo Methods
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Hoshino, Takahiro; Shigemasu, Kazuo – Applied Psychological Measurement, 2008
The authors propose a concise formula to evaluate the standard error of the estimated latent variable score when the true values of the structural parameters are not known and must be estimated. The formula can be applied to factor scores in factor analysis or ability parameters in item response theory, without bootstrap or Markov chain Monte…
Descriptors: Monte Carlo Methods, Markov Processes, Factor Analysis, Computation
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Wells, Craig S.; Bolt, Daniel M. – Applied Measurement in Education, 2008
Tests of model misfit are often performed to validate the use of a particular model in item response theory. Douglas and Cohen (2001) introduced a general nonparametric approach for detecting misfit under the two-parameter logistic model. However, the statistical properties of their approach, and empirical comparisons to other methods, have not…
Descriptors: Test Length, Test Items, Monte Carlo Methods, Nonparametric Statistics
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