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Direct linkVictoria Savalei; Yves Rosseel – Structural Equation Modeling: A Multidisciplinary Journal, 2022
This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…
Descriptors: Structural Equation Models, Computation, Error of Measurement, Robustness (Statistics)
Anders Holm; Anders Hjorth-Trolle; Robert Andersen – Sociological Methods & Research, 2025
Lagged dependent variables (LDVs) are often used as predictors in ordinary least squares (OLS) models in the social sciences. Although several estimators are commonly employed, little is known about their relative merits in the presence of classical measurement error and different longitudinal processes. We assess the performance of four commonly…
Descriptors: Elementary Education, Scores, Error of Measurement, Predictor Variables
Download full textMatthew J. Salganik; Ian Lundberg; Alexander T. Kindel; Caitlin E. Ahearn; Khaled Al-Ghoneim; Abdullah Almaatouq; Drew M. Altschul; Jennie E. Brand; Nicole Bohme Carnegie; Ryan James Compton; Debanjan Datta; Thomas Davidson; Anna Filippova; Connor Gilroy; Brian J. Goode; Eaman Jahani; Ridhi Kashyap; Antje Kirchner; Stephen McKay; Allison C. Morgan; Alex Pentland; Kivan Polimis; Louis Raes; Daniel E. Rigobon; Claudia V. Roberts; Diana M. Stanescu; Yoshihiko Suhara; Adaner Usmani; Erik H. Wang; Muna Adem; Abdulla Alhajri; Bedoor AlShebli; Redwane Amin; Ryan B. Amos; Lisa P. Argyle; Livia Baer-Bositis; Moritz Büchi; Bo-Ryehn Chung; William Eggert; Gregory Faletto; Zhilin Fan; Jeremy Freese; Tejomay Gadgil; Josh Gagné; Yue Gao; Andrew Halpern-Manners; Sonia P. Hashim; Sonia Hausen; Guanhua He; Kimberly Higuera; Bernie Hogan; Ilana M. Horwitz; Lisa M. Hummel; Naman Jain; Kun Jin; David Jurgens; Patrick Kaminski; Areg Karapetyan; E. H. Kim; Ben Leizman; Naijia Liu; Malte Möser; Andrew E. Mack; Mayank Mahajan; Noah Mandell; Helge Marahrens; Diana Mercado-Garcia; Viola Mocz; Katariina Mueller-Gastell; Ahmed Musse; Qiankun Niu; William Nowak; Hamidreza Omidvar; Andrew Or; Karen Ouyang; Katy M. Pinto; Ethan Porter; Kristin E. Porter; Crystal Qian; Tamkinat Rauf; Anahit Sargsyan; Thomas Schaffner; Landon Schnabel; Bryan Schonfeld; Ben Sender; Jonathan D. Tang; Emma Tsurkov; Austin van Loon; Onur Varol; Xiafei Wang; Zhi Wang; Julia Wang; Flora Wang; Samantha Weissman; Kirstie Whitaker; Maria K. Wolters; Wei Lee Woon; James Wu; Catherine Wu; Kengran Yang; Jingwen Yin; Bingyu Zhao; Chenyun Zhu; Jeanne Brooks-Gunn; Barbara E. Engelhardt; Moritz Hardt; Dean Knox; Karen Levy; Arvind Narayanan; Brandon M. Stewart; Duncan J. Watts; Sara McLanahan – Grantee Submission, 2020
How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning…
Descriptors: Life Satisfaction, Family Life, Quality of Life, Disadvantaged
Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
We extend a unified and easy-to-use approach to measurement error and missing data. In our companion article, Blackwell, Honaker, and King give an intuitive overview of the new technique, along with practical suggestions and empirical applications. Here, we offer more precise technical details, more sophisticated measurement error model…
Descriptors: Error of Measurement, Correlation, Simulation, Bayesian Statistics
Leckie, George; Goldstein, Harvey – British Educational Research Journal, 2017
Since 1992, the UK Government has published so-called "school league tables" summarising the average General Certificate of Secondary Education (GCSE) "attainment" and "progress" made by pupils in each state-funded secondary school in England. While the headline measure of school attainment has remained the percentage…
Descriptors: Foreign Countries, Achievement Rating, Academic Achievement, Secondary School Students
Pinder, Jonathan P. – Decision Sciences Journal of Innovative Education, 2014
Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection ("type I errors") is…
Descriptors: Data Collection, Data Analysis, Regression (Statistics), Predictive Measurement
Cornejo, Felipe A.; Castillo, Ramon D.; Saavedra, Maria A.; Vogel, Edgar H. – Psicologica: International Journal of Methodology and Experimental Psychology, 2010
Considerable research has examined the contrasting predictions of configural and elemental associative accounts of learning. One of the simplest methods to distinguish between these approaches is the summation test, in which the associative strength of a novel compound (AB) made of two separately-trained cues (A+ and B+) is examined. The…
Descriptors: Animals, Cues, Classical Conditioning, Prediction
Zwick, Rebecca; Himelfarb, Igor – Journal of Educational Measurement, 2011
Research has often found that, when high school grades and SAT scores are used to predict first-year college grade-point average (FGPA) via regression analysis, African-American and Latino students, are, on average, predicted to earn higher FGPAs than they actually do. Under various plausible models, this phenomenon can be explained in terms of…
Descriptors: Socioeconomic Status, Grades (Scholastic), Error of Measurement, White Students
Woodruff, David – 1989
Previous methods for estimating the conditional standard error of measurement (CSEM) at specific score or ability levels are critically discussed, and a brief summary of prior empirical results is given. A new method is developed which avoids theoretical problems inherent in some prior methods, is easy to implement, and estimates not only a…
Descriptors: Error of Measurement, Estimation (Mathematics), Mathematical Models, Predictive Measurement
Peer reviewedSchulman, Robert S. – Psychometrika, 1976
Based on the test theory model for ordinal measurements proposed by Schulman and Haden, the present paper considers correlations between tests, attenuation, regressions involving true and observed scores, and predictions of test reliability. Comparisons are made to interval test theory. (Author/JKS)
Descriptors: Correlation, Error of Measurement, Measurement Techniques, Predictive Measurement
Comparison of Anthropometry to Dual Energy X-Ray Absorptiometry: A New Prediction Equation for Women
Ball, Stephen; Swan, Pamela D.; DeSimone, Rosemarie – Research Quarterly for Exercise and Sport, 2004
The purpose of this study was to assess the accuracy of three recommended anthropometric equations for women and then develop an updated prediction equation using dual energy x-ray absorptiometry (DXA). The percentage of body fat (%BF) by anthropometry was significantly correlated (r = .896-. 929; p [is less than] .01) with DXA, but each equation…
Descriptors: Females, Body Composition, Predictive Measurement, Error of Measurement
Vehrs, Pat R.; George, James D.; Fellingham, Gilbert W.; Plowman, Sharon A.; Dustman-Allen, Kymberli – Measurement in Physical Education and Exercise Science, 2007
This study was designed to develop a single-stage submaximal treadmill jogging (TMJ) test to predict VO[subscript 2]max in fit adults. Participants (N = 400; men = 250 and women = 150), ages 18 to 40 years, successfully completed a maximal graded exercise test (GXT) at 1 of 3 laboratories to determine VO[subscript 2]max. The TMJ test was completed…
Descriptors: Metabolism, Body Composition, Physical Activities, Physical Fitness
Peer reviewedFullerton, Howard N., Jr. – Monthly Labor Review, 1988
Among the five rounds of labor force projections conducted between 1970 and 1980, those estimates produced in 1978 yielded results closest to actual 1985 values. (Author)
Descriptors: Employment Projections, Employment Statistics, Error of Measurement, Evaluation
Peer reviewedKaplan, 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 reviewedHarris, Chester W. – Journal of Educational Measurement, 1973
A brief note presenting algebraically equivalent formulas for the variances of three error types. (Author)
Descriptors: Algebra, Analysis of Covariance, Analysis of Variance, Error of Measurement
