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Direct linkAgley, Jon; Tidd, David; Jun, Mikyoung; Eldridge, Lori; Xiao, Yunyu; Sussman, Steve; Jayawardene, Wasantha; Agley, Daniel; Gassman, Ruth; Dickinson, Stephanie L. – Educational and Psychological Measurement, 2021
Prospective longitudinal data collection is an important way for researchers and evaluators to assess change. In school-based settings, for low-risk and/or likely-beneficial interventions or surveys, data quality and ethical standards are both arguably stronger when using a waiver of parental consent--but doing so often requires the use of…
Descriptors: Data Analysis, Longitudinal Studies, Data Collection, Intervention
van Dijk, Wilhelmina; Schatschneider, Christopher; Al Otaiba, Stephanie; Hart, Sara A. – Educational and Psychological Measurement, 2022
Complex research questions often need large samples to obtain accurate estimates of parameters and adequate power. Combining extant data sets into a large, pooled data set is one way this can be accomplished without expending resources. Measurement invariance (MI) modeling is an established approach to ensure participant scores are on the same…
Descriptors: Sample Size, Data Analysis, Goodness of Fit, Measurement
Mansolf, Maxwell; Vreeker, Annabel; Reise, Steven P.; Freimer, Nelson B.; Glahn, David C.; Gur, Raquel E.; Moore, Tyler M.; Pato, Carlos N.; Pato, Michele T.; Palotie, Aarno; Holm, Minna; Suvisaari, Jaana; Partonen, Timo; Kieseppä, Tuula; Paunio, Tiina; Boks, Marco; Kahn, René; Ophoff, Roel A.; Bearden, Carrie E.; Loohuis, Loes Olde; Teshiba, Terri; deGeorge, Daniella; Bilder, Robert M. – Educational and Psychological Measurement, 2020
Large-scale studies spanning diverse project sites, populations, languages, and measurements are increasingly important to relate psychological to biological variables. National and international consortia already are collecting and executing mega-analyses on aggregated data from individuals, with different measures on each person. In this…
Descriptors: Item Response Theory, Data Analysis, Measurement, Validity
Thomas, D. Roland; Zumbo, Bruno D. – Educational and Psychological Measurement, 2012
There is such doubt in research practice about the reliability of difference scores that granting agencies, journal editors, reviewers, and committees of graduate students' theses have been known to deplore their use. This most maligned index can be used in studies of change, growth, or perhaps discrepancy between two measures taken on the same…
Descriptors: Statistical Analysis, Reliability, Scores, Change
McArdle, John J.; Hamagami, Fumiaki; Bautista, Randy; Onoye, Jane; Hishinuma, Earl S.; Prescott, Carol A.; Takeshita, Junji; Zonderman, Alan B.; Johnson, Ronald C. – Educational and Psychological Measurement, 2014
In this study, we reanalyzed the classic Hawai'i Family Study of Cognition (HFSC) data using contemporary multilevel modeling techniques. We used the HFSC baseline data ("N" = 6,579) and reexamined the factorial structure of 16 cognitive variables using confirmatory (restricted) measurement models in an explicit sequence. These models…
Descriptors: Factor Analysis, Hierarchical Linear Modeling, Data Analysis, Structural Equation Models
Kim, Eun Sook; Willson, Victor L. – Educational and Psychological Measurement, 2010
This article presents a method to evaluate pretest effects on posttest scores in the absence of an un-pretested control group using published results of pretesting effects due to Willson and Putnam. Confidence intervals around the expected theoretical gain due to pretesting are computed, and observed gains or differential gains are compared with…
Descriptors: Control Groups, Intervals, Educational Research, Educational Psychology
Furgol, Katherine E.; Ho, Andrew D.; Zimmerman, Dale L. – Educational and Psychological Measurement, 2010
Under the No Child Left Behind Act, large-scale test score trend analyses are widespread. These analyses often gloss over interesting changes in test score distributions and involve unrealistic assumptions. Further complications arise from analyses of unanchored, censored assessment data, or proportions of students lying within performance levels…
Descriptors: Trend Analysis, Sample Size, Federal Legislation, Simulation
Gardner, Donald G.; Pierce, Jon L. – Educational and Psychological Measurement, 2010
The authors empirically examined two operationalizations of the core self-evaluation construct: (a) the Judge, Erez, Bono, and Thoresen 12-item scale and (b) a composite measure of self-esteem, self-efficacy, locus of control, and neuroticism.The study found that the composite scale relates more strongly than the shorter scale to performance,…
Descriptors: Locus of Control, Self Efficacy, Construct Validity, Measures (Individuals)
Zimmerman, Donald W. – Educational and Psychological Measurement, 2007
Properties of the Spearman correction for attenuation were investigated using Monte Carlo methods, under conditions where correlations between error scores exist as a population parameter and also where correlated errors arise by chance in random sampling. Equations allowing for all possible dependence among true and error scores on two tests at…
Descriptors: Monte Carlo Methods, Correlation, Sampling, Data Analysis
von Davier, Alina A.; Wilson, Christine – Educational and Psychological Measurement, 2007
This article discusses the assumptions required by the item response theory (IRT) true-score equating method (with Stocking & Lord, 1983; scaling approach), which is commonly used in the nonequivalent groups with an anchor data-collection design. More precisely, this article investigates the assumptions made at each step by the IRT approach to…
Descriptors: Calculus, Item Response Theory, Scores, Data Collection
Peer reviewedMorris, John D. – Educational and Psychological Measurement, 1979
Several advantages to the use of different kinds of factor scores as independent variables in a multiple regression equation are reported. A computer program is presented which will calculate a regression equation using a variety of factor scores. (Author/JKS)
Descriptors: Computer Programs, Factor Analysis, Multiple Regression Analysis, Program Descriptions
Muller, Jorg M. – Educational and Psychological Measurement, 2006
A new test index is defined as the probability of obtaining two randomly selected test scores (PDTS) as statistically different. After giving a concept definition of the test index, two simulation studies are presented. The first analyzes the influence of the distribution of test scores, test reliability, and sample size on PDTS within classical…
Descriptors: Test Reliability, Probability, Scores, Item Response Theory
Cheung, Mike W.-L. – Educational and Psychological Measurement, 2006
Response bias has long been recognized as an issue in the behavioral and social sciences, especially in cross-cultural research. Transforming raw data into ipsatized data, individual scores subject to a constant sum constraint, is proposed to be an effective measure to minimize response bias. One major problem of applying ipsatized data is that…
Descriptors: Factor Analysis, Response Style (Tests), Behavioral Sciences, Social Sciences
Peer reviewedBlair, R. Clifford; And Others – Educational and Psychological Measurement, 1983
Sampling experiments were used to assess the Type I error rates of the t test in situations where classes were randomly assigned to groups but analyses were carried out on individual student scores. Even small amounts of between-class variation caused large inflations in the Type I error rate of the t test. (Author/BW)
Descriptors: Academic Achievement, Data Analysis, Elementary Secondary Education, Error of Measurement
Cano, Francisco – Educational and Psychological Measurement, 2006
This study explores the latent structure of scores on the Learning and Study Strategies Inventory (LASSI) and analyzes the relationship between this structure and students' academic performance. Two independent samples of college freshmen (n = 527) and seniors (n = 429) completed the LASSI. Data analysis of the first sample revealed acceptable…
Descriptors: Learning Strategies, Factor Structure, Academic Achievement, Scores
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