Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 9 |
Descriptor
Error Correction | 9 |
Error of Measurement | 9 |
Statistical Bias | 9 |
Monte Carlo Methods | 3 |
Regression (Statistics) | 3 |
Research Design | 3 |
Scores | 3 |
Statistical Analysis | 3 |
Adolescents | 2 |
Effect Size | 2 |
Models | 2 |
More ▼ |
Source
Author
Barreca, Alan I. | 1 |
Beretvas, S. Natasha | 1 |
Bogaert, Jasper | 1 |
Cimpian, Joseph R. | 1 |
Dimoliatis, Ioannis D. K. | 1 |
Ferron, John M. | 1 |
Herzog, Serge | 1 |
Heyvaert, Mieke | 1 |
Jelastopulu, Eleni | 1 |
Lindo, Jason M. | 1 |
Loh, Wen Wei | 1 |
More ▼ |
Publication Type
Journal Articles | 8 |
Reports - Research | 7 |
Reports - Descriptive | 1 |
Reports - Evaluative | 1 |
Education Level
Higher Education | 2 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Researchers | 1 |
Location
California | 1 |
Laws, Policies, & Programs
Assessments and Surveys
National Longitudinal Study… | 1 |
What Works Clearinghouse Rating
Bogaert, Jasper; Loh, Wen Wei; Rosseel, Yves – Educational and Psychological Measurement, 2023
Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error…
Descriptors: Factor Analysis, Regression (Statistics), Structural Equation Models, Error of Measurement
Nguyen, Trang Quynh; Stuart, Elizabeth A. – Journal of Educational and Behavioral Statistics, 2020
We address measurement error bias in propensity score (PS) analysis due to covariates that are latent variables. In the setting where latent covariate X is measured via multiple error-prone items W, PS analysis using several proxies for X--the W items themselves, a summary score (mean/sum of the items), or the conventional factor score (i.e.,…
Descriptors: Error of Measurement, Statistical Bias, Error Correction, Probability
Mazza, Angelo; Punzo, Antonio – Sociological Methods & Research, 2015
The dissimilarity index of Duncan and Duncan is widely used in a broad range of contexts to assess the overall extent of segregation in the allocation of two groups in two or more units. Its sensitivity to random allocation implies an upward bias with respect to the unknown amount of systematic segregation. In this article, following a multinomial…
Descriptors: Statistical Bias, Error of Measurement, Error Correction, Mathematical Logic
Cimpian, Joseph R. – Educational Researcher, 2017
Quantitative research on sexual minority youths (SMYs) has likely contributed to misperceptions about the risk and deviance of this population. In part because it often relies on self-reported data from population-based self-administered questionnaires, this research is susceptible to misclassification bias whereby youths who are not SMYs are…
Descriptors: Secondary School Students, Adolescents, Minority Group Students, Homosexuality
Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Onghena, Patrick; Heyvaert, Mieke; Beretvas, S. Natasha; Van den Noortgate, Wim – School Psychology Quarterly, 2015
The purpose of this study is to illustrate the multilevel meta-analysis of results from single-subject experimental designs of different types, including AB phase designs, multiple-baseline designs, ABAB reversal designs, and alternating treatment designs. Current methodological work on the meta-analysis of single-subject experimental designs…
Descriptors: Intervention, Multivariate Analysis, Meta Analysis, Research Design
Dimoliatis, Ioannis D. K.; Jelastopulu, Eleni – Universal Journal of Educational Research, 2013
The surgical theatre educational environment measures STEEM, OREEM and mini-STEEM for students (student-STEEM) comprise an up to now disregarded systematic overestimation (OE) due to inaccurate percentage calculation. The aim of the present study was to investigate the magnitude of and suggest a correction for this systematic bias. After an…
Descriptors: Educational Environment, Scores, Grade Prediction, Academic Standards
Barreca, Alan I.; Lindo, Jason M.; Waddell, Glen R. – National Bureau of Economic Research, 2011
This study uses Monte Carlo simulations to demonstrate that regression-discontinuity designs arrive at biased estimates when attributes related to outcomes predict heaping in the running variable. After showing that our usual diagnostics are poorly suited to identifying this type of problem, we provide alternatives. We also demonstrate how the…
Descriptors: Statistical Bias, Regression (Statistics), Research Design, Monte Carlo Methods
Wang, Zhongmiao; Thompson, Bruce – Journal of Experimental Education, 2007
In this study the authors investigated the use of 5 (i.e., Claudy, Ezekiel, Olkin-Pratt, Pratt, and Smith) R[squared] correction formulas with the Pearson r[squared]. The authors estimated adjustment bias and precision under 6 x 3 x 6 conditions (i.e., population [rho] values of 0.0, 0.1, 0.3, 0.5, 0.7, and 0.9; population shapes normal, skewness…
Descriptors: Effect Size, Correlation, Mathematical Formulas, Monte Carlo Methods
Herzog, Serge – New Directions for Institutional Research, 2008
Among the varied analytical challenges institutional researchers face, examining faculty pay may be one of the most vexing. Although the literature on faculty compensation analysis dates back to the 1970s (Loeb and Ferber, 1971; Gordon, Morton, and Braden, 1974; Scott, 1977; Braskamp and Johnson, 1978; McLaughlin, Smart, and Montgomery, 1978),…
Descriptors: Teacher Salaries, Land Grant Universities, Compensation (Remuneration), Workers Compensation