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Craig K. Enders – Grantee Submission, 2023
The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…
Descriptors: Data, Research, Theories, Regression (Statistics)
Peterson, Anna D.; Ziegler, Laura – Journal of Statistics and Data Science Education, 2021
We present an innovative activity that uses data about LEGO sets to help students self-discover multiple linear regressions. Students are guided to predict the price of a LEGO set posted on Amazon.com (Amazon price) using LEGO characteristics such as the number of pieces, the theme (i.e., product line), and the general size of the pieces. By…
Descriptors: Toys, Statistics Education, Teaching Methods, Regression (Statistics)
Hope E. Lackey; Rachel L. Sell; Gilbert L. Nelson; Thomas A. Bryan; Amanda M. Lines; Samuel A. Bryan – Journal of Chemical Education, 2023
The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least-squares (CLS), principal component…
Descriptors: Chemistry, Data Analysis, Optics, Lighting
Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
Erdman, Chandra; Adams, Tamara; O'Hare, Barbara C. – Field Methods, 2016
Realistic response rate expectations are important for successfully allocating and managing data collection efforts under limited resources. Interviewer performance is often evaluated against response rate standards, and face-to-face interviewer performance can vary due to, in part, the socioeconomic characteristics of the neighborhoods in which…
Descriptors: Response Rates (Questionnaires), Standards, National Surveys, Interviews
Moraveji, Behjat; Jafarian, Koorosh – International Journal of Education and Literacy Studies, 2014
The aim of this paper is to provide an introduction of new imputation algorithms for estimating missing values from official statistics in larger data sets of data pre-processing, or outliers. The goal is to propose a new algorithm called IRMI (iterative robust model-based imputation). This algorithm is able to deal with all challenges like…
Descriptors: Mathematics, Computation, Robustness (Statistics), Regression (Statistics)
Sorensen-Unruh, Clarissa – Journal of Chemical Education, 2017
This Communication summarizes one of the invited papers to the Select 2016 BCCE Presentations ACS CHED Committee on Computers in Chemical Education online ConfChem held from October 30 to November 22, 2016. The ConfChem paper (included within Supporting Information) focuses on the results of one instructor's incorporation of social media into her…
Descriptors: Chemistry, Computer Uses in Education, Conferences (Gatherings), Teaching Methods
Castellano, Katherine E.; Ho, Andrew D. – Council of Chief State School Officers, 2013
This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…
Descriptors: Guides, Models, Academic Achievement, Achievement Gains
Yetkiner, Zeynep Ebrar – Middle Grades Research Journal, 2009
Commonality analysis is a method of partitioning variance to determine the predictive ability unique to each predictor (or predictor set) and common to two or more of the predictors (or predictor sets). The purposes of the present paper are to (a) explain commonality analysis in a multiple regression context as an alternative for middle grades…
Descriptors: Multivariate Analysis, Correlation, Regression (Statistics), Prediction

Kerwin, Mary Louise E.; And Others – Counseling Psychologist, 1987
Describes the strengths and weaknesses of a new type of multivariate technique, covariance structure analysis (LISREL). Provides a detailed example which shows how the use of covariance structure analysis can improve research sophistication and theory development in counseling psychology. (Author/ABB)
Descriptors: Counseling, Multiple Regression Analysis, Multivariate Analysis, Psychology
Kristjansson, Elizabeth; Aylesworth, Richard; Mcdowell, Ian; Zumbo, Bruno D. – Educational and Psychological Measurement, 2005
Item bias is a major threat to measurement validity. Methods for detecting differential item functioning (DIF) are now commonly used to identify potentially biased items. DIF detection methods for dichotomous items are well developed, but those for ordinal items are less well developed. In this article, the authors compare four methods for…
Descriptors: Discriminant Analysis, Test Bias, Multivariate Analysis, Regression (Statistics)

Hoeksma, Jan B.; Knol, Dirk L. – Multivariate Behavioral Research, 2001
Makes the case that hierarchical linear models or longitudinal multilevel models are a better alternative than standard regression models for empirical tests of predictive developmental hypotheses. Describes a multivariate longitudinal model linking developmental data to a criterion and presents an example from a study of the prediction of infant…
Descriptors: Behavior Patterns, Case Studies, Development, Hypothesis Testing

Maeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics