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Ting Zhang; Paul Bailey; Yuqi Liao; Emmanuel Sikali – Large-scale Assessments in Education, 2024
The EdSurvey package helps users download, explore variables in, extract data from, and run analyses on large-scale assessment data. The analysis functions in EdSurvey account for the use of plausible values for test scores, survey sampling weights, and their associated variance estimator. We describe the capabilities of the package in the context…
Descriptors: National Competency Tests, Information Retrieval, Data Collection, Test Validity
Stoner, James C. – Journal of College and University Student Housing, 2019
Hiring the most capable students to serve in the RA role should be a top priority for housing departments due to their critical role as front-line student success employees. The effort to identify and hire RAs typically includes a substantial investment of personnel resources in hiring processes, where candidates are typically evaluated across…
Descriptors: Resident Advisers, College Housing, Personnel Selection, Job Performance
Luke W. Miratrix; Jasjeet S. Sekhon; Alexander G. Theodoridis; Luis F. Campos – Grantee Submission, 2018
The popularity of online surveys has increased the prominence of using weights that capture units' probabilities of inclusion for claims of representativeness. Yet, much uncertainty remains regarding how these weights should be employed in analysis of survey experiments: Should they be used or ignored? If they are used, which estimators are…
Descriptors: Online Surveys, Weighted Scores, Data Interpretation, Robustness (Statistics)
Balmeo, Marilyn L.; Castro, Allan B.; Caplis, Kristine Joy T.; Camba, Kizzylenn N.; Cruz, Jahziel Gillian M.; Orap, Marion G.; Cabutotan, Joroma Sol T. – IAFOR Journal of Education, 2014
The study sought to determine the perceived level of importance and perceived level of satisfaction of college students on 16 areas of student service commonly provided in a tertiary education setting within any university as prescribed and observed by local and international standards of tertiary education. Each area was tested to determine the…
Descriptors: Student Satisfaction, Educational Environment, College Environment, Higher Education
Zamarro, Gema; Anderson, Kaitlin; Steele, Jennifer; Miller, Trey – Society for Research on Educational Effectiveness, 2016
The purpose of this study is to study the performance of different methods (inverse probability weighting and estimation of informative bounds) to control for differential attrition by comparing the results of different methods using two datasets: an original dataset from Portland Public Schools (PPS) subject to high rates of differential…
Descriptors: Data Analysis, Student Attrition, Evaluation Methods, Evaluation Research
Warne, Russell T.; Nagaishi, Chanel; Slade, Michael K.; Hermesmeyer, Paul; Peck, Elizabeth Kimberli – NASSP Bulletin, 2014
While research has shown the statistical significance of high school grade point averages (HSGPAs) in predicting future academic outcomes, the systems with which HSGPAs are calculated vary drastically across schools. Some schools employ unweighted grades that carry the same point value regardless of the course in which they are earned; other…
Descriptors: Grade Point Average, Weighted Scores, Low Income, College Students
Carlson, Deven; Cowen, Joshua M. – Sociology of Education, 2015
Schools and neighborhoods are thought to be two of the most important contextual influences on student academic outcomes. Drawing on a unique data set that permits simultaneous estimation of neighborhood and school contributions to student test score gains, we analyze the distributions of these contributions to consider the relative importance of…
Descriptors: Scores, Socioeconomic Influences, Neighborhoods, Achievement Gains
Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S. – Review of Higher Education, 2015
Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…
Descriptors: Student Participation, College Bound Students, Enrollment Influences, Regression (Statistics)
Chen, Vivien W.; Pong, Suet-Ling – Journal of School Choice, 2014
Using a propensity score matching method, and regression modeling based on the 2002 Education Longitudinal Study, this study found a significant Catholic school, mathematics achievement effect among those 12th graders who were least likely to attend Catholic school. This result is evident within districts after we used the School District…
Descriptors: Mathematics Achievement, Catholic Schools, Grade 12, School Districts
Shaw, Stacy; Radwin, David – National Center for Education Statistics, 2014
The web tables in this report provide original and revised estimates of statistics previously published in 2007-08 National Postsecondary Student Aid Study (NPSAS:08): Student Financial Aid Estimates for 2007-08 (NCES 2009-166). The revised estimates were generated using revised weights that were updated in August 2013. NPSAS:08 data were…
Descriptors: Student Financial Aid, Tables (Data), Comparative Analysis, Statistical Data
Williams, Matt N.; Gomez Grajales, Carlos Alberto; Kurkiewicz, Dason – Practical Assessment, Research & Evaluation, 2013
In 2002, an article entitled "Four assumptions of multiple regression that researchers should always test" by Osborne and Waters was published in "PARE." This article has gone on to be viewed more than 275,000 times (as of August 2013), and it is one of the first results displayed in a Google search for "regression…
Descriptors: Multiple Regression Analysis, Misconceptions, Reader Response, Predictor Variables
Arikan, Serkan; van de Vijver, Fons J. R.; Yagmur, Kutlay – EURASIA Journal of Mathematics, Science & Technology Education, 2016
Large-scale studies, such as the Trends in International Mathematics and Science Study (TIMSS), provide data to understand cross-national differences and similarities. In this study, we aimed to identify factors predicting mathematics achievement of Turkish students by comparing to Australian students. First, construct equivalence and item bias…
Descriptors: Foreign Countries, Comparative Education, Mathematics Achievement, Performance Factors
Waller, Niels G.; Jones, Jeff A. – Psychometrika, 2009
In a multiple regression analysis with three or more predictors, every set of alternate weights belongs to an infinite class of "fungible weights" (Waller, Psychometrica, "in press") that yields identical "SSE" (sum of squared errors) and R[superscript 2] values. When the R[superscript 2] using the alternate weights is a fixed value, fungible…
Descriptors: Multiple Regression Analysis, Predictor Variables, Algebra, Geometric Concepts
Micceri, Theodore – Online Submission, 2010
This study sought to determine whether the use of standardized test scores contributes any useful information regarding First Time in College (FTIC) students' probable success at USF, using more detailed analysis of underrepresented minorities and women, who Micceri (2009) shows, experience substantial negative bias relative to males and whites on…
Descriptors: Class Rank, Grade Point Average, Females, Males
Carrell, Scott E.; Malmstrom, Frederick V.; West, James E. – Journal of Human Resources, 2008
Using self-reported academic cheating from the classes of 1959 through 2002 at the three major United States military service academies (Air Force, Army, and Navy), we measure how peer cheating influences individual cheating behavior. We find higher levels of peer cheating result in a substantially increased probability that an individual will…
Descriptors: Military Service, College Students, Cheating, Peer Influence