NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 12 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Manly, Catherine A.; Wells, Ryan S. – Research in Higher Education, 2015
Higher education researchers using survey data often face decisions about handling missing data. Multiple imputation (MI) is considered by many statisticians to be the most appropriate technique for addressing missing data in many circumstances. In particular, it has been shown to be preferable to listwise deletion, which has historically been a…
Descriptors: Higher Education, Educational Research, Surveys, Data
Peer reviewed Peer reviewed
Direct linkDirect link
Perna, Laura W.; Gerald, Danette; Baum, Evan; Milem, Jeffrey – Research in Higher Education, 2007
This paper uses descriptive analyses of data from the Integrated Postsecondary Education Data System to examine the status of Blacks among faculty and administrators at public higher education institutions in the South, where "status" is defined as representation in employment relative to representation among bachelor's degree…
Descriptors: Higher Education, College Faculty, African Americans, Administrators
Peer reviewed Peer reviewed
Leslie, David W.; Fygetakis, Elaine C. – Research in Higher Education, 1992
This paper compares the results of National Center for Education Statistics (NCES) and the Carnegie surveys of postsecondary faculty and notes the differently constructed samples, the different response rates, and different weighting schemes in analysis and interpretation. Inconsistencies in the surveys' results are identified and methodological…
Descriptors: College Faculty, Data Analysis, Data Interpretation, Higher Education
Peer reviewed Peer reviewed
Direct linkDirect link
LaNasa, Steven M.; Olson, Elizabeth; Alleman, Natalie – Research in Higher Education, 2007
During the past two decades institutions of all types have sought to expand and enhance residential facilities. Institutional focus on scale, configuration, amenities, and academic integration has sought to leverage prior research documenting the multiple and often positive impacts of on-campus residence. Although institutional size has been…
Descriptors: Academic Achievement, College Freshmen, Social Integration, On Campus Students
Peer reviewed Peer reviewed
Direct linkDirect link
Stratton, Leslie S.; O'Toole, Dennis M.; Wetzel, James N. – Research in Higher Education, 2007
We use data from the 1990/1994 Beginning Post-Secondary Survey to determine whether the factors associated with long-term attrition from higher education differ for students who initially enrolled part-time as compared to for students who initially enrolled full-time. Using a two-stage sequential decision model to analyze the initial enrollment…
Descriptors: Student Characteristics, Enrollment Trends, Student Attrition, Dropout Research
Peer reviewed Peer reviewed
Coker, Dana Rosenberg; Friedel, Janice Nahra – Research in Higher Education, 1991
The data collection matrix makes possible the integration of functional area data from numerous assessment sources and presentation of the information in a unified composite report. This model is discussed in relation to the various assessment instruments and the evaluation of functional areas and programs in colleges and universities. (Author/MSE)
Descriptors: Data Collection, Higher Education, Institutional Research, Program Evaluation
Peer reviewed Peer reviewed
Dey, Eric L. – Research in Higher Education, 1997
A study investigated the effectiveness of a weighting procedure for adjusting survey results to correct for nonresponse bias. Using data from a Cooperative Institutional Research Program followup survey, results indicate that the procedure is highly effective in univariate distributions; its effectiveness in adjusting correlation and regression…
Descriptors: Data Analysis, Followup Studies, Higher Education, Research Methodology
Peer reviewed Peer reviewed
Saupe, Joe L. – Research in Higher Education, 1992
A procedure for smoothing proportions of a double-entry expectancy table is described. The product is a nomograph from which can be read expectancies from combinations of values of two predictor variables. Use of the procedure in admission of first-year college students, based on students' high school class rank and standardized test composite…
Descriptors: Academic Achievement, College Administration, College Admission, College Entrance Examinations
Peer reviewed Peer reviewed
Schwarzmueller, E. Beth; Pounds, Haskin R. – Research in Higher Education, 1984
Some of the errors associated with use of data from the National Center for Education Statistics' Higher Education General Information Survey (HEGIS) are described, 1980 HEGIS and census reports of college enrollment are compared in tables of data, and a more cautious use of HEGIS data is recommended. (MSE)
Descriptors: Data Collection, Databases, Educational Research, Enrollment Rate
Peer reviewed Peer reviewed
Cohen, Peter A. – Research in Higher Education, 1980
A meta-analytic methodology is applied to integrate findings from 22 comparisons of the effectiveness of student- rating feedback at the college level. Feedback had a modest but significant effect on improving instruction. The effects of student-rating feedback were accentuated when augmentation or consultation accompanied the ratings. (Author/MLW)
Descriptors: College Instruction, Course Evaluation, Data Analysis, Faculty Development
Peer reviewed Peer reviewed
Jenny, Hans H. – Research in Higher Education, 1979
W. John Minter and Howard R. Bowen's annual report on "Financial and Educational Trends in Independent Higher Education, 1978" is examined. Problems in data reporting by college administrators that skew financial assessment reports are noted. A rating questionnaire for institutional quality is appended. (Author/LBH)
Descriptors: Data Collection, Educational Assessment, Educational Finance, Evaluation Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Thomas, Emily H.; Galambos, Nora – Research in Higher Education, 2004
To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The…
Descriptors: Student Attitudes, Multiple Regression Analysis, Student Experience, Satisfaction