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Rosanna Cole – Sociological Methods & Research, 2024
The use of inter-rater reliability (IRR) methods may provide an opportunity to improve the transparency and consistency of qualitative case study data analysis in terms of the rigor of how codes and constructs have been developed from the raw data. Few articles on qualitative research methods in the literature conduct IRR assessments or neglect to…
Descriptors: Interrater Reliability, Error of Measurement, Evaluation Methods, Research Methodology
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McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
Cheema, Jehanzeb R. – Review of Educational Research, 2014
Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…
Descriptors: Educational Research, Data, Data Collection, Data Processing
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Lee, In Heok – Career and Technical Education Research, 2012
Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…
Descriptors: Vocational Education, Data Collection, Maximum Likelihood Statistics, Educational Research
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McConnell, Sheena; Stuart, Elizabeth A.; Devaney, Barbara – Evaluation Review, 2008
Although experiments are viewed as the gold standard for evaluation, some of their benefits may be lost when, as is common, outcomes are not defined for some sample members. In evaluations of marriage interventions, for example, a key outcome--relationship quality--is undefined when a couple splits up. This article shows how treatment-control…
Descriptors: Schematic Studies, Control Groups, Evaluation Research, Evaluation Problems
Gorard, Stephen – International Journal of Research & Method in Education, 2007
This paper presents an argument against the wider adoption of complex forms of data analysis, using multi-level modeling (MLM) as an extended case study. MLM was devised to overcome some deficiencies in existing datasets, such as the bias caused by clustering. The paper suggests that MLM has an unclear theoretical and empirical basis, has not led…
Descriptors: Data Analysis, Research Methodology, Error of Measurement, Error Correction
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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
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Umbach, Paul D. – New Directions for Institutional Research, 2005
Because surveys now can be implemented with relative ease and little cost, many researchers are overlooking the basic principles of survey research. This chapter discusses sources of error that researchers should consider when conducting a survey, and gives readers basic suggestions for reducing error. (Contains 1 table and 1 figure.)
Descriptors: Researchers, Research Methodology, School Surveys, Research Design
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Carter, Rufus Lynn – Research & Practice in Assessment, 2006
Many times in both educational and social science research it is impossible to collect data that is complete. When administering a survey, for example, people may answer some questions and not others. This missing data causes a problem for researchers using structural equation modeling (SEM) techniques for data analyses. Because SEM and…
Descriptors: Structural Equation Models, Error of Measurement, Data, Change Strategies