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Bernard, Robert M.; Borokhovski, Eugene; Schmid, Richard F.; Tamim, Rana M. – Journal of Computing in Higher Education, 2014
This article contains a second-order meta-analysis and an exploration of bias in the technology integration literature in higher education. Thirteen meta-analyses, dated from 2000 to 2014 were selected to be included based on the questions asked and the presence of adequate statistical information to conduct a quantitative synthesis. The weighted…
Descriptors: Meta Analysis, Bias, Technology Integration, Higher Education
Wilkins, C. – Regional Educational Laboratory Southwest (NJ1), 2008
REL Southwest received a request to review the report "Avoidable Losses: High Stakes Accountability and the Dropout Crisis" to assess the soundness of the study methodology and the appropriateness of the conclusions drawn in the report. The review found that conclusions drawn in this study cannot be generalized and are significantly…
Descriptors: Federal Legislation, Academic Achievement, Ethnography, Statistical Analysis
Peer reviewedJackson, Sally; And Others – Human Communication Research, 1988
Considers two ways of conducting the search for generalizations about messages: (1) single-message research designs used with meta-analytic summaries; and (2) multiple-message designs treating messages as a random factor in the statistical analysis. Contends that the treatment of messages as a random factor is statistically appropriate. (MS)
Descriptors: Communication Research, Experimenter Characteristics, Generalization, Meta Analysis
Peer reviewedMorley, Donald Dean – Human Communication Research, 1988
Replies to Sally Jackson, Daniel O'Keefe, and Scott Jacobs' article (same issue), maintaining that randomness requirements can not be relaxed for generalizing from message samples, since systematic samples are not truly random. (MS)
Descriptors: Communication Research, Experimenter Characteristics, Generalization, Meta Analysis
Carter, Deborah Faye; Hurtado, Sylvia – New Directions for Institutional Research, 2007
This chapter serves as a guide for quantitative researchers who seek to approach their research questions critically.
Descriptors: Statistical Analysis, Research Methodology, Autobiographies, Interpersonal Relationship
Zijlstra, Wobbe P.; Van Der Ark, L. Andries; Sijtsma, Klaas – Multivariate Behavioral Research, 2007
Classical methods for detecting outliers deal with continuous variables. These methods are not readily applicable to categorical data, such as incorrect/correct scores (0/1) and ordered rating scale scores (e.g., 0,..., 4) typical of multi-item tests and questionnaires. This study proposes two definitions of outlier scores suited for categorical…
Descriptors: Rating Scales, Scores, Regression (Statistics), Statistical Analysis
Peer reviewedMorley, Donald Dean – Human Communication Research, 1988
Argues that generalizing to message populations by treating messages as a random variable is inappropriate for complex messages, and proposes meta-analytic techniques for investigating biases in message samples and other methodological factors that can limit generalizability of communication research. (MS)
Descriptors: Communication Research, Experimenter Characteristics, Generalization, Meta Analysis
Peer reviewedPeplau, Letitia Anne; Conrad, Eva – Psychology of Women Quarterly, 1989
Discusses the features of feminist research in psychology. Evaluates proposals for distinctively feminist research methods. Refutes suggestions that experimentation and quantitative research are inherently less feminist than other approaches. Rejects criteria based on sex of participant or researcher. Concludes that any research method can be…
Descriptors: Experimental Psychology, Experimenter Characteristics, Females, Feminism

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