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A meta-analytic review of the performance-cue biasMoody, Ann Michelle. January 2005 (has links) (PDF)
Thesis (M.S.)--Montana State University--Bozeman, 2005. / Typescript. Chairperson, Graduate Committee: Richard F. Martell. Includes bibliographical references (leaves 29-33).
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Does using data from sources other than primary studies inflate estimates of true criterion-related validity in meta-analysis?Host, Paul R. 01 January 1999 (has links)
No description available.
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Interpreting evidence from multiple randomised and non-randomised studiesSmith, Teresa Clare January 1995 (has links)
No description available.
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The effects of metacognitive strategies on reading comprehension : a quantitative synthesis and the empirical investigationFauzan, Norsiah January 2003 (has links)
No description available.
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The effect of negative feedback on motivation : a meta-analytic investigationFong, Carlton Jing 25 June 2014 (has links)
Although the most prominent view in psychological theory has been that negative feedback should generally have a detrimental impact on motivation, competing perspectives and caveats on this prominent view have suggested that negative feedback may sometimes have neutral or even positive effects on motivation. A meta-analysis of 79 studies examined the effect of negative feedback on motivation and related outcomes with both child and adult samples. Results indicated that negative feedback compared to positive feedback decreased intrinsic motivation and perceived competence. This effect is much smaller when compared to neutral or no feedback. Moderator tests revealed that the effect of negative feedback seems to be less demotivating when a) the feedback statement includes instructional details to improve, b) compared to objective versus normative standards, and c) the task is interesting. Implications for future research and applications to real-world settings are discussed. / text
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A FRAMEWORK FOR THE META-ANALYSIS OF SURVEY DATAFOX, KARLA MICHELLE PHILLIPS COOPER 06 December 2011 (has links)
The research outlined in this thesis covers various different statistical issues relating to meta-analysis of survey data. These issues include the creation of an original comprehensive methodological framework for combining survey data, a comparison of this framework with the traditional one proposed by Cochran for the combination of experiments, a proposal for a new weighting method that takes into account the differences in variability due to the sampling plan, an examination of the convergence of meta-analytic estimators, and a discussion on the numerous implicit assumptions researchers make when they are using meta-analysis methods with survey data along with guidelines for completing and reporting reviews when the data come from surveys. / Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2011-12-06 15:11:24.717
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Simple strategies for variance uncertainty in meta-analysisDi Gessa, Giorgio. January 2007 (has links)
Thesis (M.Sc.(R)) - University of Glasgow, 2007. / M.Sc.(R) thesis submitted to the Department of Statistics, Faculty of Information and Mathematical Sciences, University of Glasgow, 2007. Includes bibliographical references. Print version also available.
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Analysis of the evolution of research areas, themes, and methods in electronic commerceHwang, Taewon. January 2009 (has links)
Thesis (Ph.D.)--University of Nebraska-Lincoln, 2009. / Title from title screen (site viewed January 5, 2010). PDF text: v, 149 p. : ill. ; 2 Mb. UMI publication number: AAT 3360499. Includes bibliographical references. Also available in microfilm and microfiche formats.
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An introduction to meta analysisBoykova, Alla January 1900 (has links)
Master of Science / Department of Statistics / Dallas W. Johnson / Meta analysis is a statistical technique for synthesizing of results obtained from multiple
studies. It is the process of combining, summarizing, and reanalyzing previous quantitative
research. It yields a quantitative summary of the pooled results.
Decisions of the validity of a hypothesis cannot be based on the results of a single study,
because results typically vary from one study to the next. Traditional methods do not allow
involving more than a few studies. Meta analysis provides certain procedures to synthesize data
across studies. When the treatment effect (or effect size) is consistent from one study to the next,
meta-analysis can be used to identify this common effect. When the effect varies from one study
to the next, meta-analysis may be used to identify the reason for the variation.
The amount of accumulated information in fast developing fields of science such as
biology, medicine, education, pharmacology, physics, etc. increased very quickly after the
Second World War. This lead to large amounts of literature which was not systematized. One
problem in education might include ten independent studies. All of the studies might be
performed by different researchers, using different techniques, and different measurements. The idea of integrating the research literature was proposed by Glass (1976, 1977). He referred it as the meta analysis of research.
There are three major meta analysis approaches: combining significance levels,
combining estimates of effect size for fixed effect size models and random effect size models,
and vote-counting method.
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Adherence in Exercise Meta-Analyses: Assessment and Effect on Study OutcomesBae, Jeffrey, Kobleski, Robert January 2005 (has links)
Class of 2005 Abstract / Objective: The purpose of this study was to explore whether current meta-analyses on exercise interventions assess adherence and/or compliance of the studies included in the meta-analyses and to determine if subject adherence had any effect on outcomes of the analyses.
Methods: Data was collected through a search of the MEDLINE database using the key words exercise, adherence, compliance, clinical trials, and meta-analysis. Data on study title, author, number of studies screened, number in meta-analysis, range of sample sizes, total number of subjects, primary intervention, primary outcome, how study quality was assessed, how adherence was assessed, whether adherence was used as a control variable, and did adherence affect the outcome was recorded on a paper and pencil data extraction form. Data was analyzed by constructing a table describing the meta-analyses and calculating the number and percent of analyses that included adherence. The table allowed for the evaluation of the strength and methodology of each piece of literature with respect to acknowledging adherence as a significant variable in the strength and legitimacy of each analysis.
Results: Nineteen meta-analyses met our search criteria and were evaluated. Five of the nineteen meta-analyses (26 percent) described a method for assessing adherence. It was found that none of these used adherence as a control variable. Four of the nineteen meta-analyses did not assess the quality of the studies contained within the analysis. One of these meta-analyses suggested that adherence may have confounded outcomes, but did not provide any data to address their concerns.
Conclusions: In meta-analyses, adherence is unlikely to be addressed. Current meta-analyses frequently lack methods for assessing adherence, and do not use adherence as a control variable. Whether adherence to exercise regimens affects outcomes cannot be determined from current meta-analyses.
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