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      “Using digital media or sleeping … that is the question”. A meta-analysis on digital media use and unhealthy sleep in adolescence

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      Computers in Human Behavior

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          Measuring inconsistency in meta-analyses.

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            Bias in meta-analysis detected by a simple, graphical test

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              A basic introduction to fixed-effect and random-effects models for meta-analysis.

              There are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. The fact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimates for the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the models represent fundamentally different assumptions about the data. The selection of the appropriate model is important to ensure that the various statistics are estimated correctly. Additionally, and more fundamentally, the model serves to place the analysis in context. It provides a framework for the goals of the analysis as well as for the interpretation of the statistics. In this paper we explain the key assumptions of each model, and then outline the differences between the models. We conclude with a discussion of factors to consider when choosing between the two models. Copyright © 2010 John Wiley & Sons, Ltd. Copyright © 2010 John Wiley & Sons, Ltd.
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                Author and article information

                Contributors
                Journal
                Computers in Human Behavior
                Computers in Human Behavior
                07475632
                September 2023
                September 2023
                : 146
                : 107813
                Article
                10.1016/j.chb.2023.107813
                12edcd76-38c5-4b8f-ab88-8ee267408c1c
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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