G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
Click on the Download link (shown above), which is located in the upper-right corner of the List tab on the Search Results page. A pop-up box containing download options will appear:
Use the dropdown menu to choose which table columns are downloaded for each study and in what format: Displayed Columns. Choose this option to download only table columns shown onscreen. The default study columns shown onscreen are Row, Status, Study Title, Condition and Interventions. To change which columns are shown in your search results, close the window you are in, click on the Show/Hide Columns link (located on the right side of the search results List tab), and then add or remove columns by marking or unmarking the column names. All Available Columns. Choose this option to download all available table columns. Includes over 20 columns such as Status, Conditions, Interventions, Study Type, Phase, and Sponsor/Collaborators. For more information about columns, see Customize Your Search Results Display. Select file format.
To immediately begin downloading study records (that is, all registration information as well as any available results information) for the studies found by your search, add \"download_fields\" between \"results/\" and \"\" in \"search request\" URL, and one or more of the following URL parameters to the end of the \"search request\" URL: Parameter Options* Description down_count Number of records to download: 10, 100, 1000, 10000 Specify if the top 10, 100, 1000, or 10,000 (maximum) studies retrieved by your search are to be downloaded. down_flds Fields to download: all, default Specify \"all\" available fields listed in the Show/Hide Columns window or \"default\" fields (including Title, Status, Has Study Results, Conditions, and Interventions) in the download file. down_fmt File format: plain, csv, tsv, xml, pdf Specify the format of the downloaded file. (See Select File Format) down_chunk Set of records to download: 1, 2, 3,...,N Specify which set of records to include in the downloaded file relative to the option selected for the down_count parameter. For example, down_chunk=1 when down_count=10 indicates the first set of 10 study records (i.e., rows 1 to 10 on the Search Results List). For down_chunk=2 when down_count=10, the second set 10 study records (i.e., rows 11 to 20) is downloaded. *Bold text indicates the default setting for each parameter (used if that parameter is missing/not specified) Example: _fieldscond=cancer&down_count=10 Entering the above URL in a browser searches for \"cancer\" in the Other Terms search field and downloads a PDF file (default file format when down_fmt is missing) that includes the default fields (when down_flds is missing) for the top 10 studies listed in rows 1 to 10 of the Search Results List (default when down_chunk is missing). To download the \"second set\" of 10 study records (that is, rows 11 to 20) for the same search as a plain text file, use the following URL: Example: _fieldscond=cancer&down_count=10&down_fmt=plain&down_chunk=2 Display a Single Record in XML To display an individual study protocol record in your browser in XML, add the URL parameter \"displayxml=true\" to the end of a \"show study\" URL:
To immediately begin downloading study records (that is, all registration information as well as any available results information) in XML, add \"download fields\" between \"results/\" and \"\" in \"search request\" URL. Optionally, append the \"down_chunk URL parameter to the end of a \"search request\" URL as described previously:
Note: This is a very large file. It will likely take several minutes to download the entire zip file. Additionally, many receiving systems may subject the zip file to automatic security/virus scanning. This scanning may take several additional minutes to complete before the zip file is ready for use. Please be patient.
Lastly once you have file downloaded on computer, make sure you have real time anti-malware protection. It will be your second layer of defense to detect unknown malware and protect if something still goes wrong.
Our second contribution is to harmonize, synthesize and meta-analyse the existing evidence, with special attention to variation across different subpopulations and country contexts. On the basis of the identified studies, we ask (4) to what extent has the learning progress of school-aged children changed since the onset of the pandemic, (5) how has the magnitude of the learning deficit (if any) evolved since the beginning of the pandemic, (6) to what extent has the pandemic reinforced inequalities between children from different socio-economic backgrounds, (7) are there differences in the magnitude of learning deficits between subject domains (maths and reading) and between age groups (primary and secondary students) and (8) to what extent does the magnitude of learning deficits vary across national contexts
We assessed the quality of the evidence using an adapted version of the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool9. More specifically, we analysed the risk of bias of each estimate from confounding, sample selection, classification of treatments, missing data, the measurement of outcomes and the selection of reported results. A.M.B.-M. and B.A.B. performed the risk-of-bias assessments, which were independently checked by the respective other author. We then assigned each study an overall risk-of-bias rating (low, moderate, serious or critical) based on the estimate and domain with the highest risk of bias.
Two years since the COVID-19 pandemic, there is a growing number of studies examining the learning progress of school-aged children during the pandemic. This paper first systematically reviews the existing literature on learning progress of school-aged children during the pandemic and appraises its geographic reach and quality. Second, it harmonizes, synthesizes and meta-analyses the existing evidence to examine the extent to which learning progress has changed since the onset of the pandemic, and how it varies across different groups of students and across country contexts.
The data used in the analyses for this manuscript were compiled by the authors based on the studies identified in the systematic review. The data are available on the Open Science Framework repository ( ). For our systematic review, we searched the following databases: Coronavirus Research Database ( ), Education Resources Information Centre database ( ), International Bibliography of the Social Sciences ( -services/ibss-set-c/), Politics Collection ( -services/ProQuest-Politics-Collection/), Social Science Database ( -services/pq_social_science/), Sociology Collection ( -services/ProQuest-Sociology-Collection/), Cumulative Index to Nursing and Allied Health Literature ( -databases/cinahl-database) and Web of Science ( -of-science/). We also searched the following preprint and working paper repositories: Social Science Research Network ( ), Munich Personal RePEc Archive ( -muenchen.de), IZA ( ), National Bureau of Economic Research ( =1&perPage=50&sortBy=public_date), OSF Preprints ( ), PsyArXiv ( ), SocArXiv ( ) and EdArXiv ( ). 59ce067264