[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-652559-105":59,"doc-detail-652559-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","gpower-31-manual-june-1-2023","G*Power 3.1 manual - June 1, 2023","","G*Power 3.1 manual describes statistical power analyses for multiple test families, including F tests, t tests, chi-square (χ2) tests, z tests, and several exact tests. It explains how G*Power offers effect size calculators, graphics options, and both distribution-based and design-based input modes. The manual also outlines five analysis types—A priori, Compromise, Criterion, Post-hoc, and Sensitivity—and a typical workflow: select the test, choose the analysis type, enter required parameters, and calculate. It further introduces plotting parameters to explore the parameter space.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":30,"@type":76,"position":81},"https://docshare.wps.com/document/technology/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/gpower-31-manual-june-1-2023/652559/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/gpower-31-manual-june-1-2023/652559.png","ImageObject",300,407,{"name":92,"@type":93},"eBook King","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-10-24",true,{"@type":102,"interactionType":103,"userInteractionCount":19},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What types of statistical power analysis does G*Power 3.1 support?","Question",{"text":112,"@type":113},"G*Power provides five types: A priori, Compromise, Criterion, Post-hoc, and Sensitivity. Each computes key quantities using different inputs such as power (1−β), significance level α, effect size, and sample size N.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How do you perform a power analysis workflow in G*Power?",{"text":117,"@type":113},"Select the appropriate statistical test, choose one of the five analysis types, then provide the required input parameters and click “Calculate”. The program also supports plotting one parameter as a function of another to explore the relevant parameter space.",{"name":119,"@type":110,"acceptedAnswer":120},"What is the difference between distribution-based and design-based test selection?",{"text":121,"@type":113},"Distribution-based selection first chooses the family of the test statistic (exact, F, t, χ2, or z) and then selects the specific test. Design-based selection uses a parameter class and study design in a tests menu, grouping related options (e.g., means) closer together.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},652559,1792917436,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":29,"category_name":30,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":19,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962088006270,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","G * Power 3. 1 manual June 1, 2023  \nThis manual is not yet complete. We will be adding help on more tests in the future. If you cannot find help for your test in this version of the manual, then please check the G*Power website to see if a more up-to-date version of the manual has been made available.  \nContents  \n1 Introduction 2  \n2 The G * Power calculator 7  \n3 Exact: Correlation-Difference from constant (one sample case) 9  \n4 Exact: Proportion - difference from constant (one sample case) 11  \n5 Exact: Proportion - inequality, two dependent groups (McNemar) 14  \n6 Exact: Proportions-inequality of two independent groups (Fisher’s exact-test) 17  \n7 Exact test: Multiple Regression-random model 18  \n8 Exact: Proportion-sign test 22  \n9 Exact: Generic binomial test 23  \n10 F test: Fixed effects ANOVA-one way 24  \n11 F test: Fixed effects ANOVA-special, main effects and interactions 26  \n12 t test: Linear Regression (size of slope, one group) 31  \n13 F test: Multiple Regression-omnibus (deviation of R2 from zero), fixed model 33  \n14 F test: Multiple Regression - special (increase of R2 ), fixed model 36  \n15 F test: Inequality of two Variances 39  \n16 t test: Correlation-point biserial model 40  \n17 t test: Linear Regression (two groups) 42  \n18 t test: Linear Regression (two groups) 45  \n19 t test: Means-difference between two dependent means (matched pairs) 48  \n20 t test: Means-difference from constant (one sample case) 50  \n21 t test: Means-difference between two independent means (two groups) 52  \n22 Wilcoxon signed-rank test: Means-difference from constant (one sample case) 53  \n23 Wilcoxon signed-rank test: (matched pairs) 55  \n24 Wilcoxon-Mann-Whitney test of a difference between two independent means 59  \n25 t test: Generic case 63  \n26 χ2 test: Variance - difference from constant (one sample case) 64  \n27 z test: Correlation-inequality of two independent Pearson r’s 65  \n28 z test: Correlation - inequality of two dependent Pearson r’s 66  \n29 Z test: Multiple Logistic Regression 70  \n30 Z test: Poisson Regression 75  \n31 Z test: Tetrachoric Correlation 80  \nReferences 84  \n1 Introduction  \nG * Power (Fig. 1 shows the main window of the program) covers statistical power analyses for many different statistical tests of the  \n• F test,  \n• t test,  \n• χ2-test and  \n• z test families and some  \n• exact tests.  \nG * Power provides effect size calculators and graphics options. G * Power supports both a distribution-based anda design-based input mode. It contains also a calculator that supports many central and noncentral probability distributions.  \nG * Power is free software and available for Mac OS X and Windows XP/Vista/7/8 .  \n1.1 Types of analysis  \nG * Power offers five different types of statistical power analysis:  \n1. A priori (sample size N is computed as a function of power level 1 − β, significance level α, and the to-bedetected population effect size)  \n2. Compromise (both α and 1 − β are computed as functions of effect size, N, and an error probability ratio q = β/α)  \n3. Criterion (α and the associated decision criterion are computed as a function of 1 − β, the effect size, and N)  \n4. Post-hoc (1 − β is computed as a function of α, the population effect size, and N)  \n5. Sensitivity (population effect size is computed as a function of α, 1 − β, and N)  \n1.2 Program handling  \nPerform a Power Analysis Using G * Power typically involves the following three steps:  \n1. Select the statistical test appropriate for your problem.  \n2. Choose one of the five types of power analysis available  \n3. Provide the input parameters required for the analysis and click \"Calculate\".  \nPlot parameters In order to help you explore the parameter space relevant to your power analysis, one parameter (α, power (1 − β), effect size, or sample size) can be plotted as a function of another parameter.  \n1.2.1 Select the statistical test appropriate for your problem  \nIn Step 1, the statistical test is chosen using the distributionba","cbCaiqfuQZtCHr6X","https://ap.wps.com/l/cbCaiqfuQZtCHr6X","pdf",3664779,85,"English","# Introduction\n## Types of analysis\n## Program handling\n### Select the statistical test appropriate for your problem\n### Choose one of the five types of power analysis available\n### Plot parameters","[{\"question\":\"What types of statistical power analysis does G*Power 3.1 support?\",\"answer\":\"G*Power provides five types: A priori, Compromise, Criterion, Post-hoc, and Sensitivity. Each computes key quantities using different inputs such as power (1−β), significance level α, effect size, and sample size N.\"},{\"question\":\"How do you perform a power analysis workflow in G*Power?\",\"answer\":\"Select the appropriate statistical test, choose one of the five analysis types, then provide the required input parameters and click “Calculate”. The program also supports plotting one parameter as a function of another to explore the relevant parameter space.\"},{\"question\":\"What is the difference between distribution-based and design-based test selection?\",\"answer\":\"Distribution-based selection first chooses the family of the test statistic (exact, F, t, χ2, or z) and then selects the specific test. Design-based selection uses a parameter class and study design in a tests menu, grouping related options (e.g., means) closer together.\"}]","G*Power 3.1 manual - June 1, 2023 | PDF",1792881139,214]