{"id":10563,"date":"2025-05-23T08:23:32","date_gmt":"2025-05-23T06:23:32","guid":{"rendered":"https:\/\/dpc-software.de\/?p=10563"},"modified":"2025-05-23T08:25:44","modified_gmt":"2025-05-23T06:25:44","slug":"statanow-update-mai-2025","status":"publish","type":"post","link":"https:\/\/dpc-software.de\/en\/statanow-update-mai-2025\/","title":{"rendered":"StataNow Update May 2025"},"content":{"rendered":"<h3 data-start=\"57\" data-end=\"124\"><strong data-start=\"60\" data-end=\"124\">New in StataNow 19.5: Power Analysis for Logistic Regression<\/strong><\/h3>\n<p data-start=\"126\" data-end=\"408\">With the May 21, 2025 update, we\u2019re excited to introduce the first major highlight in <strong data-start=\"212\" data-end=\"229\">StataNow 19.5<\/strong>: <strong data-start=\"231\" data-end=\"273\">power analysis for logistic regression<\/strong>. This powerful feature helps researchers make informed decisions about study design and sample size\u2014without wasting time or resources.<\/p>\n<h4 data-start=\"410\" data-end=\"429\"><strong data-start=\"414\" data-end=\"429\">What\u2019s New?<\/strong><\/h4>\n<p data-start=\"431\" data-end=\"733\">Whether you\u2019re analyzing marketing conversion rates (purchased vs. not purchased), medical recovery outcomes (recovered vs. not recovered), or digital user behavior (subscribed vs. not subscribed), the new <code data-start=\"637\" data-end=\"653\">power logistic<\/code> command helps determine the optimal sample size for logistic regression models.<\/p>\n<p data-start=\"735\" data-end=\"762\">This command allows you to:<\/p>\n<ul data-start=\"764\" data-end=\"953\">\n<li data-start=\"764\" data-end=\"868\">\n<p data-start=\"766\" data-end=\"868\">Calculate sample size, power, or effect size for testing a coefficient in a logistic regression model.<\/p>\n<\/li>\n<li data-start=\"869\" data-end=\"953\">\n<p data-start=\"871\" data-end=\"953\">Specify multiple parameter values and generate both tabular and graphical outputs.<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"955\" data-end=\"1206\">For example, suppose your binary outcome variable Y is influenced by two binary covariates\u2014X as the variable of interest and Z as a nuisance variable. To calculate the sample size needed for 80% power with a 5% significance level, you can simply type:<\/p>\n<div class=\"contain-inline-size rounded-md border-[0.5px] border-token-border-medium relative bg-token-sidebar-surface-primary\">\n<div class=\"sticky top-9\">\n<div class=\"absolute end-0 bottom-0 flex h-9 items-center pe-2\"><\/div>\n<\/div>\n<div class=\"overflow-y-auto p-4\" dir=\"ltr\"><code class=\"whitespace-pre!\">. power logistic <span class=\"hljs-number\">1.5<\/span>, <span class=\"hljs-built_in\">px<\/span>(<span class=\"hljs-number\">0.3<\/span>) <span class=\"hljs-built_in\">pz<\/span>(<span class=\"hljs-number\">0.2<\/span>) <span class=\"hljs-built_in\">py<\/span>(<span class=\"hljs-number\">0.6<\/span>) <span class=\"hljs-built_in\">pycondx1z1<\/span>(<span class=\"hljs-number\">0.8<\/span>)<br \/>\n<\/code><\/div>\n<\/div>\n<p data-start=\"1279\" data-end=\"1449\">But that\u2019s not all: the command also supports power analysis for more complex models, allowing up to <strong data-start=\"1380\" data-end=\"1406\">20 nuisance covariates<\/strong> drawn from <strong data-start=\"1418\" data-end=\"1448\">11 different distributions<\/strong>.<\/p>\n<h4 data-start=\"1451\" data-end=\"1491\"><strong data-start=\"1455\" data-end=\"1491\">What Makes This Feature Special?<\/strong><\/h4>\n<p data-start=\"1493\" data-end=\"1790\">The method implemented in <code data-start=\"1519\" data-end=\"1535\">power logistic<\/code> is recognized as one of the <strong data-start=\"1564\" data-end=\"1581\">most accurate<\/strong> available, and Stata is one of the <strong data-start=\"1617\" data-end=\"1645\">few statistical packages<\/strong> to offer it. It combines precision with Stata\u2019s well-known ease of use and flexibility\u2014making even complex model specifications straightforward.<\/p>\n<h4 data-start=\"1792\" data-end=\"1816\"><strong data-start=\"1796\" data-end=\"1816\">Who Is This For?<\/strong><\/h4>\n<p data-start=\"1818\" data-end=\"2225\">This new feature is especially useful for users in <strong data-start=\"1869\" data-end=\"1923\">medicine, epidemiology, public health, and ecology<\/strong> who frequently perform logistic regression analysis. They benefit from an accurate and user-friendly tool to conduct power analysis efficiently\u2014whether for study planning or for analyzing complex relationships. And for anyone working with binary outcomes in other fields, this feature adds real value.<\/p>\n<p data-start=\"2232\" data-end=\"2392\">\u00a0Learn more about the new feature at: <a class=\"\" href=\"https:\/\/stata.com\/statanow\/power-analysis-logistic-regression\/\" target=\"_new\" rel=\"noopener\" data-start=\"2272\" data-end=\"2392\">stata.com\/statanow\/power-analysis-logistic-regression\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>New in StataNow 19.5: Power Analysis for Logistic Regression With the May 21, 2025 update, we\u2019re excited to introduce the first major highlight in StataNow 19.5: power analysis for logistic regression. This powerful feature helps researchers make informed decisions about study design and sample size\u2014without wasting time or resources. What\u2019s New? Whether you\u2019re analyzing marketing [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":10567,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"categories":[15],"tags":[],"class_list":["post-10563","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>StataNow Update May 2025 - DPC Software GmbH<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dpc-software.de\/en\/statanow-update-mai-2025\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"StataNow Update May 2025 - DPC Software GmbH\" \/>\n<meta property=\"og:description\" content=\"New in StataNow 19.5: Power Analysis for Logistic Regression With the May 21, 2025 update, we\u2019re excited to introduce the first major highlight in StataNow 19.5: power analysis for logistic regression. 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