{"id":45854,"date":"2025-05-23T11:18:00","date_gmt":"2025-05-23T11:18:00","guid":{"rendered":"https:\/\/dpc-software.de\/statanow-update-may-2025\/"},"modified":"2026-10-05T08:54:44","modified_gmt":"2026-10-05T08:54:44","slug":"statanow-update-may-2025","status":"publish","type":"post","link":"https:\/\/dpc-software.de\/nl\/statanow-update-may-2025\/","title":{"rendered":"StataNow Update May 2025"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\"><strong>New in StataNow 19.5: Power Analysis for Logistic Regression <\/strong><\/h3>\n\n<p class=\"wp-block-paragraph\">With the update from May 21, 2025, we are pleased to introduce the first new highlight in <strong>StataNow 19.5<\/strong>: <strong>power analysis for logistic regression<\/strong>. This powerful feature supports researchers in making informed decisions about study design and sample size\u2014without wasting unnecessary resources.  <\/p>\n\n<h4 class=\"wp-block-heading\"><strong>What\u2019s New?<\/strong> <\/h4>\n\n<p class=\"wp-block-paragraph\">Whether it involves conversion rates in marketing (purchased vs. not purchased), recovery progress in medicine (recovered vs. not recovered), or user behavior in digital products (subscribed vs. not subscribed)\u2014the new <code>power logistic<\/code> function helps calculate the optimal sample size for logistic regression models. <\/p>\n\n<p class=\"wp-block-paragraph\">With this command, you can: <\/p>\n\n<ul class=\"wp-block-list\">\n<li>Calculate sample size, power, or effect size for testing a coefficient in a logistic regression model. <\/li>\n\n\n\n<li>Specify multiple parameter values simultaneously and display results in both tabular and graphical formats. <\/li>\n<\/ul>\n\n<p class=\"wp-block-paragraph\">For example: Suppose your outcome variable <strong>Y<\/strong> is binary and you have two binary covariates\u2014<strong>X<\/strong> as the covariate of interest and <strong>Z<\/strong> as a nuisance covariate. To calculate the required sample size for 80% power at an \u03b1 of 5%, the following command is sufficient:  <\/p>\n\n<pre class=\"wp-block-code\"><code>. power logistic 1.5, px(0.3) pz(0.2) py(0.6) pycondx1z1(0.8)<\/code><\/pre>\n\n<p class=\"wp-block-paragraph\">But that\u2019s not all: The function also allows for power analyses for more complex models with up to <strong>20 nuisance covariates from 11 different distributions<\/strong>. <\/p>\n\n<h4 class=\"wp-block-heading\"><strong>What Makes This Feature Special?<\/strong> <\/h4>\n\n<p class=\"wp-block-paragraph\">The method used by <code>power logistic<\/code> is considered one of the <strong>most precise<\/strong> on the market\u2014and Stata is one of the <strong>few statistical packages<\/strong> that offers it at all. Furthermore, the typical Stata user-friendliness and flexibility are maintained: even complex models can be implemented easily.  <\/p>\n\n<h4 class=\"wp-block-heading\"><strong>Who Is This For?<\/strong> <\/h4>\n\n<p class=\"wp-block-paragraph\">The new function is primarily aimed at users in <strong>medicine, epidemiology, public health<\/strong>, and <strong>ecology<\/strong> who frequently work with <strong>logistic regression models<\/strong>. They benefit from the precise yet user-friendly way to perform power analyses efficiently\u2014whether planning studies or analyzing complex relationships. The feature also offers clear added value in other fields with <strong>binary outcomes<\/strong>.   <\/p>\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.stata.com\/news\/statanow-updates\/\" data-type=\"link\" data-id=\"https:\/\/www.stata.com\/news\/statanow-updates\/\">Discover all StataNow innovations.<\/a><\/p>\n\n<p class=\"wp-block-paragraph\">If you have any questions, please feel free to contact us:<strong> <a>Info@dpc-software.de<\/a><\/strong><\/p>\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>New in StataNow 19.5: Power Analysis for Logistic Regression With the update from May 21, 2025, we are pleased to introduce the first new highlight in StataNow 19.5: power analysis for logistic regression. This powerful feature supports researchers in making informed decisions about study design and sample size\u2014without wasting unnecessary resources. What\u2019s New? Whether it&hellip;<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[226],"tags":[],"class_list":["post-45854","post","type-post","status-publish","format-standard","hentry","category-statanow","category-226","description-off"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.7 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>StataNow Update May 2025 | DPC Software GmbH<\/title>\n<meta name=\"robots\" content=\"noindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<meta property=\"og:locale\" content=\"nl_NL\" \/>\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 update from May 21, 2025, we are pleased to introduce the first new highlight in StataNow 19.5: power analysis for logistic regression. This powerful feature supports researchers in making informed decisions about study design and sample size\u2014without wasting unnecessary resources. What\u2019s New? 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