{"id":6397,"date":"2020-03-02T09:44:47","date_gmt":"2020-03-02T09:44:47","guid":{"rendered":"https:\/\/www.enago.com\/academy\/tw\/?p=6397"},"modified":"2023-11-09T09:52:55","modified_gmt":"2023-11-09T09:52:55","slug":"free-ebook-on-a-guide-to-biostatistics-in-clinical-research","status":"publish","type":"post","link":"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/","title":{"rendered":"A Guide to Biostatistics in Clinical Research"},"content":{"rendered":"<p>Biostatistics in clinical research is important to collect, analyze, present, and interpret data. It finds applications in various fields such as epidemiology, clinical trials, population genetics, systems biology, and more. In clinical research, it helps in making decisions regarding the efficacy and safety of a drug, line of treatment, or therapy.<\/p>\n<p>This ebook gives an overview of the concepts in hypothesis testing, error types, power and sample size, interpreting relationship among variables, and multiplicity issue in clinical trials. This ebook will offer structured and comprehensive information to early-stage clinical researchers and students who are interested in learning about the use and interpretation of biostatistical data in clinical studies. This information will also help readers who want to understand the statistical approach and methods used in scientific research papers.<\/p>\n<p class=\"feeunaoa\"><strong><a href=\"https:\/\/app.monstercampaigns.com\/c\/jqecoiasoop2mn6ujoly\/\" target=\"_blank\" rel=\"noopener noreferrer\">Subscribe Now!<\/a> to download the ebook.<\/strong><\/p>\n<p>Here\u2019s what you can expect from &#8220;A Quick Guide to Biostatistics in Clinical Research&#8221;.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_74 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">\u5e38\u898b\u554f\u984c<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Hypothesis\" >Hypothesis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Hypothesis_Testing\" >Hypothesis Testing<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Types_of_Errors\" >Types of Errors<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Power_of_a_Statistical_Test\" >Power of a Statistical Test<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Sample_Size\" >Sample Size<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Relative_Risk_Odds_Ratio\" >Relative Risk &amp; Odds Ratio<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Correlation_Regression\" >Correlation &amp; Regression<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.enago.com\/academy\/tw\/free-ebook-on-a-guide-to-biostatistics-in-clinical-research\/#Multiplicity_Issue\" >Multiplicity Issue<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Hypothesis\"><\/span>Hypothesis<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A research process starts with identifying a gap in the knowledge area and framing a hypothesis to validate the prediction. In this section of the ebook, we will look at<\/p>\n<ol>\n<li>Definition and types of hypothesis<\/li>\n<li>Characteristics of a good hypothesis<\/li>\n<li>Study designs<\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"Hypothesis_Testing\"><\/span>Hypothesis Testing<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A hypothesis will be accepted or rejected based on the interpretation of supporting data. In this section, we will learn about<\/p>\n<ol>\n<li>Interpretation using p-value<\/li>\n<li>Misinterpretation of p-value<\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"Types_of_Errors\"><\/span>Types of Errors<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Sometimes, researchers may arrive at a wrong conclusion. In this section, we will learn about<\/p>\n<ol>\n<li>Types of errors<\/li>\n<li>How do these errors arise<\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"Power_of_a_Statistical_Test\"><\/span>Power of a Statistical Test<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Power of a statistical test is important to evaluate the likelihood of detecting an effect when it exists. In this section, we will look at<\/p>\n<ol>\n<li>Defining and interpreting power<\/li>\n<li>Factors influencing the power of a test<strong>\u00a0<\/strong><\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"Sample_Size\"><\/span>Sample Size<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>It is important to determine the appropriate sample size for a clinical researcher to observe the desired\/predicted effect. In this section, we will look at<\/p>\n<ol>\n<li>Understanding sample size<\/li>\n<li>Factors affecting sample size<\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"Relative_Risk_Odds_Ratio\"><\/span>Relative Risk &amp; Odds Ratio<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Relative risks and odds ratio are important parameters in epidemiology studies to arrive at a conclusion based on an association between an outcome and exposure. In this section, we will learn about<\/p>\n<ol>\n<li>Understanding relative risk and odds ratio<\/li>\n<li>Calculating these parameters<\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"Correlation_Regression\"><\/span>Correlation &amp; Regression<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Correlation and regression are important in evaluating the nature and strength of a relationship among different independent variables. In this section, we will learn about<\/p>\n<ol>\n<li>Understanding correlation and regression<\/li>\n<li>Interpreting results<\/li>\n<\/ol>\n<h2><span class=\"ez-toc-section\" id=\"Multiplicity_Issue\"><\/span>Multiplicity Issue<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Many times, clinical trials face issues due to multiple endpoints, subgroups or statistical tests, resulting in the false impression of relationships and associations. \u00a0In this section, we will learn about<\/p>\n<ol>\n<li>Why multiplicity issue arises and its implications<\/li>\n<li>Few ways to handle this issue<\/li>\n<\/ol>\n<p>This e-book is a quick guide to biostatistics for early-stage researchers, clinicians, and students.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Biostatistics in clinical research is important to collect, analyze, present, and interpret data. It finds [&hellip;]<\/p>\n","protected":false},"author":8203,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1211],"tags":[1077],"ppma_author":[1240],"class_list":["post-6397","post","type-post","status-publish","format-standard","hentry","category-free-resources","tag-tips-for-phd-students"],"better_featured_image":null,"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>A Guide to Biostatistics in Clinical Research - Enago\u82f1\u8ad6\u95a3 \u90e8\u843d\u683c\uff1a\u8ad6\u6587\u64b0\u5beb\u8207\u79d1\u5b78\u7814\u7a76\u767c\u8868\u652f\u63f4<\/title>\n<meta name=\"description\" content=\"This e-book gives an overview of biostatistics concepts in clinical trials including, hypothesis, power, sample size, regression, and more.\" \/>\n<meta name=\"robots\" content=\"index, follow, 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