{"id":8543,"date":"2022-04-28T21:14:23","date_gmt":"2022-04-28T21:14:23","guid":{"rendered":"https:\/\/www.tun.com\/courses\/2019\/12\/23\/dealing-with-missing-data\/"},"modified":"2022-04-28T21:14:23","modified_gmt":"2022-04-28T21:14:23","slug":"dealing-with-missing-data","status":"publish","type":"post","link":"https:\/\/www.tun.com\/courses\/dealing-with-missing-data\/university-of-maryland-college-park\/","title":{"rendered":"Dealing With Missing Data"},"content":{"rendered":"<div class=\"single_post\" style=\"margin-top:16px;\";>\n<div class=\"post-single-content box mark-links entry-content\">\n<div class=\"thecontent\">\n<h2>Description<\/h2>\n<p>This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration.  Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation.  Alternative techniques for imputing values for missing items will be discussed.  For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R\u00ae, Stata\u00ae, and SAS\u00ae.<\/p>\n<div style=\"height:45px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<h2 class=\"has-text-align-center\">Price: Enroll For Free!<\/h2>\n<div style=\"height:45px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<div class=\"wp-block-button aligncenter\"><a class=\"wp-block-button__link has-text-color has-very-light-gray-color has-background has-vivid-red-background-color\" href=\"https:\/\/www.coursera.org\/learn\/missing-data\">View Class<\/a><\/div>\n<div style=\"height:55px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<div class=\"wp-block-columns\">\n<div class=\"wp-block-column\">\n<p class=\"has-text-align-center\"><em><strong>Language:<\/strong> <\/em>English<\/p>\n<\/div>\n<div class=\"wp-block-column\">\n<p class=\"has-text-align-center\"><em><strong>Subtitles<\/strong>: <\/em>English<\/p>\n<\/div>\n<\/div>\n<p style=\"background-color:#496d89\" class=\"has-text-color has-background has-text-align-center has-very-light-gray-color\"><a href=\"https:\/\/www.coursera.org\/learn\/missing-data\">Dealing With Missing Data<strong> &#8211; University of Maryland, College Park<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Description This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[261],"tags":[],"class_list":["post-8543","post","type-post","status-publish","format-standard","hentry","category-university-of-maryland-college-park"],"aioseo_notices":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"Axiom Pegasus","author_link":"https:\/\/www.tun.com\/courses\/author\/magic\/"},"uagb_comment_info":0,"uagb_excerpt":"Description This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For&hellip;","featured_media_src_url":null,"_links":{"self":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/8543","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/comments?post=8543"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/8543\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media?parent=8543"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/categories?post=8543"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/tags?post=8543"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}