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"content": "<p>When performing multiple imputation of missing data, it is essential to evaluate how the imputed values compare to the observed data.</p><p>The attached image, created with the bwplot() function, showcases how the distributions of observed and imputed values vary across different imputations for multiple variables.</p><p>I’ll be hosting an 8-week online workshop on Missing Data Imputation in R: <a href=\"https://statisticsglobe.com/online-workshop-missing-data-imputation-r\" target=\"_blank\" rel=\"nofollow noopener\" translate=\"no\"><span class=\"invisible\">https://</span><span class=\"ellipsis\">statisticsglobe.com/online-wor</span><span class=\"invisible\">kshop-missing-data-imputation-r</span></a></p><p><a href=\"https://mastodon.social/tags/dataanalytics\" class=\"mention hashtag\" rel=\"tag\">#<span>dataanalytics</span></a> <a href=\"https://mastodon.social/tags/dataviz\" class=\"mention hashtag\" rel=\"tag\">#<span>dataviz</span></a> <a href=\"https://mastodon.social/tags/statistical\" class=\"mention hashtag\" rel=\"tag\">#<span>statistical</span></a> <a href=\"https://mastodon.social/tags/database\" class=\"mention hashtag\" rel=\"tag\">#<span>database</span></a> <a href=\"https://mastodon.social/tags/datavisualization\" class=\"mention hashtag\" rel=\"tag\">#<span>datavisualization</span></a> <a href=\"https://mastodon.social/tags/package\" class=\"mention hashtag\" rel=\"tag\">#<span>package</span></a></p>",
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