{"id":5545,"date":"2017-12-30T02:05:12","date_gmt":"2017-12-30T07:05:12","guid":{"rendered":"http:\/\/www.thejuliagroup.com\/blog\/?p=5545"},"modified":"2017-12-30T02:05:12","modified_gmt":"2017-12-30T07:05:12","slug":"what-would-you-do-if-one-person-changed-your-results","status":"publish","type":"post","link":"https:\/\/www.thejuliagroup.com\/blog\/what-would-you-do-if-one-person-changed-your-results\/","title":{"rendered":"What would you do if one person changed your results?"},"content":{"rendered":"

This is a hypothetical question, but it could easily happen. Let me give you a real example.<\/p>\n

Using a mobile phone game, we administered a standard depression screening measure (CESD-C) to 18 children living on or near an American Indian reservation. All children had a family member who was an alcoholic or addicted to drugs.\u00a0 I decide to do a one-sample t-test of the hypothesis that the mean for this population = 15, which is the cutoff value for symptoms of depression .\u00a0 Here is the code but I didn’t code it (more about that later).
\n
\nPROC TTEST DATA=cesd_score SIDES=2 H0=15 plots(showh0);<\/code>
\nvar CESDTotal;<\/code><\/p>\n

The results are shown below, with\u00a0 a mean of 21 and a range from 3 to 38.<\/p>\n

\"ttest<\/a><\/p>\n

You can see that the t-value of 2.34 is significant at p < .05, that is the mean for this sample is significantly different than the cutoff score of 15. You can see more results here.<\/a>\u00a0 What if it hadn’t been, though? What if, instead of .0317 the probability was .0517?<\/p>\n

What if dropping out this one person with a score of 3 changed the result? In fact, it did change the mean to 22, and the p-value to .0115 . You can see all of those results here<\/a>.<\/p>\n

So, let’s say that hypothetically dropping out this outlier WOULD change your results. Would you do it? Would you report it?<\/h3>\n

Think about it. In a couple of days, I will give you my answer and my justification.<\/p>\n

As to not having coded it – I used the tasks in SAS Studio which I found to be pretty fun, but more on that in my next post.<\/p>\n

\n

Play Aztech: Meet the Maya – for your iPad in the app store, in Spanish and English.\u00a0 The second in our series of bilingual games teaching basic statistics and Latin American history. Only $1.99\u00a0<\/a><\/h2>\n

\"girl<\/a><\/p>\n

P.S. There is a third possibility here, which is changing the test from a two-tailed test to one-tailed test. Surely, an argument can be made that we don’t expect children with a family member who is addicted to alcohol or drugs to be\u00a0less<\/strong> depressed than the cut-off score? They would either be equal or more depressed. Personally, I don’t buy that argument. I could accept that the sample might be more depressed than the average but I’m not sure one could justify that the mean necessarily MUST be more than the cut-off for depressive symptoms.\u00a0<\/em><\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

This is a hypothetical question, but it could easily happen. Let me give you a real example. Using a mobile phone game, we administered a standard depression screening measure (CESD-C) to 18 children living on or near an American Indian reservation. All children had a family member who was an alcoholic or addicted to drugs.\u00a0…<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[9,11],"tags":[],"class_list":["post-5545","post","type-post","status-publish","format-standard","hentry","category-software","category-statistics"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/posts\/5545","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/comments?post=5545"}],"version-history":[{"count":2,"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/posts\/5545\/revisions"}],"predecessor-version":[{"id":5549,"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/posts\/5545\/revisions\/5549"}],"wp:attachment":[{"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/media?parent=5545"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/categories?post=5545"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.thejuliagroup.com\/blog\/wp-json\/wp\/v2\/tags?post=5545"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}