{"id":486,"date":"2015-07-17T15:47:17","date_gmt":"2015-07-17T15:47:17","guid":{"rendered":"http:\/\/labmath.org\/?p=486"},"modified":"2015-07-17T18:04:40","modified_gmt":"2015-07-17T18:04:40","slug":"streiner-does-it-again","status":"publish","type":"post","link":"http:\/\/labmath.org\/?p=486","title":{"rendered":"Streiner does it again"},"content":{"rendered":"

David Streiner, my favorite statistician (if that’s not obvious from other posts here), has been writing short pieces (that I wish I could have written) about important but often misunderstood or forgotten statistical topics. \u00a0 I just read one, about sample size and power, that makes these two uncomfortable topics very clear. \u00a0In particular, he uses a fabulous analogy to illustrate why sample size affects statistical significance, and I quote:<\/p>\n

“In general terms, the sample size of a study is analogous to the magnification of a microscope. The\u00a0smaller the object you are studying, the greater the magnification you need. Analogously, the smaller\u00a0the effect you wish to detect, the larger the sample size you will need.”<\/h3>\n

 <\/p>\n

Statistics Commentary Series: Commentary\u00a0#9\u2014Sample Size Made Easy (Power a Bit\u00a0Less So) \u00a0JOURNAL OF CLINICAL PSYCHOPHARMACOLOGY \u00b7 MARCH 2015\u00a0\u00b7 DOI: 10.1097\/JCP.0000000000000297 \u00b7 \u00a0<\/address>\n
http:\/\/www.researchgate.net\/publication\/273463222<\/span><\/a><\/span><\/address>\n
\u00a0<\/address>\n

The reason I like this analogy so much is that magnification is intuitively clear to just about anyone who has ever stood far away from something, then moved in for a closer look. \u00a0We know perfectly well that what we are looking at isn’t changing, but by changing position so that we can gather more information, we become more sure of what we are seeing. \u00a0By gathering more data (having a larger sample size), we can be more sure* (have better statistical significance) of what we are seeing.<\/p>\n

*Remember, p-values, which are what most people mean when they refer to statistical significance, only<\/em> tell you the probability that you have incorrectly found a difference between two treatments (a false positive), so the words “can be more sure” are on purpose\u00a0not<\/em> “can know.”<\/p>\n

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

David Streiner, my favorite statistician (if that’s not obvious from other posts here), has been writing short pieces (that I wish I could have written) about important but often misunderstood or forgotten statistical topics. \u00a0 I just read one, about sample size and power, that makes these two uncomfortable topics very clear. \u00a0In particular, he […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[],"_links":{"self":[{"href":"http:\/\/labmath.org\/index.php?rest_route=\/wp\/v2\/posts\/486"}],"collection":[{"href":"http:\/\/labmath.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/labmath.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/labmath.org\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/labmath.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=486"}],"version-history":[{"count":6,"href":"http:\/\/labmath.org\/index.php?rest_route=\/wp\/v2\/posts\/486\/revisions"}],"predecessor-version":[{"id":493,"href":"http:\/\/labmath.org\/index.php?rest_route=\/wp\/v2\/posts\/486\/revisions\/493"}],"wp:attachment":[{"href":"http:\/\/labmath.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=486"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/labmath.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=486"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/labmath.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=486"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}