{"id":1220,"date":"2022-10-10T14:51:46","date_gmt":"2022-10-10T18:51:46","guid":{"rendered":"https:\/\/blog.uvm.edu\/tbplante\/?p=1220"},"modified":"2024-12-11T10:00:24","modified_gmt":"2024-12-11T15:00:24","slug":"making-a-scatterplot-with-r-squared-and-percent-coefficient-of-variation-in-stata","status":"publish","type":"post","link":"https:\/\/blog.uvm.edu\/tbplante\/2022\/10\/10\/making-a-scatterplot-with-r-squared-and-percent-coefficient-of-variation-in-stata\/","title":{"rendered":"Making a scatterplot with R squared and percent coefficient of variation in Stata"},"content":{"rendered":"\n

I recently had to make some scatterplots for Figure 3 of this paper<\/a>. I decided to clean up the code in case it might be helpful to others. <\/p>\n\n\n\n

The below code outputs a scatterplot with R-squared and %CV. I grabbed the %CV-from-a-regression code from Mehmet Mehmetoglu’s CV program. (Type –ssc install cv– to grab that one. It’s not needed for below.) By the way, you might also be interested in how to make a related Bland-Altman plot here.<\/a> <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Here’s the code:<\/p>\n\n\n\n

\/\/ note this uses local macros so you need to run this entire thing\n\/\/ top to bottom in a do file, not line by line. \n\/\/\n\/\/ Step 1: input some fake data:\nclear all\n\ninput id yvar xvar\n1 2 5\n2 3 5\n3 6 5\n4 7 7\n5 3 2\n6 10 12\n7 1 2\n8 11 12\n9 4 6\n10 5 5\nend\n\n\/\/ Step 2a: Grab the R2 from a regresssion\nregress yvar xvar\nlocal rsq = e(r2)\n\/\/ Step 2b, from the same regression, calculate the percent CV\nlocal  rmse= e(rmse)\nlocal depvar = e(depvar)\nsum `depvar' if e(sample), meanonly\nlocal depvarmean = r(mean)\nlocal cv = `rmse'\/`depvarmean'*100\n\n\/\/ Step 3: graph!\nset scheme s1mono \/\/ I like this scheme\n\ntwoway \/\/\/\n\/\/\/ Line of unity, you'll need to tweak the range for your data.\n\/\/\/ note that 'y' and 'x' are not the same as 'yvar' and 'xvar'\n\/\/\/ but are instead what's required here to print the line of\n\/\/\/ unity:\n(function y=x , range(0 12) lcolor(red) lpattern(solid) lwidth(medium)) \/\/\/\n\/\/\/ line of fit:\n(lfit yvar xvar,  lcolor(red) lpattern(dash) lwidth(medium)) \/\/\/\n\/\/\/ Scatter plot dots:\n(scatter yvar xvar, msymbol(O) msize(medium) mcolor(black)) \/\/\/\n, \/\/\/\naspect(1) \/\/\/ force output to be square\n\/\/\/ here's the text box with R2 and CV,\n\/\/\/ you'll need to tweak the first two numbers so the y,x\n\/\/\/ coordinates drop the text where you want it\ntext(12 0 \"{bf:R\u00b2=`:di %3.1f `=`rsq'''}\" \"{bf:CV=`:di %4.1f `=`cv'''%}\", placement(se) justification(left)) \/\/\/ \nlegend(off) \/\/\/ Shut off the legend\nyla(0(3)12, angle(0)) \/\/\/ you'll need to tweak range for your data\nxla(0(3)12) \/\/\/ you'll need to tweak range for your data\nytitle(\"yvar!\") \/\/\/\nxtitle(\"xvar!\") \/\/\/\ntitle(\"Title!\") <\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"
I recently had to make some scatterplots for Figure 3 of this paper. I decided to clean up the code in case it might be helpful to others. The below code outputs a scatterplot with R-squared and %CV. I grabbed the %CV-from-a-regression code from Mehmet Mehmetoglu’s CV program. (Type –ssc install cv– to grab that … Continue reading Making a scatterplot with R squared and percent coefficient of variation in Stata<\/span><\/a><\/p>\n","protected":false},"author":4473,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[477491],"tags":[394639,703412,393478,222041,703415,703411,703410,53641,579,703417,502556],"class_list":["post-1220","post","type-post","status-publish","format-standard","hentry","category-stata-code","tag-cv-2","tag-coefficient-of-variation","tag-cv","tag-epidemiology","tag-percent-coefficient-of-variation","tag-r-squared","tag-r2","tag-regression","tag-research","tag-scatterplot","tag-stata"],"_links":{"self":[{"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/posts\/1220","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/users\/4473"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/comments?post=1220"}],"version-history":[{"count":10,"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/posts\/1220\/revisions"}],"predecessor-version":[{"id":1996,"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/posts\/1220\/revisions\/1996"}],"wp:attachment":[{"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/media?parent=1220"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/categories?post=1220"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.uvm.edu\/tbplante\/wp-json\/wp\/v2\/tags?post=1220"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}