Dear All,
I want to create a bar graph that compares change in the outcome variable at the level of county versus state by the rank variable
To plot the county and state bars next to each other I tried the following:
But I got an error.
However, ideally, I want to show the county and state bars next to each other and I want the x axis to simply show the 4 quartiles [1-4] with the distinction between the pre_rateq for county and pre_rateq_s for state only in the background. [NOTE:
I want to create a bar graph that compares change in the outcome variable at the level of county versus state by the rank variable
pre_rateq and pre_rateq_s respectively
. Both pre_rateq and pre_rateq_s take the values 1-4 and reflect quartiles.
My data is an annual panel as follows:Code:
Code:* Example generated by -dataex-. To install: ssc install dataex clear input byte state int county float(year pre_rateq pre_rateq_s avgdeloxy_mme_pc avgdeloxy_mme_pc_s) 1 1 2006 3 3 -.01886584 -.033673316 1 1 2007 3 3 -.01886584 -.033673316 1 1 2008 3 3 -.01886584 -.033673316 1 1 2009 3 3 -.01886584 -.033673316 1 1 2010 3 3 -.01886584 -.033673316 1 1 2011 3 3 -.01886584 -.033673316 1 1 2012 3 3 -.01886584 -.033673316 1 1 2013 3 3 -.01886584 -.033673316 1 1 2014 3 3 -.01886584 -.033673316 1 1 2015 3 3 -.01886584 -.033673316 1 1 2016 3 3 -.01886584 -.033673316 1 1 2017 3 3 -.01886584 -.033673316 1 3 2006 4 3 -.0551143 -.033673316 1 3 2007 4 3 -.0551143 -.033673316 1 3 2008 4 3 -.0551143 -.033673316 1 3 2009 4 3 -.0551143 -.033673316 1 3 2010 4 3 -.0551143 -.033673316 1 3 2011 4 3 -.0551143 -.033673316 1 3 2012 4 3 -.0551143 -.033673316 1 3 2013 4 3 -.0551143 -.033673316 1 3 2014 4 3 -.0551143 -.033673316 1 3 2015 4 3 -.0551143 -.033673316 1 3 2016 4 3 -.0551143 -.033673316 1 3 2017 4 3 -.0551143 -.033673316 1 5 2006 2 3 -.007270626 -.033673316 1 5 2007 2 3 -.007270626 -.033673316 1 5 2008 2 3 -.007270626 -.033673316 1 5 2009 2 3 -.007270626 -.033673316 1 5 2010 2 3 -.007270626 -.033673316 1 5 2011 2 3 -.007270626 -.033673316 1 5 2012 2 3 -.007270626 -.033673316 1 5 2013 2 3 -.007270626 -.033673316 1 5 2014 2 3 -.007270626 -.033673316 1 5 2015 2 3 -.007270626 -.033673316 1 5 2016 2 3 -.007270626 -.033673316 1 5 2017 2 3 -.007270626 -.033673316 1 7 2006 4 3 -.0551143 -.033673316 1 7 2007 4 3 -.0551143 -.033673316 1 7 2008 4 3 -.0551143 -.033673316 1 7 2009 4 3 -.0551143 -.033673316 1 7 2010 4 3 -.0551143 -.033673316 1 7 2011 4 3 -.0551143 -.033673316 1 7 2012 4 3 -.0551143 -.033673316 1 7 2013 4 3 -.0551143 -.033673316 1 7 2014 4 3 -.0551143 -.033673316 1 7 2015 4 3 -.0551143 -.033673316 1 7 2016 4 3 -.0551143 -.033673316 1 7 2017 4 3 -.0551143 -.033673316 1 9 2006 3 3 -.01886584 -.033673316 1 9 2007 3 3 -.01886584 -.033673316 1 9 2008 3 3 -.01886584 -.033673316 1 9 2009 3 3 -.01886584 -.033673316 1 9 2010 3 3 -.01886584 -.033673316 1 9 2011 3 3 -.01886584 -.033673316 1 9 2012 3 3 -.01886584 -.033673316 1 9 2013 3 3 -.01886584 -.033673316 1 9 2014 3 3 -.01886584 -.033673316 1 9 2015 3 3 -.01886584 -.033673316 1 9 2016 3 3 -.01886584 -.033673316 1 9 2017 3 3 -.01886584 -.033673316 1 11 2006 1 3 -.0007063786 -.033673316 1 11 2007 1 3 -.0007063786 -.033673316 1 11 2008 1 3 -.0007063786 -.033673316 1 11 2009 1 3 -.0007063786 -.033673316 1 11 2010 1 3 -.0007063786 -.033673316 1 11 2011 1 3 -.0007063786 -.033673316 1 11 2012 1 3 -.0007063786 -.033673316 1 11 2013 1 3 -.0007063786 -.033673316 1 11 2014 1 3 -.0007063786 -.033673316 1 11 2015 1 3 -.0007063786 -.033673316 1 11 2016 1 3 -.0007063786 -.033673316 1 11 2017 1 3 -.0007063786 -.033673316 1 13 2006 2 3 -.007270626 -.033673316 1 13 2007 2 3 -.007270626 -.033673316 1 13 2008 2 3 -.007270626 -.033673316 1 13 2009 2 3 -.007270626 -.033673316 1 13 2010 2 3 -.007270626 -.033673316 1 13 2011 2 3 -.007270626 -.033673316 1 13 2012 2 3 -.007270626 -.033673316 1 13 2013 2 3 -.007270626 -.033673316 1 13 2014 2 3 -.007270626 -.033673316 1 13 2015 2 3 -.007270626 -.033673316 1 13 2016 2 3 -.007270626 -.033673316 1 13 2017 2 3 -.007270626 -.033673316 1 15 2006 4 3 -.0551143 -.033673316 1 15 2007 4 3 -.0551143 -.033673316 1 15 2008 4 3 -.0551143 -.033673316 1 15 2009 4 3 -.0551143 -.033673316 1 15 2010 4 3 -.0551143 -.033673316 1 15 2011 4 3 -.0551143 -.033673316 1 15 2012 4 3 -.0551143 -.033673316 1 15 2013 4 3 -.0551143 -.033673316 1 15 2014 4 3 -.0551143 -.033673316 1 15 2015 4 3 -.0551143 -.033673316 1 15 2016 4 3 -.0551143 -.033673316 1 15 2017 4 3 -.0551143 -.033673316 1 17 2006 4 3 -.0551143 -.033673316 1 17 2007 4 3 -.0551143 -.033673316 1 17 2008 4 3 -.0551143 -.033673316 1 17 2009 4 3 -.0551143 -.033673316 end
Code:
graph bar avgdeloxy_mme_pc avgdeloxy_mme_pc_s, over(pre_rateq pre_rateq_s, relabel(1 "Q > uartile 1" 2 "Quartile 2" 3 "Quartile 3" 4 "Quartile 4")) ytitle(∆ orig. OxyContin supp > ly rate, margin(vlarge)) /// > leg(order(1 "County" 2 "State")) too many variables specified r(103);
I am able to separately plot
avgdeloxy_mme_pc against pre_rateq and in another bar graph avgdeloxy_mme_pc_s againt pre_rateq_s as follows:
Code:
graph bar avgdeloxy_mme_pc, over(pre_rateq, relabel(1 "Quartile 1" 2 "Quartile 2" 3 "Quartile 3" 4 "Quartile 4")) ytitle(∆ orig. OxyContin supply rate, margin(vlarge)) name(a) graph bar avgdeloxy_mme_pc_s, over(pre_rateq_s, relabel(1 "Quartile 1" 2 "Quartile 2" 3 "Quartile 3" 4 "Quartile 4")) ytitle(∆ orig. OxyContin supply rate, margin(vlarge)) name(b) graph combine a b
pre_rateq for county and pre_rateq_s for state are not perfectly correlated. Counties in the first county quartile may be fourth state quartile].
I will grateful for any help you may be able to offer.
Sincerely,
Sumedha.
I will grateful for any help you may be able to offer.
Sincerely,
Sumedha.
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