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Confidence bands in ggplot2
4 messages · Abhijit Dasgupta, Christopher David Desjardins
You can easily do this by:
qplot(x=as.factor(sch),y=est, geom='point', colour='red') +
geom_pointrange(aes(x=as.factor(sch), y=est, ymin=lower.95ci, ymax=upper.95ci))+
xlab('School') + ylab("Value-added")+theme_bw()
On 07/07/2011 05:55 PM, Christopher Desjardins wrote:
Hi, I have the following data:
est
sch190 sch107 sch290 sch256 sch287 sch130 sch139
4.16656026 2.64306071 4.22579866 6.12024789 4.49624748 11.12799127 1.17353917
sch140 sch282 sch161 sch193 sch156 sch288 sch352
3.48197696 -0.29659410 -1.99194986 10.23489859 7.77342138 6.77624539 9.66795001
sch368 sch225 sch301 sch105 sch353 sch291 sch179
7.20229569 4.41989204 5.61586860 5.99460203 -2.65019242 -9.42614560 -0.25874193
sch134 sch135 sch324 sch360 bb1
3.26432479 10.52555091 -0.09637968 2.49668858 -3.24173545
se
sch190 sch107 sch290 sch256 sch287 sch130 sch139 sch140
3.165127 3.710750 4.680911 6.335386 3.896302 4.907679 4.426284 4.266303
sch282 sch161 sch193 sch156 sch288 sch352 sch368 sch225
3.303747 4.550193 3.995261 5.787374 5.017278 7.820763 7.253183 4.483988
sch301 sch105 sch353 sch291 sch179 sch134 sch135 sch324
4.076570 7.564359 10.456522 5.705474 4.247927 5.671536 10.567093 4.138356
sch360 bb1
4.943779 1.935142
sch
[1] "190" "107" "290" "256" "287" "130" "139" "140" "282" "161" "193" "156" "288"
[14] "352" "368" "225" "301" "105" "353" "291" "179" "134" "135" "324" "360" "BB"
From this data I have created 95% confidence intervals assuming a normal distribution.
lower.95ci<- est - se*qnorm(.975)
upper.95ci<- est + se*qnorm(.975)
What I'd like to do is plot the estimate (est) and have lines attach to the points located in lower.95ci and upper.95ci. Presently I am doing the following:
qplot(x=as.factor(sch),y=lower.95ci) + geom_point(aes(x=as.factor(sch),y=upper.95ci),colour="black") + geom_point(aes(x=as.factor(sch), y=est),colour="red") + ylab("Value-Added") + xlab("School") + theme_bw()
Which creates this graph ---> http://dl.dropbox.com/u/1501309/value_added_test.pdf
That's fine except that it doesn't connect the points vertically. Does anyone know how I could make the 'black' points connect to the 'red' point, i.e. show confidence bands?
Thanks,
Chris
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______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Thanks that worked perfectly. One thing if I may. Is it possible to make the center dot red and the lines connecting the dots black? Thanks, Chris
On Jul 7, 2011, at 5:10 PM, Abhijit Dasgupta, PhD wrote:
You can easily do this by:
qplot(x=as.factor(sch),y=est, geom='point', colour='red') +
geom_pointrange(aes(x=as.factor(sch), y=est, ymin=lower.95ci, ymax=upper.95ci))+
xlab('School') + ylab("Value-added")+theme_bw()
On 07/07/2011 05:55 PM, Christopher Desjardins wrote:
Hi, I have the following data:
est
sch190 sch107 sch290 sch256 sch287 sch130 sch139
4.16656026 2.64306071 4.22579866 6.12024789 4.49624748 11.12799127 1.17353917
sch140 sch282 sch161 sch193 sch156 sch288 sch352
3.48197696 -0.29659410 -1.99194986 10.23489859 7.77342138 6.77624539 9.66795001
sch368 sch225 sch301 sch105 sch353 sch291 sch179
7.20229569 4.41989204 5.61586860 5.99460203 -2.65019242 -9.42614560 -0.25874193
sch134 sch135 sch324 sch360 bb1
3.26432479 10.52555091 -0.09637968 2.49668858 -3.24173545
se
sch190 sch107 sch290 sch256 sch287 sch130 sch139 sch140 3.165127 3.710750 4.680911 6.335386 3.896302 4.907679 4.426284 4.266303 sch282 sch161 sch193 sch156 sch288 sch352 sch368 sch225 3.303747 4.550193 3.995261 5.787374 5.017278 7.820763 7.253183 4.483988 sch301 sch105 sch353 sch291 sch179 sch134 sch135 sch324 4.076570 7.564359 10.456522 5.705474 4.247927 5.671536 10.567093 4.138356 sch360 bb1 4.943779 1.935142
sch
[1] "190" "107" "290" "256" "287" "130" "139" "140" "282" "161" "193" "156" "288"
[14] "352" "368" "225" "301" "105" "353" "291" "179" "134" "135" "324" "360" "BB"
From this data I have created 95% confidence intervals assuming a normal distribution.
lower.95ci<- est - se*qnorm(.975)
upper.95ci<- est + se*qnorm(.975)
What I'd like to do is plot the estimate (est) and have lines attach to the points located in lower.95ci and upper.95ci. Presently I am doing the following:
qplot(x=as.factor(sch),y=lower.95ci) + geom_point(aes(x=as.factor(sch),y=upper.95ci),colour="black") + geom_point(aes(x=as.factor(sch), y=est),colour="red") + ylab("Value-Added") + xlab("School") + theme_bw()
Which creates this graph ---> http://dl.dropbox.com/u/1501309/value_added_test.pdf
That's fine except that it doesn't connect the points vertically. Does anyone know how I could make the 'black' points connect to the 'red' point, i.e. show confidence bands?
Thanks,
Chris
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
It's basically a question of layering, and the order in which the layers are drawn. Draw the pointranges first and then the points: qplot(x=as.factor(sch), y=est, ymin=lower.95ci, ymax=upper.95ci, geom='pointrange')+ geom_point(aes(x=as.factor(sch), y=est), color='red')+...
On Jul 7, 2011, at 6:16 PM, Christopher Desjardins wrote:
Thanks that worked perfectly. One thing if I may. Is it possible to make the center dot red and the lines connecting the dots black? Thanks, Chris On Jul 7, 2011, at 5:10 PM, Abhijit Dasgupta, PhD wrote:
You can easily do this by:
qplot(x=as.factor(sch),y=est, geom='point', colour='red') +
geom_pointrange(aes(x=as.factor(sch), y=est, ymin=lower.95ci, ymax=upper.95ci))+
xlab('School') + ylab("Value-added")+theme_bw()
On 07/07/2011 05:55 PM, Christopher Desjardins wrote:
Hi, I have the following data:
est
sch190 sch107 sch290 sch256 sch287 sch130 sch139
4.16656026 2.64306071 4.22579866 6.12024789 4.49624748 11.12799127 1.17353917
sch140 sch282 sch161 sch193 sch156 sch288 sch352
3.48197696 -0.29659410 -1.99194986 10.23489859 7.77342138 6.77624539 9.66795001
sch368 sch225 sch301 sch105 sch353 sch291 sch179
7.20229569 4.41989204 5.61586860 5.99460203 -2.65019242 -9.42614560 -0.25874193
sch134 sch135 sch324 sch360 bb1
3.26432479 10.52555091 -0.09637968 2.49668858 -3.24173545
se
sch190 sch107 sch290 sch256 sch287 sch130 sch139 sch140 3.165127 3.710750 4.680911 6.335386 3.896302 4.907679 4.426284 4.266303 sch282 sch161 sch193 sch156 sch288 sch352 sch368 sch225 3.303747 4.550193 3.995261 5.787374 5.017278 7.820763 7.253183 4.483988 sch301 sch105 sch353 sch291 sch179 sch134 sch135 sch324 4.076570 7.564359 10.456522 5.705474 4.247927 5.671536 10.567093 4.138356 sch360 bb1 4.943779 1.935142
sch
[1] "190" "107" "290" "256" "287" "130" "139" "140" "282" "161" "193" "156" "288"
[14] "352" "368" "225" "301" "105" "353" "291" "179" "134" "135" "324" "360" "BB"
From this data I have created 95% confidence intervals assuming a normal distribution.
lower.95ci<- est - se*qnorm(.975)
upper.95ci<- est + se*qnorm(.975)
What I'd like to do is plot the estimate (est) and have lines attach to the points located in lower.95ci and upper.95ci. Presently I am doing the following:
qplot(x=as.factor(sch),y=lower.95ci) + geom_point(aes(x=as.factor(sch),y=upper.95ci),colour="black") + geom_point(aes(x=as.factor(sch), y=est),colour="red") + ylab("Value-Added") + xlab("School") + theme_bw()
Which creates this graph ---> http://dl.dropbox.com/u/1501309/value_added_test.pdf
That's fine except that it doesn't connect the points vertically. Does anyone know how I could make the 'black' points connect to the 'red' point, i.e. show confidence bands?
Thanks,
Chris
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.