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From |
"moleps islon" <moleps2@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: error bars |

Date |
Wed, 18 Jun 2008 22:17:52 +0200 |

I' making a double error bar graph- e.g two different variables x and y with error bars categorised according to z. I've tried using ciplot x y, by(z) however I get a graph with two identical error bars (though different symbol, but identical values) for each instance of z. Any idea how to remedy this? If I need to make bars (a bar graph) for each category and then have the positive part of the error bar projecting from the top- how do I go about this? Regards On Mon, Jun 16, 2008 at 2:23 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote: > Standard errors can come from lots of places, including the -ci- > command. > > Moleps seems to be implying that -ci- does the right calculation for his > or her purposes. > > (I note that Moleps has yearly results, but -ci- for separate years does > nothing about any time series structure in the data, for example about > taking serial correlation into account.) > > -ciplot- and -stripplot- from SSC both do -ci-type calculations and > graphing in one. > > Nick > n.j.cox@durham.ac.uk > > Maarten buis > > --- moleps islon <moleps2@gmail.com> wrote: >> I need to make a an error-bar graph categorised by year. I've tried >> using serrbar mean(x) etc, but I cant find a command for the standard >> error. Do I need to run a CI, generate a new variable from the ci >> result and feed that into serrbar? > > There are many ways of doing this. For instance you can use methods > discussed in (Buis 2007) (a convenient estimatation command would in > this case be -mean-), or you can remember that the standard error of > the mean is the standard deviation divided by the square root of the > number of observations, like in the example below: > > *-------------- begin example ----------------------- > sysuse nlsw88, clear > gen mis = missing(wage, age) > bys age: egen mwage = mean(wage) > bys age: egen sdwage = sd(wage) > bys age mis: gen se = sdwage/sqrt(_N) if mis == 0 > serrbar mwage se age, scale(1.96) > *-------------- end example ------------------------- > > Notice that a fixed scale is slightly problematic here as idealy this > scale should depend on the number of observations (a t-test), but 1.96 > should work fine in large samples. For a more flexible approach, where > you can take all this into account see: (Newson 2003) > > -- maarten > > M.L. Buis (2007), "Stata tip 54: Where did my p-values go?", The Stata > Journal, 7(4), pp.584--586. > http://home.fsw.vu.nl/m.buis/wp/pvalue.html > > R. Newson (2003), "Confidence intervals and p-values for delivery to > the end user", The Stata Journal, 3(3), pp. 245--269. > http://www.stata-journal.com/article.html?article=st0043 > > > * > * For searches and help try: > * http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: error bars***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**Re: st: error bars***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**References**:**st: error bars***From:*"moleps islon" <moleps2@gmail.com>

**Re: st: error bars***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**RE: st: error bars***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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