Grokbase Groups R r-help August 2011
FAQ
Hi all,

I?m trying to plot confidence intervals for the fitted values I get with my
lme model in R.

Is there any way I can plot this in the form of a shaded band, like the
output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
glm, gam, loess and rlm as smoothing methods.

Any advice on the functions I should use to accomplish this will be very
helpful.

Thank you very much.

Ben

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  • R. Michael Weylandt at Aug 8, 2011 at 5:35 pm
    I don't know lme models very well, but if you have standard errors for your
    values, this shouldn't be too hard (as a last resort) using polygon()

    For example

    x = 1:10
    y = x^2
    y.Err = 2*x
    y.Up = y + y.Err; y.Dn =y-y.Err

    # This graph is actually quite ugly so don't copy the formatting....
    plot(x,y,type="n")
    polygon(c(x,rev(x)),c(y.Up,rev(y.Dn)),col="grey",border="red")
    # Use the rev commands so the border moves logically around the shaded area
    lines(x,y,type="b",lwd=3) # put the means back on top of the polygon

    Still, this is a little brute force and I'd imagine that someone else will
    shortly let you know how R can already do automatically.

    Michael Weylandt
    On Mon, Aug 8, 2011 at 1:07 PM, bjmjarrett wrote:

    Hi all,

    I�m trying to plot confidence intervals for the fitted values I get with my
    lme model in R.

    Is there any way I can plot this in the form of a shaded band, like the
    output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
    glm, gam, loess and rlm as smoothing methods.

    Any advice on the functions I should use to accomplish this will be very
    helpful.

    Thank you very much.

    Ben

    --
    View this message in context:
    http://r.789695.n4.nabble.com/confidence-interval-as-shaded-band-lme-tp3727645p3727645.html
    Sent from the R help mailing list archive at Nabble.com.

    ______________________________________________
    r-help@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.
  • Dennis Murphy at Aug 8, 2011 at 8:07 pm
    Hi:
    On Mon, Aug 8, 2011 at 10:07 AM, bjmjarrett wrote:
    Hi all,

    I?m trying to plot confidence intervals for the fitted values I get with my
    lme model in R.
    Which fitted values? The ones conditional on the random effects or the
    ones averaged over the random effects? The standard errors of the two
    sets of predictions are not the same.
    Is there any way I can plot this in the form of a shaded band, like the
    output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
    glm, gam, loess and rlm as smoothing methods.
    You can fake it with geom_ribbon(), but it would be convenient to have
    the endpoints of the CIs in a data frame you could input into ggplot2.

    HTH,
    Dennis
    Any advice on the functions I should use to accomplish this will be very
    helpful.

    Thank you very much.

    Ben

    --
    View this message in context: http://r.789695.n4.nabble.com/confidence-interval-as-shaded-band-lme-tp3727645p3727645.html
    Sent from the R help mailing list archive at Nabble.com.

    ______________________________________________
    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.
  • Bert Gunter at Aug 8, 2011 at 8:40 pm
    Would someone tell me how they propose to go from "standard errors" to
    confidence intervals*. I suspect Doug Bates would probably like to
    know, also, as he has expended a lot of effort on this over the years,
    I believe. :-)

    -- Bert

    * Note +/- 2 std errors is almost certainly not the right answer --
    how far wrong it is ... that's the question.


    Cheers,
    Bert
    On Mon, Aug 8, 2011 at 1:07 PM, Dennis Murphy wrote:
    Hi:
    On Mon, Aug 8, 2011 at 10:07 AM, bjmjarrett wrote:
    Hi all,

    I?m trying to plot confidence intervals for the fitted values I get with my
    lme model in R.
    Which fitted values? The ones conditional on the random effects or the
    ones averaged over the random effects? The standard errors of the two
    sets of predictions are not the same.
    Is there any way I can plot this in the form of a shaded band, like the
    output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
    glm, gam, loess and rlm as smoothing methods.
    You can fake it with geom_ribbon(), but it would be convenient to have
    the endpoints of the CIs in a data frame you could input into ggplot2.

    HTH,
    Dennis
    Any advice on the functions I should use to accomplish this will be very
    helpful.

    Thank you very much.

    Ben

    --
    View this message in context: http://r.789695.n4.nabble.com/confidence-interval-as-shaded-band-lme-tp3727645p3727645.html
    Sent from the R help mailing list archive at Nabble.com.

    ______________________________________________
    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.
    ______________________________________________
    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.


    --
    "Men by nature long to get on to the ultimate truths, and will often
    be impatient with elementary studies or fight shy of them. If it were
    possible to reach the ultimate truths without the elementary studies
    usually prefixed to them, these would not be preparatory studies but
    superfluous diversions."

    -- Maimonides (1135-1204)

    Bert Gunter
    Genentech Nonclinical Biostatistics

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