Sorry, I had lme4 loaded as well.

 > require(nlme)
Loading required package: nlme
 > require(gmodels)
Loading required package: gmodels
 > fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1)
 > ci(fm2)
               Estimate   CI lower   CI upper Std. Error DF      p-value
(Intercept) 17.7067130 16.0471544 19.3662716 0.83392247 80 1.283974e-34
age          0.6601852  0.5375855  0.7827849 0.06160592 80 3.952235e-17
SexFemale   -2.3210227 -3.8891901 -0.7528554 0.76141685 25 5.375056e-03
 > mm <- unique(model.matrix(with(Orthodont, distance ~ age + Sex)))
 > estimable(fm2, cm = mm, conf.int = 0.95)
    Estimate Std. Error  t value DF Pr(>|t|) Lower.CI Upper.CI
1  22.98819  0.5199561 44.21180 80        0 21.95345 24.02294
2  24.30856  0.4898898 49.62047 80        0 23.33365 25.28348
3  25.62894  0.4898898 52.31571 80        0 24.65402 26.60385
4  26.94931  0.5199561 51.82996 80        0 25.91456 27.98405
65 20.66717  0.6145864 33.62777 25        0 19.40141 21.93294
66 21.98754  0.5893676 37.30701 25        0 20.77372 23.20137
67 23.30791  0.5893676 39.54733 25        0 22.09409 24.52174
68 24.62828  0.6145864 40.07294 25        0 23.36252 25.89405
Warning message:
In estimable.default(fm2, cm = mm, conf.int = 0.95) :
   Degrees of freedom vary among parameters used to construct linear  
contrast(s): 1, 2, 3, 4, 5, 6, 7, 8. Using the smallest df among the  
set of parameters.
_____________________________
Professor Michael Kubovy
University of Virginia
Department of Psychology
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         McCormick Road    Charlottesville, VA 22903
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On Aug 13, 2008, at 11:05 AM, Michael Kubovy wrote:

> require(nlme)
> require(gmodels)
> fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1)
> ci(fm2)
> mm <- unique(model.matrix(with(Orthodont, distance ~ age + Sex)))
> estimable(fm2, cm = mm, conf.int = 0.95)


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