[R] Discrepancy between intervals.lme and coef.lme

[datkins@u.washington.edu]

I'm using R on Windows v2.0.1 with the nlme package (v3.1-53) and am finding some unexpected discrepancies in the output of intervals.lme and coef.lme.  I've included a toy dataset at the end, but briefly, the data are longitudinal data from couples in marital therapy.  Each spouse's relationship satisfaction is measured 4 times; I've fit both linear and quadratic models to the change over time.  The quadratic fits show the discrpancies.

Here's the call to lmList, coef, and intervals:

tmp.lis1 <- lmList(dv ~ time + I(time^2)| id/sex, data = tmp.df,
                      na.action = na.omit)
coef(tmp.lis1)
intervals(tmp.lis1)

Here is the coef() output:
           (Intercept)       time  I(time^2)
1/Husband       89.60  11.100000  -2.500000
1/Wife          69.80   5.300000  -0.500000
2/Husband       49.00   8.833333  -2.833333
2/Wife          45.00  28.666667  -9.666667
3/Husband       96.00  -6.000000         NA
3/Wife          60.00  19.000000         NA
4/Husband       70.00  48.500000 -16.500000
4/Wife          92.00  14.500000  -4.500000
5/Husband       75.00  43.500000 -14.500000
5/Wife          87.00  37.000000 -14.000000
6/Husband       66.75   1.250000  -1.250000
6/Wife          66.15  12.150000  -2.750000
7/Husband       92.75   6.750000  -0.750000
7/Wife          82.35  17.850000  -3.250000
8/Husband       76.15 -25.350000  11.750000
8/Wife         100.50 -12.000000   6.000000

And just the (Intercept) portion of the intervals() output:
, , (Intercept)

                lower       est.       upper
1/Husband 72.4335719 89.6000000 106.7664281
1/Wife    52.6335719 69.8000000  86.9664281
2/Husband        NaN 49.0000000         NaN
2/Wife           NaN 45.0000000         NaN
3/Husband        NaN 96.0000000         NaN
3/Wife           NaN        NaN         NaN
4/Husband        NaN        NaN         NaN
4/Wife           NaN        NaN         NaN
5/Husband        NaN        NaN         NaN
5/Wife           NaN        NaN         NaN
6/Husband -3.8551591 -0.7453560   2.3644471
6/Wife    -3.2306740 -1.4468675   0.3369390
7/Husband -2.1707917 -0.1916630   1.7874658
7/Wife    -2.4667397 -1.0766253   0.3134891
8/Husband  4.0996388  4.5693563   5.0390738
8/Wife     0.9368527  1.7888544   2.6408560

Notice that the intercept estimates for couples 6-8 are wildly different between the coef() and intervals() output.  Granted, fitting an intercept, slope, and quadratic to 4 data points doesn't leave much for an error term, but it seems like the intercept coefficients ought to be the same.  If the quadratic is dropped, there is no discrepancy between coef() and intevals(), so perhaps this is related to the complexity of the model vs. sparseness of data?

Any insights appreciated (data below).

Dave
-- 
Dave Atkins, PhD
datkins at u.washington.edu

tmp.df <- data.frame(id = as.factor(rep(1:8, each=8)),
                      sex = factor(rep(0:1, each=4, length.out=64), 0:1,
                                   c("Husband","Wife")),
                      time = rep(0:3, length.out=64),
                      dv = c(92, 91, 109, 98, 70, 74, 79, 81, 49, 55, NA,
                         50, 45, 64, NA, 44, NA, 90, 84, NA, NA, 79, 98, NA,
                         70, 102, 101, NA, 92, 102, 103, NA, 75, 104, 104,
                         NA, 87, 110, 105, NA, 66, 69, 62, 60, 67, 73, 82,
                         77, 91, 104, 98, 108, 81, 101, 101, 108, 75, 66,
                         69, 107, 102, 90, 105, 117))