[R] Problem fitting network meta-analysis using lme

[David Scott]

I am trying to use the network meta-analysis approach of Thomas Lumley, 
described in his paper in Statistics in Medicine, 2002.

My problem is fairly simple as network meta analyses go, I have two 
groups of trials, ones comparing A and B, and ones comparing A and C, 
and I am interested in comparing B and C

Thomas gives the code snippet to fit the model:
netmeta <- lme(effect ~ trt.B + trt.C + trt.D + trt.E,
                random = ~1|trtpair,
                var = varConstPower(form = ~sigma,
                                    fixed = list(power = 1)))

This is when there are 5 different treatments being considered. This 
appears to be for an earlier version of lme, because currently there is 
no var argument to lme.

I am using R 2.8.1 on windows vista and nlme 3.1-92. I have the latest 
nlme but could upgrade my R I guess.

I used the command
compNetMeta <- lme(effect ~ trtB + trtC, data = comp,
                    random = ~1 | trtpair,
                    weights = varConstPower(form = ~sigma,
                                            fixed = list(power = 1)))

where the first two lines of the dataframe comp look like this:
 > head(comp,2)
   studlab event.e n.e event.c n.c   group    effect     sigma
1  Conway       5  29       9  28 Doppler -0.622878 0.4908300
2 Noblett       3  51      12  52 Doppler -1.366876 0.6146772
   trtA trtB trtC trtpair
1   -1    1    0     A.B
2   -1    1    0     A.B

The output is the error message:

Error in MEEM(object, conLin, control$niterEM) :
   Singularity in backsolve at level 0, block 1

I would be grateful for any advice on what is going wrong here. I think 
I have the correct command with the var argument now being weights, but 
that is an area of uncertainty for me. To make the problem reproducible, 
the data is given below.

David Scott

 > dput(comp)
structure(list(studlab = structure(c(2L, 7L, 3L, 8L, 1L, 5L,
4L, 6L), .Label = c("Brandstrup", "Conway", "Gan", "Kabon", "Lobo",
"Nisanevich", "Noblett", "Wakeling"), class = "factor"), event.e = c(5,
3, 14, 24, 21, 1, 32, 13), n.e = c(29, 51, 50, 64, 69, 10, 129,
77), event.c = c(9, 12, 36, 38, 40, 7, 31, 23), n.c = c(28, 52,
50, 64, 72, 10, 124, 75), group = structure(c(1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L), .Label = c("Doppler", "Restricted"), class = "factor"),
     effect = c(-0.622877984713389, -1.36687627526279, -0.944461608840851,
     -0.45953232937844, -0.601797401971717, -1.94591014905531,
     -0.00778214044205496, -0.596862166784986), sigma = 
c(0.490829977462803,
     0.614677195199759, 0.243323548400785, 0.191657131723166,
     0.210326900578529, 0.971008312455225, 0.218384089169977,
     0.306726248424056), trtA = c(-1, -1, -1, -1, -1, -1, -1,
     -1), trtB = c(1, 1, 1, 1, 0, 0, 0, 0), trtC = c(0, 0, 0,
     0, 1, 1, 1, 1), trtpair = structure(c(1L, 1L, 1L, 1L, 2L,
     2L, 2L, 2L), .Label = c("A.B", "A.C"), class = "factor")), .Names = 
c("studlab",
"event.e", "n.e", "event.c", "n.c", "group", "effect", "sigma",
"trtA", "trtB", "trtC", "trtpair"), row.names = c(NA, -8L), class = 
"data.frame")

_________________________________________________________________
David Scott	Department of Statistics
		The University of Auckland, PB 92019
		Auckland 1142,    NEW ZEALAND
Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055
Email:	d.scott at auckland.ac.nz,  Fax: +64 9 373 7018

Director of Consulting, Department of Statistics