[R-sig-ME] pedigreemm number of levels per grouping factor

[David Duffy]

On Fri, 7 Feb 2014, Wilson, Alastair wrote:

> Thanks - that's v much appreciated. Data file and pedigree structures 
> attached.

OK, runs fine with older versions of pedigreemm and lmer

Linear mixed model fit by REML
Formula: size ~ sex + forage + (1 | ID)
    Data: pheno
   AIC  BIC logLik deviance REMLdev
  1160 1180 -574.8     1143    1150
Random effects:
  Groups   Name        Variance Std.Dev.
  ID       (Intercept) 0.35597  0.59663
  Residual             0.73231  0.85575
Number of obs: 400, groups: ID, 400

Fixed effects:
             Estimate Std. Error t value
(Intercept)  5.29569    0.24255  21.833
sex          0.14436    0.09604   1.503
forage       0.88907    0.30644   2.901

Correlation of Fixed Effects:
        (Intr) sex
sex    -0.594
forage -0.717  0.000

The newest version of pedigreemm is failing in pedigreemm::relfactor(), 
which is supposed to produce the Cholesky factor of the relationship 
matrix, where the error arises in:

solve(t(as(ped,"sparseMatrix")),
       as(factor(labs, levels = ped at label),"sparseMatrix"))

specifically in your exampe, NRM is 500*500 but labs is 400*1 (100 
unphenotyped founders)

Cheers, David Duffy.

| David Duffy (MBBS PhD)
| email: David.Duffy at qimrberghofer.edu.au  ph: INT+61+7+3362-0217 fax: -0101
| Genetic Epidemiology, QIMR Berghofer Institute of Medical Research
| 300 Herston Rd, Brisbane, Queensland 4006, Australia  GPG 4D0B994A