Thank you for your responses, however I don't fully understand what you are
recommending.  I won't ask you to write the code for me but are there
examples or someplace I can read how to try either of the methods you are
suggesting?

How would I fit the interactions by random effects?

How would I design specific contrasts?

Thanks again,

On Mon, Jan 30, 2012 at 1:38 PM, Thompson,Paul <
Paul.Thompson@sanfordhealth.org> wrote:

> Another approach to the problem of interactions with missing cells would
> be to design specific contrasts which assess interactions in those cases,
> but which exclude the missing cells. To do that, you would need to define
> the entire experiment as a single factor situation, and write the
> appropriate contrasts.
>
>
> -----Original Message-----
> From: r-sig-mixed-models-bounces@r-project.org [mailto:
> r-sig-mixed-models-bounces@r-project.org] On Behalf Of Kevin Wright
> Sent: Monday, January 30, 2012 1:31 PM
> To: Charles Determan Jr
> Cc: r-sig-mixed-models@r-project.org
> Subject: Re: [R-sig-ME] lmer on dataset with missing values 'not at random'
>
> Charles,
>
> You are trying to fit fixed effects for two-way and three-way interactions
> when, as you have shown, there are no data for certain combinations of
> those factors.  Generally, to estimate fixed-effect interactions you need
> data in every cell of the interaction xtabs table.
>
> You can start by removing the interactions from your model.  If the
> interactions are of interest, you could try fitting the interactions as
> random effects, but you need to understand this leads to a different model
> with different interpretations and inferences...
>
> Kevin
>
>
> On Mon, Jan 30, 2012 at 12:44 PM, Charles Determan Jr <deter088@umn.edu
> >wrote:
>
> > Greetings R users,
> >
> > I have been trying to fit a mixed model on the following dataset.  All
> > columns are factors except 'met'.  When I try to run a full model with
> > lmer, I get the error 'Error in mer_finalize(ans) : Downdated X'X is not
> > positive definite, 27.'  I took a quick look at the dataset and I can see
> > there are 4 '0's in the survival 2 group.  This makes sense as not all
> > experiments made it to the end, therefore if they didn't finish then they
> > didn't have any further timepoints.  I have read about missing data at
> > random but I can't find a way to run lmer on a dataset that has values
> > missing 'not at random'.  Is there a way to modify the lmer statement
> > without cutting out data points?
> >
> > My sincere thanks,
> >
> > x
> >    time group survival subj met
> > 1      1     2        1      2   1.3954
> > 2      2     2        1      2   1.8063
> > 3      3     2        1      2   1.3684
> > 4      4     2        1      2   2.0046
> > 5      5     2        1      2   1.0334
> > 6      6     2        1      2   0.3644
> > 7      7     2        1      2   0.4819
> > 8      8     2        1      2   1.4558
> > 9      9     2        1     2   0.9718
> > 10     1     1        2    5   0.7771
> > 11     2     1        2    5   1.2439
> > 12     1     2        2    8   1.0980
> > 13     2     2        2    8   0.9511
> > 14     1     2        1    9   1.0534
> > 15     2     2        1    9   1.7279
> > 16     3     2        1    9   1.4904
> > 17     4     2        1    9   1.2737
> > 18     5     2        1    9   0.8929
> > 19     6     2        1    9   0.5828
> > 20     7     2        1    9   0.3260
> > 21     8     2        1    9   1.0373
> > 22     9     2        1    9   0.9624
> > 23     1     2        2   10   1.1391
> > 24     2     2        2   10   1.3945
> > 25     3     2        2   10   0.9414
> > 26     4     2        2   10   1.1152
> > 27     5     2        2   10   0.8222
> > 28     6     2        2   10   0.4417
> > 29     7     2        2   10   0.4126
> > 30     1     1        1   12   1.3024
> > 31     2     1        1   12   1.1811
> > 32     3     1        1   12   0.9379
> > 33     4     1        1   12   1.3000
> > 34     5     1        1   12   1.2977
> > 35     6     1        1   12   0.4949
> > 36     7     1        1   12   0.5238
> > 37     8     1        1   12   1.3862
> > 38     1     1        1   16   1.2259
> > 39     2     1        1   16   0.8681
> > 40     3     1        1   16   1.2645
> > 41     4     1        1   16   0.7316
> > 42     5     1        1   16   0.6648
> > 43     6     1        1   16   0.9671
> > 44     7     1        1   16   1.0131
> > 45     8     1        1   16   1.1762
> > 46     9     1        1   16   0.8776
> > 47     1     2        2   18   1.1231
> > 48     2     2        2   18   1.2133
> > 49     3     2        2   18   1.2005
> > 50     4     2        2   18   0.7198
> > 51     5     2        2   18   0.6620
> > 52     6     2        2   18   0.5908
> > 53     7     2        2   18   0.3945
> > 54     1     2        2   19   0.7852
> > 55     2     2        2   19   0.6758
> > 56     3     2        2   19   0.5246
> > 57     4     2        2   19   0.5263
> > 58     1     2        2   20   1.2284
> > 59     2     2        2   20   0.7017
> > 60     1     2        1   23   0.9604
> > 61     2     2        1   23   0.7977
> > 62     3     2        1   23   1.2267
> > 63     4     2        1   23   1.3857
> > 64     5     2        1   23   0.9486
> > 65     6     2        1   23   0.3571
> > 66     7     2        1   23   0.3134
> > 67     8     2        1   23   1.9984
> > 68     9     2        1   23   0.4837
> > 69     1     1        1   24   1.1793
> > 70     2     1        1   24   1.3883
> > 71     3     1        1   24   2.1080
> > 72     4     1        1   24   0.8810
> > 73     5     1        1   24   0.8825
> > 74     6     1        1   24   0.4124
> > 75     7     1        1   24   0.5270
> > 76     8     1        1   24   1.9003
> > 77     9     1        1   24   1.4344
> > 78     1     1        1   27   1.1905
> > 79     2     1        1   27   1.1033
> > 80     3     1        1   27   1.4976
> > 81     4     1        1   27   1.9018
> > 82     5     1        1   27   0.5815
> > 83     6     1        1   27   0.4428
> > 84     7     1        1   27   0.4728
> > 85     8     1        1   27   1.6309
> > 86     9     1        1   27   0.4054
> > 87     1     1        1   28   0.9538
> > 88     2     1        1   28   0.7796
> > 89     3     1        1   28   1.7906
> > 90     5     1        1   28   0.4715
> > 91     6     1        1   28   0.4214
> > 92     7     1        1   28   0.4120
> > 93     8     1        1   28   1.3111
> > 94     9     1        1   28   0.3677
> > 95     1     1        2    1   1.3853
> > 96     2     1        2    1   1.5966
> > 97     3     1        2    1   1.4542
> > 98     4     1        2    1   1.3084
> > 99     5     1        2    1   1.2826
> > 100    6     1        2    1   0.6835
> > 101    7     1        2    1   0.9709
> > 102    1     1        1    3   1.3175
> > 103    2     1        1    3   0.7792
> > 104    3     1        1    3   1.8763
> > 105    5     1        1    3   1.4633
> > 106    6     1        1    3   0.0735
> > 107    7     1        1    3   0.5612
> > 108    8     1        1    3   1.3777
> > 109    9     1        1    3   0.3810
> > 110    1     1        2    4   1.3486
> > 111    1     1        1    6   1.2635
> > 112    2     1        1    6   0.7572
> > 113    3     1        1    6   1.5011
> > 114    5     1        1    6   0.6873
> > 115    6     1        1    6   0.3778
> > 116    7     1        1    6   0.4231
> > 117    8     1        1    6   1.3817
> > 118    9     1        1    6   0.5850
> > 119    1     2        2    7   0.7362
> > 120    2     2        2    7   0.5495
> > 121    3     2        2    7   0.7621
> > 122    4     2        2    7   0.8421
> > 123    5     2        2    7   1.0438
> > 124    6     2        2    7   0.9802
> > 125    7     2        2    7   0.5627
> > 126    1     1        1   11   1.5575
> > 127    2     1        1   11   2.1356
> > 128    3     1        1   11   1.3575
> > 129    4     1        1   11   1.3056
> > 130    5     1        1   11   0.8144
> > 131    6     1        1   11   0.5876
> > 132    7     1        1   11   0.4104
> > 133    9     1        1   11   0.4942
> > 134    1     2        1   13   1.0046
> > 135    2     2        1   13   0.8805
> > 136    3     2        1   13   0.7685
> > 137    4     2        1   13   0.8786
> > 138    5     2        1   13   1.4249
> > 139    6     2        1   13   0.5339
> > 140    7     2        1   13   0.5480
> > 141    8     2        1   13   2.6369
> > 142    9     2        1   13   1.7159
> > 143    1     2        1   14   0.7161
> > 144    2     2        1   14   0.3968
> > 145    3     2        1   14   0.8142
> > 146    4     2        1   14   0.6140
> > 147    5     2        1   14   0.6585
> > 148    6     2        1   14   0.7176
> > 149    7     2        1   14   0.6613
> > 150    8     2        1   14   1.6494
> > 151    9     2        1   14   0.3903
> > 152    1     1        1   15   1.4357
> > 153    2     1        1   15   1.4772
> > 154    3     1        1   15   1.3156
> > 155    4     1        1   15   0.9654
> > 156    5     1        1   15   1.2709
> > 157    6     1        1   15   0.9330
> > 158    7     1        1   15   0.3515
> > 159    8     1        1   15   1.6801
> > 160    9     1        1   15   0.3584
> > 161    1     2        2   17   0.8077
> > 162    2     2        2   17   0.7560
> > 163    1     1        1   21   1.1890
> > 164    2     1        1   21   0.9631
> > 165    3     1        1   21   0.9753
> > 166    4     1        1   21   0.9519
> > 167    5     1        1   21   0.6348
> > 168    6     1        1   21   0.8516
> > 169    7     1        1   21   0.2366
> > 170    8     1        1   21   1.0440
> > 171    9     1        1   21   0.5360
> > 172    1     2        1   22   1.0747
> > 173    2     2        1   22   0.6451
> > 174    3     2        1   22   0.8408
> > 175    5     2        1   22   0.8730
> > 176    6     2        1   22   0.3594
> > 177    7     2        1   22   0.3019
> > 178    9     2        1   22   1.2053
> > 179    1     2        2   25   0.4654
> > 180    2     2        2   25   0.3024
> > 181    3     2        2   25   0.7525
> > 182    4     2        2   25   0.7808
> > 183    5     2        2   25   0.6294
> > 184    6     2        2   25   0.3016
> > 185    7     2        2   25   0.3223
> > 186    1     2        1   26   0.5363
> > 187    2     2        1   26   0.2279
> > 188    3     2        1   26   0.4756
> > 189    4     2        1   26   0.6644
> > 190    5     2        1   26   0.6631
> > 191    6     2        1   26   0.3419
> > 192    7     2        1   26   0.4188
> > 193    8     2        1   26   0.3199
> > 194    9     2        1   26   0.2889
> > 195    1     1        2   29   1.2765
> > 196    2     1        2   29   1.0653
> > 197    3     1        2   29   1.5607
> > 198    1     1        1   30   0.8641
> > 199    2     1        1   30   0.9250
> > 200    3     1        1   30   1.0887
> > 201    4     1        1   30   0.5537
> > 202    5     1        1   30   0.7930
> > 203    6     1        1   30   0.3960
> > 204    7     1        1   30   0.3917
> > 205    8     1        1   30   1.2687
> > 206    9     1        1   30   0.5328
> > 207    1     2        1   31   1.0765
> > 208    2     2        1   31   0.8778
> > 209    3     2        1   31   0.8228
> > 210    4     2        1   31   1.2017
> > 211    5     2        1   31   1.1787
> > 212    6     2        1   31   0.4037
> > 213    7     2        1   31   0.2625
> > 214    8     2        1   31   2.2690
> > 215    9     2        1   31   0.4423
> > 216    1     1        2   32   1.2880
> > 217    2     1        2   32   0.8537
> >
> > ds=lmer(met~group*time*survival + (1|subj), data=x)
> > Error in mer_finalize(ans) : Downdated X'X is not positive definite, 27.
> >
> > xtabs(~group+time+survival, x)
> > , , survival = 1
> >
> >     time
> > group  1  2  3  4  5  6  7  8  9
> >    1 11 11 11  8 11 11 11 10 10
> >    2  8  8  8  7  8  8  8  7  8
> >
> > , , survival = 2
> >
> >     time
> > group  1  2  3  4  5  6  7  8  9
> >    1  5  4  2  1  1  1  1  0  0
> >    2  8  8  5  5  4  4  4  0  0
> >
> >        [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
>
>
>
> --
> Kevin Wright
>
>        [[alternative HTML version deleted]]
>
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> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
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