After the data is input, and factors are assigned,

model=lme(arginine~group*time*survival, random=~1|subj, method="REML",
data=x)

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



On Fri, Feb 3, 2012 at 10:01 AM, Kevin Wright <kw.stat@gmail.com> wrote:

> Providing the data is not a "reproducible example".  Complete data and
> R-code are helpful.
>
> Kevin
>
>
>
> On Fri, Feb 3, 2012 at 9:31 AM, Charles Determan Jr <deter088@umn.edu>wrote:
>
>> Here is the dataset, everything should be run as a factor except 'met'
>> which is numeric.  Thanks for the assistance,
>>
>>    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
>>
>> On Fri, Feb 3, 2012 at 9:25 AM, Baldwin, Jim -FS <jbaldwin@fs.fed.us>
>> wrote:
>>
>> > I think the only way to resolve this is to provide a specific example.
>> >
>> > Jim Baldwin
>> > Station Statistician
>> > USDA Forest Service
>> > Albany, California
>> >
>> > -----Original Message-----
>> > From: r-sig-mixed-models-bounces@r-project.org [mailto:
>> > r-sig-mixed-models-bounces@r-project.org] On Behalf Of Charles
>> Determan Jr
>> > Sent: Friday, February 03, 2012 7:18 AM
>> > To: Thompson,Paul; r-sig-mixed-models@r-project.org
>> > Subject: Re: [R-sig-ME] lme capable of running with missing data?
>> >
>> > So, is there a way in which I can alter the design matrix so the mixed
>> > model will work or is this something that can only be done in SAS
>> > currently?  The output from the SAS run did provide Type III fixed
>> effect
>> > test values.
>> >
>> > On Fri, Feb 3, 2012 at 9:14 AM, Thompson,Paul <
>> > Paul.Thompson@sanfordhealth.org> wrote:
>> >
>> > >  That's interesting. SAS uses the sweep approach (it was in fact
>> > > devised by Goodnight). The method used in construction of various
>> > > types of SS does allow you to estimate when cells are missing. I would
>> > > wonder if Type II SS can be done. Type III (despite the incorrect
>> > > statement that they are
>> > > illegitimate) and Type IV would work fine. ****
>> > >
>> > > ** **
>> > >
>> > > It's really an issue of the manner in which the design matrix is
>> > > contructed.****
>> > >
>> > > ** **
>> > >
>> > > *From:* Charles Determan Jr [mailto:deter088@umn.edu]
>> > > *Sent:* Friday, February 03, 2012 8:36 AM
>> > > *To:* Thompson,Paul; r-sig-mixed-models@r-project.org
>> > > *Subject:* Re: [R-sig-ME] lme capable of running with missing
>> > > data?****
>> > >
>> > > ** **
>> > >
>> > > Thank you Paul, I do appreciate your response and especially your
>> time.
>> > > The reason I am so persistent is that I know the prior data I posted
>> > > was run in SAS (however I don't have the exact coding although I do
>> > > know it was done with PROC MIXED with an unstructured covariance
>> > > structure and REML estimation method) and it provided all the
>> > > interactions.  As such, I have scoured the web and literature as to
>> > > how this could be done with the missing data (timepoints as a result
>> > > of survival).  Perhaps this simply has not yet been done in R and I am
>> > > stuck for the time being.  None-the-less, I want to be certain before
>> I
>> > give up on running this type of analysis in R.
>> > >
>> > > Thanks again,****
>> > >
>> > > On Fri, Feb 3, 2012 at 8:26 AM, Thompson,Paul <
>> > > Paul.Thompson@sanfordhealth.org> wrote:****
>> > >
>> > > Charles:
>> > >
>> > > I did suggest the use of specific contrasts to do the analysis with
>> > > missing cells. I played around, and just have to admit that this is
>> > > not possible. I tried to use standard construction techniques to
>> > > produce main effects using contrast coding, and then multiply those to
>> > > produce interactions. This does not work. It may be possible to use
>> > > orthonormalization and the sweep operator to produce a consistent
>> > > estimator, but I ran out of time to work on this.
>> > >
>> > > What you can do is convert the design to a single factor, and do the
>> > > analysis with specific contrasts, recognizing that this will not
>> > > enable you to get to specific things like interaction effects. To
>> > > understand why, consider the situation with a 2 x 2, where one cell is
>> > entirely missing.
>> > > You have lost 1 df for the design, and the interaction is entirely
>> > missing.
>> > > You can estimate and test specific contrasts, but you can't even
>> > > really test the A factor or the B factor. If Cell(2,2) is missing, you
>> > > can test Cell (1,1) v Cell(1,2) and you can test Cell (2,1) v Cell
>> > > (1,1), but neither of these is the test of the "main effect" of A or
>> > > B. When you have larger designs with 2 or 3 factors, the comparisons
>> > > again have fewer df than should be encountered. This means that the
>> > > interactions are not defined properly.
>> > >
>> > > Do you NEED the interactions for theoretical purposes, or are they
>> > > there simply for completedness? Are the cells missing due to your
>> > > design or due to happenstance?
>> > >
>> > > It is the case that fractional factorial designs eliminate cells from
>> > > the design to estimate main effects and losing the ability to estimate
>> > > interactions. So, missing cells, when planned for appropriately, can
>> > > result in appropriate analysis. I am not sure how to run mixed models
>> > > with fractional factorials, however.****
>> > >
>> > >
>> > > -----Original Message-----
>> > > From: r-sig-mixed-models-bounces@r-project.org [mailto:
>> > > r-sig-mixed-models-bounces@r-project.org] On Behalf Of Charles
>> > > Determan Jr
>> > > Sent: Friday, February 03, 2012 7:06 AM
>> > > To: r-sig-mixed-models@r-project.org
>> > > Subject: [R-sig-ME] lme capable of running with missing data?
>> > >
>> > > Greetings,
>> > >
>> > > Some of you may recognize my name from a few related posts but I just
>> > > have general question that perhaps can be clarified.  I have read
>> > > several times that 'lme' and 'lmer' are techniques capable of running
>> > > data sets with missing values.  Is this true?  I have put up similar
>> > > posts where when I try to run a two or three way interaction mixed
>> > > model I get an error of singularities or X'X not positive.  Does the
>> > > data set need to be formatted in some way where the mixed model can be
>> > run with all interactions?
>> > > Furthermore, if the missing values are 'not missing at random' is
>> > > there another method to follow for generating the mixed model?  I am
>> > > just confused why I see posts that lme can be run when data is
>> missing.
>> > >
>> > > Regards,****
>> > >
>> > >        [[alternative HTML version deleted]]
>> > >
>> > > _______________________________________________
>> > > R-sig-mixed-models@r-project.org mailing list
>> > > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>> > >
>> > > ----------------------------------------------------------------------
>> > > - Confidentiality Notice: This e-mail message, including any
>> > > attachments, is for the sole use of the intended recipient(s) and may
>> > > contain privileged and confidential information.  Any unauthorized
>> > > review, use, disclosure or distribution is prohibited.  If you are not
>> > > the intended recipient, please contact the sender by reply e-mail and
>> > > destroy all copies of the original message.****
>> > >
>> > > ** **
>> > >
>> > >
>> > > ----------------------------------------------------------------------
>> > > - Confidentiality Notice: This e-mail message, including any
>> > > attachments, is for the sole use of the intended recipient(s) and may
>> > > contain privileged and confidential information. Any unauthorized
>> > > review, use, disclosure or distribution is prohibited. If you are not
>> > > the intended recipient, please contact the sender by reply e-mail and
>> > > destroy all copies of the original message.
>> > >
>> >
>> >         [[alternative HTML version deleted]]
>> >
>> >
>> >
>>
>>        [[alternative HTML version deleted]]
>>
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>>
>
>
>
> --
> Kevin Wright
>
>

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