[R-sig-ME] Error message in lme function and question about the residual plot
li li
hannah.hlx at gmail.com
Thu Jun 11 20:27:46 CEST 2015
Thanks very mcuh for reply.
For question 1: There was a typo model 3. The model should be the following.
But I still get error message as follows.
> mod3 <- lme(fixed= res ~ method*time, random=~ 0+ method+ time | individual, data=one, weights= varIdent(form=~1|method))
Error in logLik.reStruct(object, conLin) :
NA/NaN/Inf in foreign function call (arg 3)
Thanks.
Li
2015-06-11 13:44 GMT-04:00, Thierry Onkelinx <thierry.onkelinx at inbo.be>:
> You need to add type ="norm" to resid() to see the effect of varIdent.
>
> Make sure that assay is present in one before fitting model3
> Op 11 jun. 2015 19:23 schreef "li li" <hannah.hlx at gmail.com>:
>
>> Hi all,
>> I have the following data frame named "one" in which there is a
>> grouping factor method with three levels. The varibility is very
>> different among the three groups seen from the plot. I am trying to
>> compare three models as follows. I have the following two questions:
>> 1. As you can see the third model does not seem to work. I am not
>> sure whether it is a convergent issue.
>> 2. The first model doesnot take into account the variance
>> heterogeneity issue while the second one does. However, when I compare
>> the residual plot between mod1 and mod2, there is not much difference.
>> The residual for the second model still has much larger variance for
>> methods 2 and 3 than the method 1.
>>
>> Thanks very much!
>> Hanna
>>
>>
>> > one
>> method individual time res
>> 1 3 12 0 101.40000
>> 2 3 12 3 101.50000
>> 3 3 12 6 101.50000
>> 4 3 12 9 101.30000
>> 5 3 12 12 100.70000
>> 6 3 12 15 101.00000
>> 7 3 12 18 101.50000
>> 14 3 10 0 101.30000
>> 15 3 10 3 101.20000
>> 16 3 10 6 101.50000
>> 17 3 10 9 100.70000
>> 18 3 10 12 101.50000
>> 19 3 10 15 101.30000
>> 20 3 10 18 101.30000
>> 27 3 11 0 100.70000
>> 28 3 11 3 101.10000
>> 29 3 11 6 101.90000
>> 30 3 11 9 100.80000
>> 31 3 11 12 99.80000
>> 32 3 11 15 100.60000
>> 33 3 11 18 100.60000
>> 40 3 1 0 97.50000
>> 41 3 1 3 97.40000
>> 42 3 1 6 97.70000
>> 43 3 1 9 97.40000
>> 44 3 1 12 97.30000
>> 45 3 1 15 96.70000
>> 46 3 1 18 96.60000
>> 54 3 3 0 98.10000
>> 55 3 3 3 98.50000
>> 56 3 3 6 97.90000
>> 57 3 3 9 97.90000
>> 58 3 3 12 97.70000
>> 59 3 3 15 98.00000
>> 60 3 3 18 98.50000
>> 67 3 6 0 100.20000
>> 68 3 6 3 99.60000
>> 69 3 6 6 99.90000
>> 70 3 6 9 99.90000
>> 71 3 6 12 100.30000
>> 77 3 2 0 98.90000
>> 78 3 2 3 98.90000
>> 79 3 2 6 98.70000
>> 80 3 2 9 98.90000
>> 81 3 2 12 98.80000
>> 82 3 2 15 97.80000
>> 83 3 2 18 98.90000
>> 90 3 4 0 100.20000
>> 91 3 4 3 99.80000
>> 92 3 4 6 99.50000
>> 93 3 4 9 100.40000
>> 96 3 5 0 100.70000
>> 97 3 5 3 100.30000
>> 98 3 5 6 100.70000
>> 99 3 5 9 100.50000
>> 102 3 7 0 100.90000
>> 105 3 8 0 99.30000
>> 108 3 9 0 100.20000
>> 111 3 13 0 101.00000
>> 114 3 14 0 100.80000
>> 117 3 15 0 100.40000
>> 8 2 12 0 108.00000
>> 9 2 12 12 97.00000
>> 21 2 10 0 112.00000
>> 22 2 10 12 93.00000
>> 34 2 11 0 98.00000
>> 35 2 11 12 96.00000
>> 47 2 1 0 94.00000
>> 48 2 1 12 103.00000
>> 49 2 1 18 103.00000
>> 61 2 3 0 87.00000
>> 62 2 3 12 105.00000
>> 72 2 6 0 119.00000
>> 73 2 6 3 105.00000
>> 74 2 6 12 91.00000
>> 84 2 2 0 105.00000
>> 85 2 2 12 112.00000
>> 95 2 4 0 96.00000
>> 101 2 5 0 113.00000
>> 104 2 7 0 106.00000
>> 107 2 8 0 71.00000
>> 110 2 9 0 95.00000
>> 113 2 13 0 88.00000
>> 116 2 14 0 86.00000
>> 119 2 15 0 81.00000
>> 86 1 12 0 105.90300
>> 94 1 12 12 99.82400
>> 10 1 12 15 91.26400
>> 11 1 12 18 72.15000
>> 191 1 10 0 91.14300
>> 201 1 10 12 100.36800
>> 211 1 10 15 104.79600
>> 221 1 10 18 102.58200
>> 301 1 11 0 78.32400
>> 311 1 11 12 88.20900
>> 321 1 11 15 95.52600
>> 331 1 11 18 106.87200
>> 411 1 1 0 99.04500
>> 421 1 1 12 82.83600
>> 431 1 1 15 116.51200
>> 441 1 1 18 89.05600
>> 52 1 3 0 97.81800
>> 53 1 3 12 89.81500
>> 541 1 3 15 82.11000
>> 551 1 3 18 79.83400
>> 611 1 6 0 89.06000
>> 621 1 6 12 102.56500
>> 701 1 2 0 112.32000
>> 711 1 2 12 104.40000
>> 721 1 2 15 90.06800
>> 731 1 2 18 107.28000
>> 781 1 4 0 125.92500
>> 831 1 5 0 95.16000
>> 851 1 7 0 111.28981
>> 87 1 8 0 102.22482
>> 89 1 9 0 91.61610
>> 911 1 13 0 111.18053
>> 931 1 14 0 91.70376
>> 951 1 15 0 98.04994
>>
>>
>>
>> library(nlme)
>> mod1 <- lme(fixed= res ~ method*time, random=~ 1+ time | individual,
>> data=one)
>> summary(mod1)
>> anova(mod1)
>>
>> mod2 <- lme(fixed= res ~ method*time, random=~ 1+ time | individual,
>> data=one, weights= varIdent(form=~1|method))
>> summary(mod2)
>> anova(mod2)
>>
>> mod3 <- lme(fixed= res ~ method*time, random=~ 0+ method+ time |
>> individual, data=one, weights= varIdent(form=~1|assay))
>> summary(mod3)
>> anova(mod3)
>>
>> par(mfrow=c(1,2))
>> plot(resid(mod1))
>> plot(resid(mod2))
>>
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