[R-sig-ME] Error message in lme function and question about the residual plot

Thierry Onkelinx thierry.onkelinx at inbo.be
Thu Jun 11 19:44:05 CEST 2015


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 op 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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