[R] lme Random Effects and Covariates

[patze003]

1.  I'm attempting to test for Random Effects.  I've grouped the data on
subject (grid) but want to use lme to build the model without subject as a
RE then add it and do anova between the 2 models.  This is the result I get
and it appears it's adding Random Effects.

tmp.dat4 - groupedData(Trials ~ 1 | grid, data = tmp.dat4)

mod2a - lme(Trials ~ factor(group_id) + reversal, data = tmp.dat4,
na.action = na.omit, method = REML)

 summary(mod2a)
Linear mixed-effects model fit by REML
 Data: tmp.dat4 
   AIC  BIClogLik
  4544.054 4587.718 -2262.027

Random effects:
 Formula: ~factor(group_id) + reversal | grid
 Structure: General positive-definite
  StdDevCorr 
(Intercept)   10.505303 (Intr) fc(_)2
factor(group_id)2  9.830679 -0.778   
reversal2  7.106839 -0.275  0.023
Residual   9.995963  

Fixed effects: Trials ~ factor(group_id) + reversal 
  Value Std.Error  DF   t-value p-value
(Intercept)   23.275874  1.876185 510 12.405960   0e+00
factor(group_id)2 -7.639842  2.151004  72 -3.551757   7e-04
reversal2  7.681495  1.206858 510  6.364869   0e+00
 Correlation: 
  (Intr) fc(_)2
factor(group_id)2 -0.785   
reversal2 -0.308 -0.015

Standardized Within-Group Residuals:
   Min Q1Med Q3Max 
-2.6884393 -0.5059063 -0.1892908  0.4944976  2.8477377 

Number of Observations: 585
Number of Groups: 74 

2.  Secondly is this the correct way to add covariates (such as age).

mod2i - lme(Trials ~ factor(group_id)*factor(reversal) * age, data =
tmp.dat4, random = ~ 1 | grid, na.action = na.omit, method = ML)

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[R] Executing Command on Multiple R Objects

[patze003]

Hello Everyone - 

I want to print a number of results from lme function objects out to a txt
file.  How could I do this more efficiently than what you see here:

out2 - capture.output(summary(mod2a))
out3 - capture.output(summary(mod3))
out4 - capture.output(summary(mod5))
out5 - capture.output(summary(mod6))
out6 - capture.output(summary(mod7))
cat(out2,file=out.txt,sep=\n,append=TRUE)
cat(out3,file=out.txt,sep=\n,append=TRUE)
cat(out4,file=out.txt,sep=\n,append=TRUE)
cat(out5,file=out.txt,sep=\n,append=TRUE)
cat(out6,file=out.txt,sep=\n,append=TRUE)
cat(third,file=out.txt,sep=\n,append=TRUE)


Here's an example of what I tried, but didn't work.

for (i in ls(pat = mod))
{ out - capture.output(summary[[i]])
cat(out, file = results_paired.txt, sep = \n, append = TRUE)
}
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and provide commented, minimal, self-contained, reproducible code.