sas to R
I restarted R and tried to fit the model. However, I got the same message... So, I checked the session information with sessionInfo(). I found there is still nlme package in "loaded via a namespace (and not attached)". Is it still causing problem? Here is what I did: R version 2.15.0 (2012-03-30) Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i386-pc-mingw32/i386 (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. [Previously saved workspace restored]
df <- bcwrear1 y <- df$day10 trial <- df$trial block <- df$block trt <- df$turf library(lme4)
Loading required package: Matrix
Loading required package: lattice
Attaching package: ?lme4?
The following object(s) are masked from ?package:stats?:
AIC, BIC
fm.lmer <- lmer(log10(day10) ~ trt + (1|trial/block/trt), data=df, na.action=na.omit)
Error: length(f1) == length(f2) is not TRUE In addition: Warning messages: 1: In block:trial : numerical expression has 92 elements: only the first used 2: In block:trial : numerical expression has 92 elements: only the first used 3: In trt:(block:trial) : numerical expression has 92 elements: only the first used 4: In block:trial : numerical expression has 92 elements: only the first used 5: In block:trial : numerical expression has 92 elements: only the first used
sessionInfo()
R version 2.15.0 (2012-03-30) Platform: i386-pc-mingw32/i386 (32-bit) locale: [1] LC_COLLATE=English_United States.1252 [2] LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] lme4_0.999375-42 Matrix_1.0-6 lattice_0.20-6 loaded via a namespace (and not attached): [1] grid_2.15.0 nlme_3.1-103 stats4_2.15.0 Thanks!!! Steve
On Mon, Jun 25, 2012 at 1:01 PM, Douglas Bates <bates at stat.wisc.edu> wrote:
On Mon, Jun 25, 2012 at 12:41 PM, Steve Hong <emptican at gmail.com> wrote:
Hi Prof. Bates, Thanks for replying. ?Yes, I loaded both packages together and ran them. ?I don't understand different/separate R 'session'? ?Obviously, it seems not different versions (e.g., 2.15.0 vs. 2.14.0). ?Could you rephrase what you meant by R 'session'?
I mean to run R, load lme4 and fit the model. ?Then quit R and restart it, load nlme and fit that model.
On Mon, Jun 25, 2012 at 12:28 PM, Douglas Bates <bates at stat.wisc.edu> wrote:
Are you trying to load both the nlme and the lme4 packages at the same time? ?That can cause problems. ?You are better off fitting the lmer model in one R session and the lme model in another. On Mon, Jun 25, 2012 at 11:50 AM, Steve Hong <emptican at gmail.com> wrote:
Thank all of you for replying to me. I tried lmer, lme, and SAS. ?I was able to get outputs when I use 'lme' whereas no results from 'lmer'. ?I don't know why. ?Does anyone know what the warning message mean? ?Outputs from ?'lme' were similar with those from SAS. ?Below is selected outputs from lmer, lme, and SAS, FYI. Thanks again, Steve Hong
fm.lmer <- lmer(y ~ trt + (1|trial/block/trt), data=df, na.action=na.omit)
Error: length(f1) == length(f2) is not TRUE In addition: Warning messages: 1: In block:trial : ? numerical expression has 92 elements: only the first used 2: In block:trial : ? numerical expression has 92 elements: only the first used 3: In trt:(block:trial) : ? numerical expression has 92 elements: only the first used 4: In block:trial : ? numerical expression has 92 elements: only the first used 5: In block:trial : ? numerical expression has 92 elements: only the first used
fm.lme <- lme(y ~ trt, random=(~1|trial/block/trt), data = df, na.action=na.omit) summary(fm.lme)
Linear mixed-effects model fit by REML ?Data: df ? ? ? ? AIC ? ? ? BIC ? logLik ? -85.22388 -60.68041 52.61194 Random effects: ?Formula: ~1 | trial ? ? ? ? (Intercept) StdDev: ? 0.1112442 ?Formula: ~1 | block %in% trial ? ? ? ? ?(Intercept) StdDev: 1.449228e-06 ?Formula: ~1 | trt %in% block %in% trial ? ? ? ? (Intercept) ?Residual StdDev: ?0.07081356 0.1020226 Fixed effects: y ~ trt ? ? ? ? ? ? ? ? ? Value ?Std.Error DF ? ?t-value p-value (Intercept) ?0.24428523 0.08793775 56 ?2.7779337 ?0.0074 trtau2 ? ? ?-0.00996643 0.05605221 25 -0.1778063 ?0.8603 trtberm ? ? -0.12786905 0.05686903 25 -2.2484830 ?0.0336 trtls44 ? ? ?0.12326637 0.05478364 25 ?2.2500582 ?0.0335 trtsr10y5 ? ?0.02513355 0.05517460 25 ?0.4555275 ?0.6527 trtsr10y6 ? ?0.01932992 0.05478364 25 ?0.3528410 ?0.7272 ?Correlation: ? ? ? ? ? (Intr) trtau2 trtbrm trtl44 trt105 trtau2 ? ?-0.314 trtberm ? -0.309 ?0.486 trtls44 ? -0.321 ?0.504 ?0.497 trtsr10y5 -0.319 ?0.500 ?0.493 ?0.511 trtsr10y6 -0.321 ?0.504 ?0.497 ?0.515 ?0.511 Standardized Within-Group Residuals: ? ? ? ? ? Min ? ? ? ? ? ?Q1 ? ? ? ? ? Med ? ? ? ? ? ?Q3 ? ? ? ? ? Max -2.614096e+00 -5.666986e-01 -9.727356e-05 ?4.692685e-01 ?2.410879e+00 Number of Observations: 92 Number of Groups: ? ? ? ? ? ? ? ? ? ? trial ? ? ? ? ?block %in% trial trt %in% block %in% trial ? ? ? ? ? ? ? ? ? ? ? ? 2 ? ? ? ? ? ? ? ? ? ? ? ? 6 ? ? ? ? ? ? ? ? ? ? ? ?36
anova(fm.lme)
? ? ? ? ? ? numDF denDF ?F-value p-value (Intercept) ? ? 1 ? ?56 9.907983 ?0.0026 trt ? ? ? ? ? ? 5 ? ?25 4.122070 ?0.0072 SAS code and outputs: proc glimmix data=df; model y=trt; random trial block(trial) turf(block*turf); run; ? ? Covariance Parameter Estimates ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Standard Cov Parm ? ? ? ? ? ? Estimate ? ? ? Error trial ? ? ? ? ? ? ? ? 0.01237 ? ? 0.01823 block(trial) ? ? ? ? ? ? ? ?0 ? ? ? ? ? . trt(trial*block) ? ?0.005015 ? ?0.002546 Residual ? ? ? ? ? ? ?0.01041 ? ?0.001963 ? ? ? ?Type III Tests of Fixed Effects ? ? ? ? ? ? ?Num ? ? ?Den Effect ? ? ? ? DF ? ? ? DF ? ?F Value ? ?Pr > F trt ? ? ? ? ? ?5 ? ? ? 25 ? ? ? 4.12 ? ?0.0072 On Mon, Jun 25, 2012 at 10:25 AM, Kevin Wright <kw.stat at gmail.com> wrote:
This could be similar to a multi-location RCB design were "trial" is location. ?Since no distribution is specified, the distribution is assumed to be Gaussian. ?Make sure that trial, block, trt are factors, this should be similar to SAS: lmer(y ~ trt + (1|trial/block/trt), data=df)
proc glimmix data=df; class trial block trt; model y=trt; random trial block(trial) trt(block*trial);
Kevin Wright
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