Pryseley Assam
2006-Mar-07 13:45 UTC
[R] lme and gls : accessing values from correlation structure and variance functions
Dear R-users I am relatively new to R, i hope my many novice questions are welcome. I have problems accessing some objects (specifically the random effects, correlation structure and variance function) from an object of class gls and lme. I used the following models: yah <- gls (outcome~ -1 + as.factor(Trial):as.factor(endpoint)+ as.factor(Trial):as.factor(endpoint):trt, data=datt[datt$Trial<4,], correlation = corSymm(form=~1|as.factor(Trial)/as.factor(subject)), weights=varIdent(form=~1|endpoint)) bm <- lme (outcome~ -1 + as.factor(endpoint)+ as.factor(endpoint):trt, data=datt[datt$Trial<4,], random=~-1 + as.factor(endpoint) + as.factor(endpoint):trt|as.factor(Trial), correlation = corSymm(form=~1|as.factor(Trial)/as.factor(subject)), weights=varIdent(form=~1|endpoint)) When i print the object "bm" i get the following output: ---------------------------------------------------------------------------------------------------------- > bm Linear mixed-effects model fit by REML Data: datt[datt$Trial < 4, ] Log-restricted-likelihood: -52.23147 Fixed: outcome ~ -1 + as.factor(endpoint) + as.factor(endpoint):trt as.factor(endpoint)-1 as.factor(endpoint)1 as.factor(endpoint)-1:trt -3.663087 -1.772427 -3.661823 as.factor(endpoint)1:trt -3.209671 Random effects: Formula: ~-1 + as.factor(endpoint) + as.factor(endpoint):trt | as.factor(Trial) Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr as.factor(endpoint)-1 2.05744327 as.()-1 as.()1 a.()-1: as.factor(endpoint)1 0.08400874 -0.976 as.factor(endpoint)-1:trt 1.90318009 0.975 -0.967 as.factor(endpoint)1:trt 3.25432832 -0.992 0.982 -0.972 Residual 6.48819860 Correlation Structure: General Formula: ~1 | as.factor(Trial)/as.factor(subject) Parameter estimate(s): Correlation: 1 2 0.812 Variance function: Structure: Different standard deviations per stratum Formula: ~1 | endpoint Parameter estimates: 1 -1 1.000000 1.764878 Number of Observations: 18 Number of Groups: 3 ---------------------------------------------------------------------------------------------------- Can somebody tell me how to access the values in blue above? Also, when i tried accessing these values i obtained the following bm$modelStruct corStruct parameters: [1] -1.394879 varStruct parameters: [1] 0.5680815 What do these values represent. Thanks in advance.. Pryseley sample data: RowNames Trial subject VISUAL0 TRT VISUAL24 VISUAL52 TREAT outcome endpoint trt 4 1 1003 65 4 65 55 2 0 1 1 8 1 1007 67 1 64 68 2 -3 1 -1 12 2 1110 59 4 53 42 2 -6 1 1 14 2 1111 64 1 72 65 2 8 1 -1 16 2 1112 39 1 37 37 2 -2 1 -1 18 2 1115 59 4 54 58 2 -5 1 1 24 3 1806 46 4 27 24 2 -19 1 1 26 3 1813 31 4 33 48 2 2 1 1 28 3 1815 64 1 67 64 2 3 1 -1 4 1 1003 65 4 65 55 2 -10 -1 1 8 1 1007 67 1 64 68 2 1 -1 -1 12 2 1110 59 4 53 42 2 -17 -1 1 14 2 1111 64 1 72 65 2 1 -1 -1 16 2 1112 39 1 37 37 2 -2 -1 -1 18 2 1115 59 4 54 58 2 -1 -1 1 24 3 1806 46 4 27 24 2 -22 -1 1 26 3 1813 31 4 33 48 2 17 -1 1 28 3 1815 64 1 67 64 2 0 -1 -1 --------------------------------- [[alternative HTML version deleted]]
Spencer Graves
2006-Mar-11 18:19 UTC
[R] lme and gls : accessing values from correlation structure and variance functions
You ask, "how to access the values in blue". I can't see what you carefully highlighted in blue, because this listserve often removes formatting. Have you consulted Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer)? I have learned a lot from that book, both about how to use the nlme package and about mixed-effects modeling more generally, and I would expect that you could find there answers to this question and many others you will want answered in the future. Beyond that, I checked the documentation for "gls" and "lme" and found they produced objects of class "gls" and "lme", respectively. I then entered 'methods(class="gls")' and 'methods(class="lme")' and got the following: > methods(class="lme") [1] ACF.lme* anova.lme augPred.lme* [4] BIC.lme* coef.lme* comparePred.lme* [7] fitted.lme* fixef.lme* formula.lme* [10] getData.lme* getGroups.lme* getGroupsFormula.lme* [13] getResponse.lme* getVarCov.lme* intervals.lme* [16] logLik.lme* pairs.lme* plot.lme [19] predict.lme* print.anova.lme* print.lme* [22] qqnorm.lme* ranef.lme* residuals.lme* [25] simulate.lme summary.lme* update.lme* [28] VarCorr.lme* Variogram.lme* vcov.lme* Non-visible functions are asterisked > methods(class="gls") [1] ACF.gls* anova.gls* augPred.gls* [4] BIC.gls* coef.gls* comparePred.gls* [7] fitted.gls* formula.gls* getData.gls* [10] getGroups.gls* getGroupsFormula.gls* getResponse.gls* [13] getVarCov.gls* intervals.gls* logLik.gls* [16] plot.gls* predict.gls* print.gls* [19] qqnorm.gls* residuals.gls* summary.gls* [22] update.gls* Variogram.gls* vcov.gls* Non-visible functions are asterisked > This suggests to me that you might like to read '?VarCorr.lme'. hope this helps. spencer graves Pryseley Assam wrote:> Dear R-users > > I am relatively new to R, i hope my many novice questions are welcome. > > I have problems accessing some objects (specifically the random effects, correlation structure and variance function) from an object of class gls and lme. > > I used the following models: > > > yah <- gls (outcome~ -1 + as.factor(Trial):as.factor(endpoint)+ as.factor(Trial):as.factor(endpoint):trt, data=datt[datt$Trial<4,], > correlation = corSymm(form=~1|as.factor(Trial)/as.factor(subject)), weights=varIdent(form=~1|endpoint)) > > > bm <- lme (outcome~ -1 + as.factor(endpoint)+ as.factor(endpoint):trt, data=datt[datt$Trial<4,], > random=~-1 + as.factor(endpoint) + as.factor(endpoint):trt|as.factor(Trial), > correlation = corSymm(form=~1|as.factor(Trial)/as.factor(subject)), weights=varIdent(form=~1|endpoint)) > > When i print the object "bm" i get the following output: > ---------------------------------------------------------------------------------------------------------- > > bm > Linear mixed-effects model fit by REML > Data: datt[datt$Trial < 4, ] > Log-restricted-likelihood: -52.23147 > Fixed: outcome ~ -1 + as.factor(endpoint) + as.factor(endpoint):trt > as.factor(endpoint)-1 as.factor(endpoint)1 as.factor(endpoint)-1:trt > -3.663087 -1.772427 -3.661823 > as.factor(endpoint)1:trt > -3.209671 > > Random effects: > Formula: ~-1 + as.factor(endpoint) + as.factor(endpoint):trt | as.factor(Trial) > Structure: General positive-definite, Log-Cholesky parametrization > StdDev Corr > as.factor(endpoint)-1 2.05744327 as.()-1 as.()1 a.()-1: > as.factor(endpoint)1 0.08400874 -0.976 > as.factor(endpoint)-1:trt 1.90318009 0.975 -0.967 > as.factor(endpoint)1:trt 3.25432832 -0.992 0.982 -0.972 > Residual 6.48819860 > > Correlation Structure: General > Formula: ~1 | as.factor(Trial)/as.factor(subject) > Parameter estimate(s): > Correlation: > 1 > 2 0.812 > > Variance function: > Structure: Different standard deviations per stratum > Formula: ~1 | endpoint > Parameter estimates: > 1 -1 > 1.000000 1.764878 > Number of Observations: 18 > Number of Groups: 3 > ---------------------------------------------------------------------------------------------------- > > Can somebody tell me how to access the values in blue above? > > Also, when i tried accessing these values i obtained the following > > bm$modelStruct > corStruct parameters: > [1] -1.394879 > varStruct parameters: > [1] 0.5680815 > > What do these values represent. > > Thanks in advance.. > Pryseley > > > sample data: > > RowNames Trial subject VISUAL0 TRT VISUAL24 VISUAL52 TREAT outcome endpoint trt > 4 1 1003 65 4 65 55 2 0 1 1 > 8 1 1007 67 1 64 68 2 -3 1 -1 > 12 2 1110 59 4 53 42 2 -6 1 1 > 14 2 1111 64 1 72 65 2 8 1 -1 > 16 2 1112 39 1 37 37 2 -2 1 -1 > 18 2 1115 59 4 54 58 2 -5 1 1 > 24 3 1806 46 4 27 24 2 -19 1 1 > 26 3 1813 31 4 33 48 2 2 1 1 > 28 3 1815 64 1 67 64 2 3 1 -1 > 4 1 1003 65 4 65 55 2 -10 -1 1 > 8 1 1007 67 1 64 68 2 1 -1 -1 > 12 2 1110 59 4 53 42 2 -17 -1 1 > 14 2 1111 64 1 72 65 2 1 -1 -1 > 16 2 1112 39 1 37 37 2 -2 -1 -1 > 18 2 1115 59 4 54 58 2 -1 -1 1 > 24 3 1806 46 4 27 24 2 -22 -1 1 > 26 3 1813 31 4 33 48 2 17 -1 1 > 28 3 1815 64 1 67 64 2 0 -1 -1 > > > > --------------------------------- > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html