Dear list members,
I wonder which is the best way to plot in r the
results from the lme function, in presence of a significant interaction.
My model has two interacting fixed effects and a random effect. The
analysis is from an experiment where 19 participants had to adjust the
Centroid parameter of some sounds stimuli, and I want to assess whether
there is a relationship between their choices and their height and
weight. There were 12 stimuli repeated twice for a total of 24 trials.
Here is the output of my analysis:
> library(nlme)
> lme_Centroid <- lme(Centroid ~ Weight*Height, data = scrd, random = ~1 |
Subject)
>
> summary(lme_Centroid)
Linear mixed-effects model fit by REML
Data: scrd
AIC BIC logLik
25809.38 25840.69 -12898.69
Random effects:
Formula: ~1 | Subject
(Intercept) Residual
StdDev: 398.9658 3027.67
Fixed effects: Centroid ~ Weight * Height
Value Std.Error DF t-value p-value
(Intercept) -20232.203 9101.096 1349 -2.223051 0.0264
Weight 478.854 152.184 15 3.146536 0.0067
Height 140.440 52.194 15 2.690751 0.0168
Weight:Height -2.725 0.838 15 -3.253770 0.0053
Correlation:
(Intr) Weight Height
Weight -0.927
Height -0.994 0.886
Weight:Height 0.951 -0.996 -0.919
Standardized Within-Group Residuals:
Min Q1 Med Q3 Max
-1.5059828 -0.8664208 -0.2111113 0.7098706 2.3620633
Number of Observations: 1368
Number of Groups: 19
I
do not know how to represent in R these results. I tried
xyplot(Centroid ~ Weight * Height, type = c("p","r"), data = scrd) but I
guess it is wrong.
Thank you in advance
Best regards
Angelo
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
