Hi all,
I ran a PGLS with two variables, call them VarA and VarB, using a phylogenetic
tree and corPagel. When I try to predict VarA from VarB, I get a significant
coefficient for VarB. However, if I invert this and try to predict VarB from
VarA, I do NOT get a significant coefficient for VarA. Shouldn't these be both
significant, or both insignificant (the actual outputs and calls are pasted
below)?
If I do a simple lm for these, I get the same significance level for the
coefficients either way (i.e., lm(VarA ~ VarB) vs. lm(VarB ~ VarA), though the
values of the coefficients of course differ.
Can someone help me understand why the PGLS would not necessarily be symmetric
in this same way?
Thanks,
-Tom
> outTree_group_by_brain_LambdaEst_redo1 <- gls(log_group_size_data ~
> log_brain_weight_data, correlation = bm.t.100species_lamEst_redo1,data =
> DF.brain.repertoire.group, method= "ML")
> summary(outTree_group_by_brain_LambdaEst_redo1)
Generalized least squares fit by maximum likelihood
Model: log_group_size_data ~ log_brain_weight_data
Data: DF.brain.repertoire.group
AIC BIC logLik
89.45152 99.8722 -40.72576
Correlation Structure: corPagel
Formula: ~1
Parameter estimate(s):
lambda
0.7522738
Coefficients:
Value Std.Error t-value p-value
(Intercept) -0.0077276 0.2628264 -0.029402 0.9766
log_brain_weight_data 0.4636859 0.1355499 3.420778 0.0009
Correlation:
(Intr)
log_brain_weight_data -0.637
Standardized residuals:
Min Q1 Med Q3 Max
-1.7225003 -0.1696079 0.5753531 1.0705308 3.0685637
Residual standard error: 0.5250319
Degrees of freedom: 100 total; 98 residual
Here is the inverse:
> outTree_brain_by_group_LambdaEst_redo1 <- gls(log_brain_weight_data ~
> log_group_size_data, correlation = bm.t.100species_lamEst_redo1,data =
> DF.brain.repertoire.group, method= "ML")
> summary(outTree_brain_by_group_LambdaEst_redo1)
Generalized least squares fit by maximum likelihood
Model: log_brain_weight_data ~ log_group_size_data
Data: DF.brain.repertoire.group
AIC BIC logLik
-39.45804 -29.03736 23.72902
Correlation Structure: corPagel
Formula: ~1
Parameter estimate(s):
lambda
1.010277
Coefficients:
Value Std.Error t-value p-value
(Intercept) 1.2244133 0.20948634 5.844836 0.0000
log_group_size_data -0.0234525 0.03723828 -0.629796 0.5303
Correlation:
(Intr)
log_group_size_data -0.095
Standardized residuals:
Min Q1 Med Q3 Max
-2.0682836 -0.3859688 1.1515176 1.5908565 3.1163377
Residual standard error: 0.4830596
Degrees of freedom: 100 total; 98 residual
_________________________________________________
P. Thomas Schoenemann
Associate Professor
Department of Anthropology
Cognitive Science Program
Indiana University
Bloomington, IN 47405
Phone: 812-855-8800
E-mail: t...@indiana.edu
Open Research Scan Archive (ORSA) Co-Director
Consulting Scholar
Museum of Archaeology and Anthropology
University of Pennsylvania
http://www.indiana.edu/~brainevo
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