Dear colleagues,
I am testing the impact of categorical binary characters (habitat and
presence/absence of symbionts) on a continuous variable (log of body size)
using PGLS...
I am not sure if I should remove the intercept from the formulae and the
biological interpretation of the absence of intercept for categorical
variables.. All papers I found on the issue of regression through origin were
about PIC and continuous characters
It does not change my conclusions when I test individually each variable (BOTH
have a HIGHLY significant impact on body size), but it does when I test them
simultaneously:
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.252335 0.731056 4.4488 5.115e-05 ***
Habitat1 0.706823 0.434013 1.6286 0.1099
Location1 0.598868 0.810679 0.7387 0.4637
Habitat1:Location1 -0.078772 0.905514 -0.0870 0.9310
F-statistic: 3.744 on 4 and 48 DF, p-value: 0.009906
Coefficients:
Estimate Std. Error t value Pr(>|t|)
Habitat0 3.252335 0.731056 4.4488 5.115e-05 ***
Habitat1 3.959158 0.782851 5.0574 6.629e-06 ***
Location1 0.598868 0.810679 0.7387 0.4637
Habitat1:Location1 -0.078772 0.905514 -0.0870 0.9310
F-statistic: 3.744 on 4 and 48 DF, p-value: 0.009906
Also, the output of the above analysis depends on the order of variables
(symbiont location ~ habitat VS habitat ~ symbiont location).. Once the effect
of one variable is removed, the effect of the other one is no longer
significant, likely because both are correlated. Is there an objective way to
decide which one explains the best the body size ? Perhaps considering amount
of variance explained by each variable individually ?
Apologies for these very naive questions.. I guess answers are obvious to most
of you but...
Thanks in advance for your comments.
Regards
Julien Lorion
PhD, Post-doctoral fellow of the Japan Society for the Promotion of Science
Japan Agency for Marine-Earth Science and Technology (JAMSTEC)
Marine Ecosystems Research Department
2-15 Natsushima, Yokosuka 237-0061 Japan
Phone: +81-46-867-9570, Fax: +81-46-867-9525
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