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#convert kilograms to gramsdata_primates$Mass_gm = data_primates$Mass_kg*1000#take the natural logarithm of gramsdata_primates$Log_Mass_gm = log(data_primates$Mass_gm)
Take a look at the two new columns of data you added to your dataframe:
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Then call "brownian". R will print the following
$Trait1$Trait1$lnl[1] -30.98123$Trait1$beta[1] 0.02371125$Trait1$aic[1] 65.96246$Trait1$aicc[1] 66.27825$Trait1$k[1] 2
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trend = fitContinuous(tree_primates, data_primates$Log_Mass_gm,model="trend")
If you type "trend," R will return to the command line:
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pchisq(0.22,1,lower.tail=F)
R will print
[1] 0.6390399
So, the p-value associated with this difference in log likelihoods is not significant, and we do not have evidence that a Brownian model of evolution should be rejected in favor of one with a directional trend.
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