Thanks,

Tyler

- Thread starter t.searls
- Start date
- Tags heteroscedasticity least squares non normal ols residuals residuals non-normal

Thanks,

Tyler

In the case of a transformed dependent, predictor coefficients are now related to a log-transformed dependent rather than the dependent itself.

That is to say the coefficient for mean temperature can no longer be interpreted as 0.9 degrees to each centimeter growth increment?

This would be problematic since, as I've said, the intent of the study is to explore these relationships more than establish a idealistic fit. Still, in order to explore these relationships, the model needs to have merit. This is my dilemma.

Thanks again,

Tyler

the intent of the study is to explore these relationships more than establish a idealistic fit. Still, in order to explore these relationships, the model needs to have merit.

to meet some more or less sensible model assumptions. Here we have a substantial

argument in fovour of a transformation. Since growth is exponential, a linear model makes

only limited sense

That is to say the coefficient for mean temperature can no longer be interpreted as 0.9 degrees to each centimeter growth increment?

Although Ln would be the more appropriate choice for biological processes, at least so I was told.

Moreover, you could plot relationships on a logarithmic rather than a linear scale

With kind regards

Karabiner

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