Dear list,
I would like to know the impact of concurvity , the non-parametric analogue of
multicollinearity, on the standard error of coeffients when we use GAM. I
wonder if the standard errors produced by summary.glm in S-plus can be
smaller than the true standard errors of the estimated parameter. For example,
the model is
fit_ gam(mortality ~ lo(time) + pollution, .......)
where time and pollution are higly correlated. Do I need to worry that the
estimated standard errors are too small when multicolinearity exists?.
Can standard errors from summary.glm lead one to conclude that the effect
of pollution is statistically significant when in fact it is not? If the
standard errors
from summary.glm are not good estimates of the true standard errors, is there
any other way to get the correct standard errors?
Thank you very much.
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