R help - Dec 2008 - p(H0|data) for lm/lmer-objects R

Dear R-List,

I am interested in the Bayesian view on parameter estimation for
multilevel models and ordinary regression models. AFAIU traditional
frequentist p-values they give information about p(data_or_extreme|H0).
AFAIU it further, p-values in the Fisherian sense are also no alpha/type
 I errors and therefor give no information about future replications.

However, p(data_or_extreme|H0) is not really interesting for social
science research questions (psychology). Much more interesting is
p(H0|data). Is there a way or formula to calculate these probabilities
of the H0 (or another hypothesis) from lm-/lmer objects in R?

Yes I know that multi-level modeling as well as regression can be done
in a purely Bayesian way. However, I am not capable of Bayesian
statistics, therefor I ask that question. I am starting to learn it a
little bit.

The frequentist literature - of course - does not cover that topic.

Thanks a lot,
best,

leo g?rtler

This is very opaque to me. But if H0 is a null hypothesis (i.e. a hypothesis
about one or several coefficients in your model), then you can test linear
or nonlinear restrictions of the coefficients. Because your coefficients are
derived using your data, it appears to me you get something like a
p(H0|data).


-------------------------
cuncta stricte discussurus
-------------------------

-----Urspr?ngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im
Auftrag von Leo G?rtler
Gesendet: Thursday, December 25, 2008 1:52 PM
An: r-help at stat.math.ethz.ch
Betreff: [R] p(H0|data) for lm/lmer-objects R

Dear R-List,

I am interested in the Bayesian view on parameter estimation for multilevel
models and ordinary regression models. AFAIU traditional frequentist
p-values they give information about p(data_or_extreme|H0).
AFAIU it further, p-values in the Fisherian sense are also no alpha/type  I
errors and therefor give no information about future replications.

However, p(data_or_extreme|H0) is not really interesting for social science
research questions (psychology). Much more interesting is p(H0|data). Is
there a way or formula to calculate these probabilities of the H0 (or
another hypothesis) from lm-/lmer objects in R?

Yes I know that multi-level modeling as well as regression can be done in a
purely Bayesian way. However, I am not capable of Bayesian statistics,
therefor I ask that question. I am starting to learn it a little bit.

The frequentist literature - of course - does not cover that topic.

Thanks a lot,
best,

leo g?rtler

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