Hypothesis Testing using Wald Criterion for two regression models with dummy variables
On May 2, 2012, at 15:48 , meredith wrote:
Peter- Maybe I have not articulately my problem clearly, I have had local help with the statistical part just trying to figure out how to correctly program this test. For clarity's sake, I have months worth of data, I want to potentially combine those months into four, shall we say seasons, that have close to the same behaviour. Therefore to do this, I am trying a monthly moving window to categorize these seasons. After talking to a couple water resources statisician's we decided the way to test if the months are different is through the use of hypothesis testing and a dummy variable. So I have one regression, Model A, that includes a zero in the dummy spot with the two months of data combined, then I have another regression, Model B, that includes the interaction term for the changes between the months (the intercept changes, using a 0 or 1 dummy variable). Now we discussed running a Wald testing, Chi squared, to test to see if the interaction term is of importance probability wise, can I do this utilizing anova? Does this make more sense? Then I will run another set of restricted and unrestricted models to account for potential differences in the mean (i.e the slope). Does this explain my problem better?
Not really. It does indicate that Bert is right, though: You need to enlist a local statistician. There are things clearly not understood, which we cannot help you with on this list. -pd PS. This is a mailing list. Please quote context.
Meredith -- View this message in context: http://r.789695.n4.nabble.com/Hypothesis-Testing-using-Wald-Criterion-for-two-regression-models-with-dummy-variables-tp4601582p4603260.html Sent from the R help mailing list archive at Nabble.com.
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Peter Dalgaard, Professor Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com