Timeline for Test GLM model using null and model deviances
Current License: CC BY-SA 3.0
7 events
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| Apr 12, 2015 at 17:57 | comment | added | gung - Reinstate Monica | @jesterII, no the null hypothesis is: 'the model as a whole is no better than the null model'. Since this has been rejected, we conclude that the data are not consistent with the null model. NB, this does not necessarily mean that our model is 'good' or 'correct'. | |
| Apr 12, 2015 at 17:55 | comment | added | jII | The null hypothesis is 'the model as a whole is better than the null model', and you have rejected the null hypothesis, which means the model is poor? | |
| Apr 12, 2015 at 17:50 | comment | added | gung - Reinstate Monica | @jesterII, you are checking if the deviance changed more than might be expected by chance. Ie, you are testing if the model as a whole is better than the null model. It is analogous to the global F test in a linear model. | |
| Apr 12, 2015 at 17:30 | comment | added | jII |
What hypothesis exactly are you testing with the statement 1-pchisq(256600 - 237230, df=(671266 - 671263))?
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| Mar 11, 2015 at 2:25 | history | edited | gung - Reinstate Monica | CC BY-SA 3.0 |
deleted 1 character in body
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| Mar 10, 2015 at 18:06 | vote | accept | Zfunk | ||
| Mar 10, 2015 at 17:52 | history | answered | gung - Reinstate Monica | CC BY-SA 3.0 |