Timeline for What do you do if your degrees of freedom goes past the end of your tables?
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8 events
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| Apr 10, 2019 at 13:12 | comment | added | Glen_b | Ah, that might make more sense. Sorry to be dense. I'll try that again. | |
| Apr 10, 2019 at 12:34 | comment | added | whuber♦ | I recall I was referring to item 4. | |
| Apr 10, 2019 at 2:07 | comment | added | Glen_b | ... or is the intent that the errors of the two approaches will be opposite in direction (suggesting perhaps to combine the two?). | |
| Apr 10, 2019 at 1:52 | comment | added | Glen_b | I assume I have missed something here -- I've tried several times to work out which advantage you mean in this improvement over what I did in item 3 (which already treats it as simple function of a chi-squared with small integer d.f., as would be suggested by Slutsky's theorem as df2$\to\infty$). In the example at hand, my approximation is both simpler to carry out and more accurate (e.g. has about 57% of the absolute error). Is this suggestion better at other values of the two df's, or better because it's conservative rather than anti-conservative, ... | |
| Apr 9, 2018 at 10:32 | history | edited | Glen_b | CC BY-SA 3.0 |
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| Mar 17, 2018 at 0:58 | history | edited | Glen_b | CC BY-SA 3.0 |
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| May 8, 2017 at 16:57 | comment | added | whuber♦ |
+1 The $\chi^2$ idea can be improved. Use the fact that $F$ limits to a rational function of a $\chi^2$ distribution as its second parameter grows large. In R, for instance, you would compute it as df2/df1 * (-1 + 1/(1-qchisq(0.95, df1) / df2)). You will obtain $2.2177$, accurate to three significant figures. Note that the $\chi^2$ parameter is a small integer, indicating it will likely be in the table and available without interpolation.
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| May 8, 2017 at 15:43 | history | answered | Glen_b | CC BY-SA 3.0 |