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Deviance as a measure of fit

What you are missing here is the hypothesis testing. We have: $$H_0:\beta_{p+1} = \beta_{p+2} = ... = \beta_{q} = 0$$ $$\text{vs}$$ $$H_1:\beta_i \neq 0 \text{ for some } i \in \{p+1,...,q\}$$ where $...
sunnydk's user avatar
  • 57
1 vote

Pearson chi squared test vs deviance test in GLM

Generally, the G-test is useful in case of categorical data, but when we see the concept of "Goodness of fit", the more powerful test is chi-square test as compared to the LRT. Also I would ...
Awais Munir's user avatar
0 votes

Why do I get very bad fit indices for a moderation? (including a negative TLI!) / Multilevel Model

I would need to know more about your model and data to recommend anything besides looking at modification indices (i.e., what @Erik Ruzek and @michael_zyphur suggest you do). Though my guess is that a ...
Preston Botter's user avatar
1 vote

Use of weights in non-linear least square fitting

A nice reference relating to this question is The conditions under which chi square measures the discrepancy between observation and hypothesis Fisher RA 1924 Journal of Royal Statistical Society, 87, ...
Sextus Empiricus's user avatar
4 votes
Accepted

Deriving Sample version of Anderson Darling test statistic from the theoretical version

Let $U_{in}:= F(X_{in});$ for brevity though, we would write $u_i$ in place of $u_{in};$ take $u_0=0,~u_{n+1} = 1.$ Define $\psi(x):= [x(1-x)]^{-1}.$ Anderson-Darling statistic is given by $W_n^2:= n\...
User1865345's user avatar
  • 7,932
1 vote

How to determine which distribution fits my data best?

I recommend https://phitter.io. Fit distributions and document them. (I'm the creator)
Sebastian Jose's user avatar

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