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Use this tag for any *on-topic* question that (a) involves `R` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `R`.

3 votes

Comparing two models using anova() function in R

The Pirate's Guide to R", Chap.15.3: The anova() function will take the model objects as arguments, and return an ANOVA testing whether the more complex model is significantly better at capturing the …
András Aszódi's user avatar
3 votes

Comparing two ECDFs using Kolmogorov-Smirnov test (alternative hypothesis)

First, please note that your understanding of what the p-values mean is not correct. E.g.: Hypothesis #1: two-sided (equal) The probability that both distributions are the same is 2.03% (p-va …
András Aszódi's user avatar
0 votes

Comparision of multiple curves in R using linear mixed models

I am not sure whether there's an easy way in R to do this with e.g. orthogonal polynomials, but maybe this idea will inspire you to try it out :-) …
András Aszódi's user avatar
0 votes

Raw or orthogonal polynomial regression?

: 0.984, Adjusted R-squared: 0.9779 F-statistic: 160.1 on 5 and 13 DF, p-value: 3.34e-11 Points to note: The residual standard error, the $R^2$ values, the F-stats are exactly the same as before … As regards the model quality: Residual standard error: 0.05044 on 15 degrees of freedom Multiple R-squared: 0.9829, Adjusted R-squared: 0.9795 F-statistic: 288.1 on 3 and 15 DF, p-value: 1.768e- …
András Aszódi's user avatar
0 votes

Why do we say "Residual standard error"?

For the nls (nonlinear least squares fit) R function, the "Residual standard error" seems to be: $$\sqrt{\frac{\mathrm{RSS}}{n-p}}$$ where RSS is the "residual sum-of-squares", n is the number of observations …
András Aszódi's user avatar
1 vote

Poisson model for non-integer

@jbowman said that "You can in fact run a Poisson regression on non-integer data, at least in R; you'll still get the "right" coefficient estimates etc.". … : 0.9976, Adjusted R-squared: 0.9976 F-statistic: 1.228e+04 on 1 and 29 DF, p-value: < 2.2e-16 If I run a Poisson GLM in R using log(N) as the offset I get a very similar result: Call: glm(formula …
András Aszódi's user avatar