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| * log() DV, log() IV | | * log() DV, log() iv |
| * polynomial terms and interaction terms both with: I() | | * polynomial terms: I() |
| * logistic regression
| | * graphing residuals against fitted values (not just against different values of x |
| ** create a dummy variable: mpg > mean(mpg)
| | * discussing anova better |
| ** glm(formula, family=binomial("logit"))
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| two things worth returning to:
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| * graphing residuals against fitted values (not just against different values of x) | |
| * discussing anova() better. The key thing I didn't talk about is about different types of "sum of squares" which are discussed in depth on [https://afni.nimh.nih.gov/sscc/gangc/SS.html this page hosted by the NIH]. By default, SPSS produces Type III standard errors although these [https://myowelt.blogspot.com/2008/05/obtaining-same-anova-results-in-r-as-in.html very frequently not what you want]. | |
| ** Getting the same results in R is easy enough though: library(car); Anova(fit, type="III")
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