Autor des Abschnitts: Danielle J. Navarro and David R. Foxcroft

Auslassungen innerhalb der behandelten Themen

Even within the topics that I have covered in the book, there are a lot of omissions that I would like to redress in a future version. Just sticking to things that are purely about statistics (rather than things associated with jamovi), the following is a representative but not exhaustive list of topics that I would like to expand on at some time:

  • Andere Arten von Korrelationen. Im Kapitel Korrelation und lineare Regression habe ich über zwei Arten von Korrelationen gesprochen: Pearson und Spearman. Beide Methoden zur Bewertung der Korrelation eignen sich für den Fall, dass Sie zwei kontinuierliche Variablen continuous haben und die Beziehung zwischen ihnen bewerten möchten. Wie sieht es aber aus, wenn Ihre Variablen beide nominalskaliert nominal sind? Oder wenn die eine nominalskaliert nominal und die andere kontinuierlich continuous ist? Es gibt tatsächlich Methoden zur Berechnung von Korrelationen in solchen Fällen (z. B. polychorische Korrelation), und es wäre gut, wenn diese einbezogen würden.

  • More detail on effect sizes. In general, I think the treatment of effect sizes throughout the book is a little more cursory than it should be. In almost every instance, I have tended just to pick one measure of effect size (usually the most popular one) and describe that. However, for almost all tests and models there are multiple ways of thinking about effect size, and I would like to go into more detail in the future.

  • Dealing with violated assumptions. In a number of places, I have talked about some things you can do when you find that the assumptions of your test (or model) are violated, but I think that I ought to say more about this. In particular, I think it would have been nice to talk in a lot more detail about how you can tranform variables to fix problems. I talked a bit about this in the sections Transforming variables and Mathematische Funktionen und Operationen, but the discussion is not detailed enough I think.

  • Interaction terms for regression. In chapter Faktorielle ANOVA, I talked about the fact that you can have interaction terms in an ANOVA, and I also pointed out that ANOVA can be interpreted as a kind of linear regression model. Yet, when talking about regression in chapter Korrelation und lineare Regression I made not mention of interactions at all. However, there is nothing stopping you from including interaction terms in a regression model. It is just a little more complicated to figure out what an “interaction” actually means when you are talking about the interaction between two continuous predictors continuous, and it can be done in more than one way. Even so, I would have liked to talk a little about this.

  • Method of planned comparison. As I mentioned this in chapter Faktorielle ANOVA, it is not always appropriate to be using a post-hoc correction like Tukey’s HSD when doing an ANOVA, especially when you had a very clear (and limited) set of comparisons that you cared about ahead of time. I would like to talk more about this in the future.

  • Methoden für Mehrfachvergleiche. Selbst im Rahmen der Diskussion über Post-hoc-Tests und mehrfache Vergleiche hätte ich gerne ausführlicher über die Methoden gesprochen und darüber, welche anderen Methoden es neben den wenigen von mir genannten Möglichkeiten gibt.