# Recent content by ooostats

1. ### Repeated measures ANOVA trend analysis is confusing me

Well these are actually what I would like to understand. I know that I want to follow up on my ANOVA, and I expected my DV to show a similar effect to the one in the example. I initially did some pairwise comparisons because I did not know any better, but my supervisor suggested to me that trend...
2. ### Repeated measures ANOVA trend analysis is confusing me

I'm trying to understand how trend analysis works with respect to repeated measures ANOVA, but I'm a bit confused and have some questions. My first question at the bottom of this post is the thing I'm most interested in. I'm using SPSS, but it is unclear what is going on with the outputs and the...
3. ### Advice on repeated measures ANOVA vs multi-level model

interesting, i can't wait to click on the link you sent - I bet it's going to answer my question perfectly.
4. ### Advice on repeated measures ANOVA vs multi-level model

Hello! I have a situation that I have never encountered before, but I think I know what the issue is. Nevertheless, I could use some assistance. I ran an experimental study with a within-subjects design. Subjects learned words under 4 different conditions (A,B,C,D), 30 words in each condition...
5. ### One-way ANOVA with string variables as factor

I think you might need to code these as discrete numeric values rather than strings. Let's say in a study testing the effects of 3 different drugs between people, I'll create a factor (column) called "Drug" and it will take on values 0, 1, and 2, where the values might correspond to placebo...
6. ### Normality: DV itself or residuals?

There are lots of interesting points raised in this thread that I'll no doubt be going back to. One thing that I'm a little confused about though is what you said (@spunky): Why are parametric assumptions only really important for inference and not modeling in general? For example if I have...
7. ### Normality: DV itself or residuals?

I guess I tend towards this opinion as well. Although I also think that this gets blown way out of proportion: Some sub-fields are much worse than others, and in different ways (e.g. theoretical vs statistical vs experimental design & control), and journal companies are def not helping given...
8. ### Normality: DV itself or residuals?

Yeah this is what he means. Interesting post. I would like to learn as much as I can about all of this now, just I don't have a maths background so this is quite heavy. And that's the thing, if it were taught in psych classes then it would be quite pointless because most wouldn't have a clue...
9. ### Normality: DV itself or residuals?

Well I do have to say that the Field book is the best book I've used, maybe it's just me not getting my head around this in general. He does state that normality refers to the residuals of the model, "or the sampling distribution". However, we don't have access to the sampling distribution so we...
10. ### Normality: DV itself or residuals?

Good point. I guess I'm one of those students then! So could you both please recommend a textbook/resource that covers these topics correctly? All I ever hear about is Andy Field's book, but I can't see him covering this in a definitive way. On one page we should check assumptions, and our DV...
11. ### Normality: DV itself or residuals?

Not so much counter intuitive, just completely the opposite of what I thought I was being taught! I study psychology, and all resources explicitly talk about checking assumptions prior to applying tests. It makes me wonder whether people teaching/writing the textbooks don't fully understand it...
12. ### Normality: DV itself or residuals?

Thanks, I'll give it a read. Just skimming over the part on normality though, it seems the assumption of normality depends on the difference between the observed data and the regression model's predictions i.e. the residuals. But what I don't understand is that in order to find out what the...
13. ### Normality: DV itself or residuals?

I always thought that we should be testing the assumption of normality by looking at the distribution of the DV in our design (by each level of the IV). But I keep seeing people talking about the residuals of the DV. For example, in ANOVA (and I suppose by extension the t-test and regression)...
14. ### Basic Stats - T-test, ANOVA, Chi sq?

Also, you mention that you are looking at "the mean BMI (normal, overweight, obese)". BMI is a continuous variable, whereas the classifications of BMI into normal/overweight/obese means you treat it as a categorical variable. In either case, you should be clear as to what level of measurement...
15. ### small sample size problems

Right, but how can the results possibly be interpretable? Whatever the result, the risk of it being a T1/T2 is too high. Also if any test were to be used, shouldn't it be a Mann-Whitney U?