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Confidence intervals around treatment effect in stratified experiment

Taking your questions in turn: Adjusting for pre-experiment run-times is not strictly necessary in a randomized experiment, but you'd want to do it, because it makes inference more efficient (because ...
Björn's user avatar
  • 32.3k
3 votes
Accepted

Why do interaction terms work?

The question seeks an explanation what is happening to the column space of a design matrix, when you add new a column by multiplying two existing columns. Almost without exception, interactions are ...
whuber's user avatar
  • 323k
0 votes

Modeling longitudinal change in outcome per unit of change in a continuous explanatory variable

does the visit:wlp interaction without main effects give me the change in outcomes (gene expression) per wlp at the two ...
EdM's user avatar
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0 votes

Block-treatment interaction for Randomized Block Design (RCBD) and Generalized Random Block Design (GRBD)

I am surprised this is not answered on site so far (at least I cannot find it by search). We suppose balanced designs. First the unreplicated case, then the analysis is by a two-way anova. Let the ...
kjetil b halvorsen's user avatar
2 votes

Mixed models - interactions or individual regression

In general, the interaction model would enable you to test if a treatment works better for one group than for another. With separate groups you would only see that there is a difference in treatment ...
BenP's user avatar
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8 votes
Accepted

Should I run a moderated regression or a regression on a subset of my data?

First, just running a model only for those who have a PhD won't answer your question, because it gives you no information about whether your iv predicts the DV among people who do not. Second, it ...
Graham Wright's user avatar
0 votes

Comparing two models from the "fish" dataset

Consider the 5 models below. fm1 is Model 1 from the question. fm2 is just a different way of writing it. fm3 uses / notation and is similar to fm4 but is a single model. fm4 is equivalent to running ...
G. Grothendieck's user avatar
0 votes

Conceptual Question about Interactions

... is significant for roughly 85% of the individuals assuming a normal distribution? No, that cannot be true. It is not entirely clear what you intends, but there is no reasonable interpretation ...
kjetil b halvorsen's user avatar
1 vote

Comparing two models from the "fish" dataset

You should almost always include the main effects when fitting an interaction. Some call this the "hierarchical principle". Logically, it is odd to only consider an interaction independent ...
Shawn Hemelstrand's user avatar
1 vote

Adding predictors to an intercept-only model

You have two good answers already. But I think your experimental design is less than optimal. What I would do is randomly assign the animals to train and test. Then use "was trained" as an ...
Peter Flom's user avatar
  • 120k
1 vote

Interpreting interaction coefficients between continuous and categorical variables + interaction plot with confidence bands

Regarding your first question: Your interpretation is correct. Is the first coefficient "meaningful"? Well you can use it (and the other coefficients) to get the predicted level of overall ...
Peter Flom's user avatar
  • 120k
1 vote

Regression with depended predictors, animal study sample size

Yes, you can include them, and yes you should include an interaction if you have a theoretically justifiable reason to do so. Here it makes sense to do, as we would almost always expect there to be ...
Shawn Hemelstrand's user avatar
1 vote

Beta regression for interaction terms without full rank? (R)

Answer: Based on your description, I think that your assessment is correct: betareg() cannot estimate all coefficients because there are some factor combinations ...
Achim Zeileis's user avatar

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