Linked Questions

3
votes
1answer
1k views

Can we skip the lower order terms in interactions? [duplicate]

This question is about three-way interaction and the possibility of applying without second lower terms with keeping the main variables in the equation not like the other questions. In fact the other ...
1
vote
1answer
818 views

Are lower-order interactions a prequisite for three-way interactions in regression analysis? [duplicate]

I'm applying growth curve modelling and am interested in modelling a three-way interaction between predictors A x B x C. From what I remember a condition for modelling three-way interactions in ...
100
votes
18answers
88k views

Including the interaction but not the main effects in a model

Is it ever valid to include a two-way interaction in a model without including the main effects? What if your hypothesis is only about the interaction, do you still need to include the main effects?
63
votes
4answers
63k views

Does it make sense to add a quadratic term but not the linear term to a model?

I have a (mixed) model in which one of my predictors should a priori only be quadratically related to the predictor (due to the experimental manipulation). Hence, I would like to add only the ...
14
votes
1answer
10k views

Interactions terms and higher order polynomials

If I were interested in fitting two-way interactions between a linear explanatory variable $a$ and another explanatory variable $b$ that has a quadratic relationship with the dependent variable $y$, ...
4
votes
2answers
8k views

Does triple interaction need to include all main effect variables?

I have a triple interaction: AxBxD, where A and B are continuous variables and D is a dummy. My regression is Y = A + B + AxB + AxD + AxBxD In this case, do I HAVE TO include BxD also? In theory here ...
2
votes
1answer
9k views

Testing for moderation with continuous vs. categorical moderators

I am testing an interaction effect where $X$ and $Y$ are continuous variable and $M$ (Moderator) is a categorical variable (effects coding $+1$, $-1$). I have no clue about how to do a post-hoc ...
2
votes
3answers
3k views

Whether to include $x$ and $x^2$ in regression model examining diminishing returns when only $x^2$ is significant?

I have a data set with sales as $Y$ and total retail shelf space ($x$). I want to investigate the diminishing return, i.e. whether additional shelf space would contribute to more sales. I did ...
2
votes
1answer
3k views

Interaction Terms and Logit Models

I have read the previous discussions on interaction effects and main effects, and I have a question on the subject. I am running a destination choice model (multinomial logit), and I have one ...
2
votes
3answers
1k views

What is the meaning of the beta for the interaction between continuous variables in a linear mixed-model?

If I create a mixed-effects linear regression model similar to the following (using the lme4 package in R), where all of the fixed effect variables are continuous: ...
5
votes
2answers
480 views

Testing significant differences between regressions in R

I am running several phylogenetic least squares analyses in R, where I'm taking an existing data set for several species, and adding two new species for which I have data. I want to do is test whether ...
2
votes
1answer
1k views

Why lasso yield a higher mse then ridge?

I do a rige and lasso regression on a train data set and get the lambdas via cross validation and evalute the prediction ...
2
votes
2answers
398 views

To exclude a main effect that is not of interest in ANCOVA, or not? [duplicate]

Possible Duplicate: Including the interaction but not the main effects in a model I have an experimental design with pretest and posttest. Two groups, experimental and control group. I am ...
0
votes
1answer
1k views

Excluding the components and only including the interaction term in a logistic regression? [duplicate]

Possible Duplicate: What if interaction wipes out my direct effects in regression? We have a question regarding a regression we are working on. We have two dummy variables, net income (If net ...
2
votes
1answer
886 views

How does step function selects best linear Models which includes polynomial effects and interaction effects in R?

I try to find "best" linear models with continuous and categorical covariables with Interaction Effect by BIC. The continuous covariables should have a quadratic effect on the response variable. ...

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