Questions tagged [interaction]
A situation where the effect of an explanatory variable may depend on the value of another explanatory variable.
2,576
questions
0
votes
0
answers
14
views
Emmeans and lmer with quadratic and cubic interaction
I have an experiment where I predict that the two levels of my Cond variable (effect coded as -1 and 1) will have different trends over time on my EDA_cs outcome variable (skin conductance). ...
0
votes
0
answers
7
views
Interpretation of interaction term in Cox regression
I am trying in Stata to analyze the effect of an exposure on the risk of an event, and to determine whether this risk increases or not after a temporal cut-off.
I have two groups of subjects, with ...
1
vote
1
answer
57
views
Can p-values help me deduce the following?
Suppose I set up a multiple regression with one continuous variable $X_1$, one (2-level) categorical variable $X_2$, and their interaction $X_1 X_2$.
This will result in four parameter estimates ($\...
0
votes
1
answer
25
views
Comparing the importance of interactions between models
I have two separate models that both use the same set of 10 continuous predictor variables.
Model_1 predicts one binary outcome (symptom_1: present vs. not present) and model_2 predicts another binary ...
0
votes
1
answer
28
views
interactions between variables using Generalized Linear Mixed Model in SPSS
I want to study which factors have an effect on the hormone PTH. PTH is used as a dichotome variable and is our outcome variable, the dependent variable.
We're using generalized linear mixed models in ...
0
votes
0
answers
31
views
Plotting the effects of an interaction term in a FE model
for my bachelor thesis i have the following linear regression model with fixed effects that i use to predict the effects of economic sanctions on GDP:
...
1
vote
1
answer
72
views
How to study what moderates a correlation?
I'd like to illustrate my objective with an example:
Imagine we have collected data on the height, weight, and level of sports activity (represented as either a continuous or categorical variable) ...
0
votes
0
answers
24
views
Interactions in Moderated Regressions with multiple IVs
I have multiple IVs in my moderated regression model, but I want to look at the specific interactions with each of the IVs. Is this possible? I did run the regressions separately but because I have so ...
1
vote
1
answer
46
views
How to deal with a summation term in a regression model?
In the following fixed-effects model, $EI$ is a dummy variable indicating an economic integration agreement in place between $i$ and $j$. $A$ is used to index the specific agreement an $i, j$ pair ...
1
vote
0
answers
6
views
How to evaluate the effect of each group in dummy D to endogenous variable X in 2SLS regression?
I have a question in terms of evaluating the effect of a dummy $D$ to endogenous variable $X$ in two-stage least squares (2SLS) regression.
Suppose I have dependent variable $Y$, endogenous variable $...
2
votes
1
answer
51
views
GAM - factor smooth and main effects for both variables?
I am working with data on cuteness judgements and size judgments for differently named fantasy creatures. The interesting part ...
0
votes
1
answer
33
views
Can sim_slopes handle polynomial models?
I am trying to compare slopes of a simple model with a polynomial effect in R:
> fit = lm(y ~ poly(x, 2)*w, data = df)
here x...
0
votes
0
answers
30
views
How to construct the standard error for the sum of three parameter estimates corresponding to two dummy variables and their interaction term?
I have a simple multiple linear regression model with an interaction term, and I would like to construct a standard error to support interpretation. My goal is to construct a standard error for an ...
5
votes
0
answers
108
views
How to transform basis functions to satisfy a restriction
I am trying to find a way to methodically transform a set of basis functions to satisfy a restriction so that the coefficient of the first basis function at a specific value of $x$ can have a special ...
1
vote
0
answers
20
views
Fixed effects regression for unbalanced panel data (sample size, interaction term, statistical significance)
I have a highly unbalanced panel data set (n= 70 firms, T= 5-3000 observations per firm, N= 15000 observations overall). I specified a fixed effect regression with time and entity fixed effects. I ...
3
votes
1
answer
57
views
Can XGBoost learn more complicated interactions/features?
For a set of features {a, b, c, d . . . n}, XGBoost can easily learn, say, a*d. In practice can it also effectively learn a/c? Or (a + b + c + 2)/d? Or (c^(2d))/(b^a)? I'd imagine some of this depends ...
0
votes
0
answers
17
views
Reporting policy effect for specific subpopulation - how to interract?
I am seeking guidance on model selection when reporting a causal policy effect for a specific subgroup of the panel. I am open to any form of help: paper, maths, intuitions... Below my setup, please ...
2
votes
1
answer
42
views
Sufficient Sample Size for Three-way Interaction from Observational Data (2x2xContinuous)
I'm wondering how one determines the sample size needed to sufficiently analyze a three-way 2x2xcontinuous (logistic) regression interaction using observational data (association study)? Any ...
0
votes
0
answers
17
views
2 x 2 x 2 interaction... need to report the 2 x 2 as well?
I am currently running a repeated measures cross-over design in which participants are completing a cognitive task before and after two different conditions. This cognitive task also has two trial ...
0
votes
1
answer
34
views
Can I include several interaction terms in a regression model?
Can I test 6 two-way interactions in the same regression model (6 interaction terms and 5 simple effects in one model so 11 effects in total)? I have a theory to suspect that two separate variables ...
1
vote
0
answers
16
views
How do deal with multicollinearity, endogeneity and interpret the interaction terms in a panel dataset?
The model
ŷ = b0 + b1X1 + b2X2 + b3X1X2
ŷ =company financial performance metric
X1 = carbon emissions
X2 = carbon assurance
X1X2 = interaction term
The issues:
Let’s say:
• X1 + X2 are related (but ...
0
votes
0
answers
10
views
Analytical form of Linear Mixed Model Regression With Interacting Random Effects?
I have been reading up on Linear Mixed Models with random slopes, and I have a question that I could not find addressed anywhere. I have seen a lot of R model formulae (example) where random slopes ...
0
votes
0
answers
12
views
Centering a skewed predictor variable in a multilevel model that is involved in an 2-way interaction
Is there a correct method to center (mean or median centering) a skewed predictor variable in a multilevel model? The predictor is a skewed, count variable and will feature in a two-way interaction ...
2
votes
1
answer
19
views
Interaction and correlation between two variables?
I fitted a generalised linear model to my medical retrospective data, in which there is
a continuous variable x
a binary variable y
If y is TRUE, x will have high values. Because whatever causes y to ...
0
votes
1
answer
39
views
Interaction terms and emmeans
Please pardon my ignorance, this may be a trivial question. I am fitting a simple linear model with interaction between a categorical predicator and a continuous predictor.
...
2
votes
3
answers
99
views
Interaction terms of one variable with many variables
Suppose that I'd like to analyze the relationship between Y and A, and A moderated by B, and A moderated by C, and A moderated by D, .... and A moderated by J.
I'd then formulate my regression as ...
1
vote
1
answer
33
views
Interaction terms in mixed effects model
I have outcome variable Y with independent variables A, ...., J and variables to control for clustering 'area'. I'd like to assess whether B, ... J inflate or deflate the relationship between A and Y. ...
0
votes
0
answers
13
views
glmer in lme4, interpreting significant sum-coded interaction in the presence of non-significant pairwise comparisons
This is my first question, so I apologize if I am leaving out information. If that's the case, I'll do my best to fix it.
I have two predictors of interest, sentence type (PO, DO) and condition (given-...
0
votes
0
answers
8
views
Can I include interaction effects in a multilevel random intercept, but fixed slope model?
I am using the lmer-command within the lme4-package to analyse a fixed intercept, random slope model:
...
0
votes
0
answers
39
views
Effect size in multiple logistic regression
I have one dummy independent variable, one categorical independent variable with six categories, and two continuous independent variables. The dependent variable is binary (yes/no). The interaction ...
0
votes
1
answer
70
views
Mathematical/statistical notation of a linear regression model with three-way interaction
I am unsure how to present the equation of a three way interaction linear model (without expanding all the interaction effects).
Let me clarify:
$y$ is a continuous outcome measured at time $i$ (for $...
0
votes
1
answer
68
views
Correct specification of cross-level interaction using lme4
For a paper on social norms, I want to predict an individual attitude by an interaction of another individual attitude with attitudes that people within the same region (e.g., cluster) hold.
In the ...
0
votes
0
answers
18
views
GAM: smooth interaction with factor that depends on second factor
I have the following scenario I'm trying to model with mgcv::gam. I have a continuous explanatory variable X whose response depends on factor A. However, That X*A ...
0
votes
0
answers
15
views
About centering to accommodate multicollinearity (Ordinal Logistic Regression Analysis, Logistic Regression Analysis)
When interaction terms are used in multiple regression analysis, often centralization of the variables (subtracting the mean of the variable from each variable) is used to deal with multicollinearity, ...
0
votes
0
answers
13
views
Interaction between continuous and categorical variables in regression
If I have the following regression model:
Where stock price is continuous dependent variable and earnings is a sole continuous independent variable.
Earnings extremity is a categorical variable (three ...
4
votes
1
answer
103
views
Is it possible to use smooth functions as part of a nonlinear regression?
Background
I am fitting nonlinear regressions with a single response and two predictors. I know the relationship between the response and each of the predictors, but I do not know how they interact. I ...
0
votes
1
answer
29
views
Mixed models for repeated measures
I have measures of weight for three countries for 3 time points.
I want to find whether there is a difference in change of weight over time, based on gender accounting for groups (country). I also ...
1
vote
0
answers
37
views
Interaction between two splines in regression analysis
I am modelling differences between the risk of getting chronic kidney disease (CKD) between two groups, group A and B. I have very long follow-up time, approx. 30 years. The trouble is that CKD ...
0
votes
2
answers
63
views
When is an interaction in quadratic regression significant?
I run a regression with a continuous variable $x_2$ and a binary grouping variable $x_1$. We suppose that the effect of $x_2$ is quadratic on the dependent variable $y$ and our question is whether the ...
0
votes
0
answers
24
views
interaction terms to assess effect of a series of variable on the relationship between an independent variable and outcome variable
Let's say that I have an independent variable x1 which I'd like to explore its association with Y (a binary outcome variable). Furthermore I'd like to explore how x1 associated with Y when x2 ...
1
vote
1
answer
19
views
Interpreting Coefficients in the Presence of Interaction Effects
I have a model which estimates the average sqft price based on whether the estate needs renovation or not and whether it is downtown, suburbs or in the transition zone between those two ares. All ...
1
vote
0
answers
45
views
How should I specify a multi-level moderated mediation in lavaan?
I have a repeated measures crossover design where two treatments were delivered to all participants, and measurements of the mediator M and outcome Y were taken following each treatment. I also have a ...
3
votes
1
answer
68
views
Why don't partial dependence plots match model predictions?
Background
My training is in statistics, but I'm interested in machine learning. My models involve nonlinear relationships between 2-5 predictors and a single response (all variables continuous). ...
0
votes
1
answer
89
views
What type of predictive analysis should I use in R?
In my study, there are a continuous dependent variable (fluency scores) and a continuous independent variable as a predictor (anxiety scores). I also include some task conditions (e.g., simple vs. ...
1
vote
1
answer
22
views
Comparing GLMs with and without an interaction term
So I had the base of a model that was based on my hypothesis:
Model 1
...
2
votes
1
answer
52
views
Controlling for a variable when estimating interaction effects
Consider the relationships among four variables: sex, activity, height, and ...
1
vote
0
answers
22
views
What is so special about interactions in regression? [duplicate]
I was recently asked why I haven't analysed interactions in my (predictive) regression model (I understood "interactions" here to mean products of predictor variables). The easy answer is ...
0
votes
0
answers
13
views
Controlling for a Variable, do not know if it is a moderating variable
I conducted a Spearman's correlation to determine if there was a relationship between emotional clarity and cognitive empathy. I found that they were positively associated, but the relationship was ...
1
vote
0
answers
36
views
Interaction between two binary variables in lavaan
I have two binary variables (X1 and X2, coded 0/1) as predictors in a growth model in lavaan. I want to understand their individual contributions and their ...
0
votes
0
answers
10
views
any issues with doing 2 two-way interactions instead of a three-way interactions?
I have data involving 3 key variables (predictors), 2 of them being randomly assigned treatment conditions, and the other denoting the sample (A vs. B). I am finding it easier to present the results ...