A situation where the effect of an explanatory variable may depend on the value of another explanatory variable.

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6 views

create interaction term between binary variables in path analysis use R lavaan package

I am using R lavaan package to do a path analysis. In my model: X ~ A + B Y ~ A + B + X Both A and B are binary factors. So, in lavaan they will be treated with dummy coding. That is, A (0, 1) and B ...
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13 views

Significant interactions force main effects to be insignificant and plus change their sign--how to interpret? [duplicate]

I've read through many similar posts regarding significant interaction wiping out the significance of main effects, but since there were no questions regarding changing signs I decided to post another ...
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9 views

How can I ENTER a 4-way interaction in a hierarchical regression blocks in SPSS? [closed]

I have 4 variables, and I want to compute their interaction in a hierarchical multiple regression. But I do not know how I put main and interaction of variables in blocks of hierarchical multiple ...
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22 views

How to visualize a significant interaction between two linear predictors using the rms package?

Two linear predictors interact significantly (see below). How can I visualize this interaction in a plot? ...
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1answer
18 views

Covariance between a variable and an interaction variable

If I have two independent variables $X$ and $Y$, then $Cov(X,Y)=0$. Now let $Z = X*Y$. Then I would assume $Cov(X,Z)\ne 0$, but given the expecations, variances and covariances of $X$ and $Y$ is there ...
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1answer
38 views

R - moderated mediation using the lavaan package

I am interested in determining the conditional indirect effects of X on Y at a series of values for a third variable Z. I was able to use the lavaan package to calculate some initial indirect ...
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7 views
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18 views

Cox Time Series Data — Analysis of Interaction Terms

In a time series data set using Cox Proporational Hazard Rate, I am testing a model with interaction terms. I am worried that my interaction term is biased by several specifications of my model and I ...
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1answer
27 views

How do I calculate the odds ratio in a logistic model with an interaction term (categorical)?

In the following logistic regression model, I am trying to model the logit of Y, where Y is a binary variable (Yes or No). Let my model be: logit($Y$) = $\beta_0$ + $\beta_1$*$x_1$+ $\beta_2$*$x_2$+ ...
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25 views

Interactions terms and Heckit/Tobit models in Stata

I am trying to read on how to interpret interaction effects in Heckman's selection model and come across with this article On Marginal and Interaction Effects: The Case of Heckit and Two-Part Models. ...
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1answer
19 views

Linear regression with interaction SPSS

I have to run a linear regression analysis with an interaction effect of two categorical variables: Modality (audio, visual and audio-visual) Repetition (1x, 2x and 4x) I have already dummified ...
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17 views

linear mixed model with paired and unpaired effects

Here is my problem: 20 subjects performed different movements: arm flexion, abduction and rotations [Ma, Mb, Mc]. In addition each of these movements were performed with or without a load of 3 kg ...
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1answer
37 views

X and Y are uncorrelated, but X becomes significant when X*A is included in model

At the zero-order level, X is not correlated with Y. When I add X and A into a regression analysis to predict Y, only A is a significant predictor. A itself is correlated highly with Y at zero-order. ...
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13 views

Unconditional versus conditional regression model. Strange results, or?

Hope someone can help me figure out these strange results. I am performing a categorical analysis, and I have a conditional regression model, where a categorical variable Z (0-1 dummy) is interacted ...
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1answer
38 views

Multinomial Logit Interaction Term

i have a multinomial logit model of the form $y= \alpha + young + year + \lambda_i + (young*year)+ \mu $ where $y$ represents three possible labour market states that an individual can be in. ...
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45 views

What statistical approach to use for this kind of analysis?

I have 1 dependent (continuous) variable, 3 explanatory (continuous) variables and a bunch of control variables. The explanatory variables are my interest variables.I want to do a categorical ...
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14 views

Interpretation of year interaction terms

I am currently specifying a multinomial logit model estimating labour market transition probabilities using quarterly survey data. I have two specific explanatory covariates that I am particularly ...
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1answer
58 views

Differences in nlme output when introducing interactions

I am searching for correlations between a dependent variable and a factor or a combination of factors in a repeated measure design. So I used lme() function in R. However, I am getting very different ...
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25 views

Seperate regressions approach vs. interaction term approach

I am writing my thesis in finance, and my thesis advisor want me to do a categorical analysis, where I include control variables. He tells me I cannot simply include interaction terms (i.e. category x ...
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1answer
18 views

Simple effects of categorical interaction

I have two two-level categorical variables, IV1 and IV2. I want to fit a linear model in R and find out the simple effect of IV1 on the DV at each level of IV2, separately. I'm not interested in the ...
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1answer
52 views

Interpretation Interaction in Cox Regression

I am estimating a discrete choice model with the help of cox regression in SPSS. I would like to interact two continuous predicting variables. The main effect of one of the ineracting variables is ...
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24 views

How to partition $R^2$ among predictors in multiple regression with interaction terms in R

Say I have some predictors, and I know how they affect some dependent variable: ...
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1answer
32 views

How do I interpret interaction effects in a log-log regression model?

I have the following model: $\log(y)=\beta_0 + \beta_1 x_1 + \beta_2 \log(x_2) + \beta_3 x_1 \log(x_2) $ In interpreting the % change of $y$ that corresponds with a 1% increase in $x_2$ at a ...
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20 views

the statistically opposite sign of the interaction that I hypothesized

Although the Beta value for BO X SS is significant, its positive sign is against the hypothesis! it's supposed to have a negative sign according to the literature & also logic! How should i treat ...
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8 views

The difference between adding a main effect of Factor C, and also adding an interaction between Factor A and C into a regression model?

I have a logistic regression model with two dichotomous predictors: Factor A and Factor B. I found that there is a significant main effect of both Factor A and Factor B. Now suppose I want to see if ...
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24 views

permanova or non-parametric test for multiple explanatory variables and interaction

Hi I am trying to find a test to analyse the following data set. Response variable is failure or success (0 and 1) measured over 4 time points, under 2 different treatments (light and temperature) in ...
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13 views

How to incorporate characteristics of the object of outcome variables as predictors in model

I'm working with survey data for a social science research topic. The particulars aren't super important, so I'll use a simplified version to make it easier to understand what I'm trying to do. I say ...
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44 views

R square change for 2-way interaction model

I want to test a regression model with neuroticism as focal predictor, agreeableness as moderator and RT variability as dependent measure (covariates: attentional control and mean RT). Previously, I ...
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1answer
28 views

One main effect and one interaction in R using multiple regression, is that possible? And why am I getting two interaction terms in output?

I have two factors that are fully crossed, the levels of the factor are each coded 0 and 1. I am running a regression testing for one main effect and one interaction. The following is my logistic ...
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1answer
33 views

Why do we ignore the main effects when the interactions are not significant in a three-way ANOVA?

I'm following an SPSS guide online, and the procedure is to first test for a three-way interaction. In my case there was no sig. three-way interaction. Then the procedure asks me to consider two-way ...
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1answer
24 views

How to check if the correlation between two continous variables is influenced by a categorical factor?

I have a data frame (df) where I see correlation between two continuous variables (c1 and c2). I need to know whether the observed correlation between the two variables differs between groups, which ...
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48 views

Multivariate Mixed Model With Continuous Independent Variable - SPSS or R?

I've been trying to find an appropriate statistical technique to analyze multiple IVs and DVs with no luck. The IVs include 1 trichotomous within-subjects factor, 1 dichotomous between-subjects ...
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2answers
83 views

Computing R-squared change, F-, and p-values for the interaction / moderation term [closed]

I would like to compute R-squared change for the interaction/moderation term in a multiple regression model, along with the corresponding F- and p-values. Previously, I have worked with the modprobe ...
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17 views

Permutation to test SNP interactions

sampleID case/ctrl var1 var2 var3 var4 var5... sample1 0 1 0 0 1 0 1... sample2 1 0 0 0 0 1 0... sample3 0 1 1 1 0 0 0... sample4 1 0 0 0 0 1 0... ... case/ctrl status is binary, variant status is ...
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14 views

Mixed ANOVA interaction effect - How do I which treatment was more effective?

I have conducted a mixed between-within ANOVA with 3 intervention groups and 2 measurement times (pre/post) in SPSS. There was a significant Time*Group interaction, but significant main effects. How ...
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16 views

Interpreting an apparent inconsistency - fitting regression models on subsets suggested by an interaction

Say we learn a linear regression model with three continuous predictors $X_1$, $X_2$, and $X_3$ (along with interaction terms $X_1X_3$ and $X_2X_3$), for some variable Y. The fitted model suggests a ...
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1answer
42 views

How to calculate the effect size of differences in groups using dummies in multiple regression?

I am running a multiple regression analyses on a sample of 1800 respondents. The dependent variable is the mean of a 5-point likert scale and I have 6 predictors (antecedents) also using mean of ...
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21 views

Interpreting interaction between time and time-varying predictor in mixed models

I have measured the DV and predictor at 2 timepoints in a single group, and am using the MIXED procedure in SPSS. I want to see whether change in the DV over time is predicted by change in the ...
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10 views

What's the drawback of using interaction terms to analyze the pre-post control data?

I am trying to analyze the data with the pre-post-control design in the context of RNA-seq analysis. I have read Best practice when analyzing pre-post treatment-control designs, but I am still ...
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10 views

How to automatically add 2-way interaction terms in SAS proc hplogistic

I am trying to run a model using SAS proc hplogistic. The syntax I used is (this is just an example, the actual data set has 100 independent variable, so it's difficult to type all interaction terms ...
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39 views

Difference-in-differences model: do I have to include hierarchical terms with interaction term?

I am contemplating using a DiD model to see the effect of an intervention on population attitudes. My DVs of interest are ordinal (Likert-style) and binary. I have two agencies measured at two time ...
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1answer
18 views

How to interpret simple effect of a variable interacted with several others?

I am sure this has been asked before (similar here but no answer). But I have not found an answer yet. To give you a short frame: I am researching firm level data and I am ivestigating several ...
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1answer
32 views

Interpreting interactions when main effect is not significant

I just started fooling around with R and I am quite struggling with mixed models: I have the following experimental layout: Seven different viruses, including ctrl virus; 27 mice, randomly infected ...
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2answers
77 views

Representing interaction effects in directed acyclic graphs

Directed acyclic graphs (DAGs; e.g. Greenland, et al, 1999) are a part of a formalism of causal inference from the contrafactual interpretation of causality camp. In these graphs the presence of an ...
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1answer
72 views

Does it make sense to interact two continuous variables in econometrics?

Let's say I have three variables: Variable A, B and C, where C is the product of A and B. Both A and B are continuous variables. If I regress Y onto A and B, A is significant and B is not. Then, if ...
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59 views

Is it possible to use several interaction terms?

I came across this equation when I was reading the article: $$\textrm{Y} = \alpha + \textrm{X}_1 (\beta_0 + \beta_1 \textrm{X}_2 + \beta_2 \textrm{X}_3) + \varepsilon$$ At least, I can understand ...
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1answer
17 views

Testing the utility of adding a continuous variable to a nonlinear regression.

Let’s say I have the hypothesis that soil fertility affects the relationship between weed biomass and crop biomass. One way to go about testing that hypothesis might be to model the relationship ...
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1answer
37 views

Model change after switching reference level in R logistic regression model with interaction

I'm fairly new here so my apologies if I'm asking something obvious. My problem is the following: I have a dataset in which I want to examine the interaction of a risk-factor with an intervention to ...
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46 views

Question about fixed-effects/time-effects model in R/plm

I have a few questions about using the plm package's models to get fixed effects and time effects. Here's a basic sketch of the code: ...
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21 views

glmnet for Mixture Model

I have a distribution that looks like a Gaussian Mixtures And then I use Python's GMM Classification package to cluster them into clusters and then perform glmnet on each of the cluster. Is this ...