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

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2
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2answers
66 views

mediator or moderator variable?

I have been given a set of data and I am confused as to whether one of the variables is a moderator or mediator variable. The hypothesis is that stress and well-being have an inverse relationship. ...
0
votes
2answers
31 views

Interaction effect 2x2

I have a little question about a 2x2 design that keeps on confusing me. If I have this kind of 2x2 design where I can have these combinations in the conditions. No/No, Yes/No, No/Yes, Yes/Yes. The ...
1
vote
1answer
11 views

Help with determining model for cross-sectional data where all variables are dummies

I am currently working on my dissertation project where my data are essentially all dummies. From my dependent to my independent variables, everything is a dummy variable (0,1), at least for the ...
0
votes
0answers
6 views

Finding Significant Interactions for Linear Model with Experimentally Measured Interaction

Consider an experiment that has four groups, and all of them have experimental replicates. No treatment Treatment X Treatment Y Both X and Y When I fit an interaction model, and check the raw ...
0
votes
0answers
17 views

Interpretation and visualization of lmer output

I am trying to correctly interpret the output of my lmer-model and I also want to visualize an interaction contained in the model based on the intercept values. My variables and levels are Training ...
1
vote
0answers
41 views

Contradicting interaction significance with graphical visualisation in glmer

I'm investigating environmental effects (wind) on acoustic receiver detection probability for two types of transmitters using a binomial glmer. While my model analysis indicates that there's a ...
0
votes
0answers
9 views

Power estimates for an interaction in a 2X2 factorial design with a proportion outcome

I am trying to calculate the power that I will have to detect an interaction between 2 different interventions in a 2X2 factorial design. We aim to have about 850 participants in each of the four ...
0
votes
0answers
26 views

Interaction in a repeated measures logistic regression

I want to test for the effect of interaction between two variables using a repeated measures logistic regression but I don't know how. I am using Stata and the following lines: ...
0
votes
1answer
31 views

Stata ANOVA Interaction term differences

The following two statements produce different results. ...
0
votes
1answer
20 views

testing for mediation of interactions

I am somewhat familiar with various ways of testing mediation for factors in different types of regression analysis. (I'm using R and currently working with a multilevel binary logistic regression.) ...
0
votes
0answers
11 views

Follow up a significant interaction in ANOVA with dichotomous variables

Hopefully this is an easily answerable question, though I've been searching for an answer without any luck. I've run a 2x2x2x2 mixed-design ANOVA with two within-subjects and two between-subjects ...
1
vote
1answer
55 views

Doing post-hoc after a not significant interaction in mixed ANOVA

I conducted a mixed design ANOVA with two within-subjects factors: FactorA (2 levels), FactorB (2 levels), and one between-subjects factor: Group (2 levels). My main hypothesis regards the interaction ...
0
votes
0answers
15 views

Testing linear contrast in an unbalanced longitudinal design (R)

I'm experiencing some conceptual problems in testing a linear contrast in an unbalanced longitudinal design. I have performed some correlation analysis with brain imaging data. These analysis ...
1
vote
0answers
42 views

F-ratio in repeated-measures ANOVA

In factorial designs with one random factor and one fixed factor, the expected mean square for the fixed factor does contain three sources: the main effect, the interaction, and error Therefore, to ...
2
votes
1answer
35 views

How to prepare interactions of categorical variables in scikit-learn?

What is the best way to prepare interactions of categorical features before fitting with scikit-learn? With statsmodels I could conveniently say in R-style ...
0
votes
0answers
16 views

categorical variables in regression analysis and interaction terms

I am learning multiple regression with categorical variables and in a book I came across this problem. For yield of corn suppose there are two factors affecting, nitrogen level and depth of ...
4
votes
1answer
50 views

Nonparametric ANOVA with interaction?

Is there any nonparametric version of ANOVA able to deal with multiple factors AND evaluate their interaction(s)? If the interactions are really impossible to evaluate, is there any generalization of ...
0
votes
1answer
33 views

Multilevel model where an interaction is a varying slope

I have a multilevel problem where I want to have a random intercept and a random slope. However the random slope is the interaction of two predictors. In this case, do I also have to allow random ...
1
vote
0answers
20 views

Methods to analyze a cross-over interaction between a factor and a continuous variable?

I'm wondering what would be the best method to analyze a "cross-over" interaction between a factor and a continuous variable. Here's my experimental set-up and hypotheses in a nutshell: 58 ...
0
votes
0answers
18 views

Interaction terms in regression-theory

I am learning categorical variables and interaction terms in the regression course and there few things I don't understand. Suppose a salary data set with predictors experience $X$ in years ...
0
votes
0answers
18 views

interaction terms with opposite signs compared to the main variables

here I am again with another question. I am using interaction terms in my model. Problem is that no matter what specification or variable construct I try, interaction term always has opposite sign ...
0
votes
0answers
32 views

Please help with basic interpretation of an insignificant interaction. (With significant main and conditional effects)

I have a very basic understanding of statistics, and have done many correlations and regressions or simple t-tests, but never an interaction and it is confusing me a bit. I only need to understand the ...
0
votes
1answer
45 views

Interaction insignificant, main effects significant

I am using modprobe syntax on SPSS to test an interaction between narcissism and rumination on a dependent variable, aggression. I get a significant effect of rumination (b = .6450, t = 2.32, p = ...
2
votes
1answer
65 views

I don't understand the figure output from package lme4 in R using the effects library?

I am using linear-mixed effect models to analyse my data (the interaction between on and arc; both ...
2
votes
1answer
53 views

Interaction effects in big data sets

I'm looking for a method to identify a shortlist of potentially good 2-way interaction terms rather than trying all possible interactions. This question is similarly asked before here but in a more ...
0
votes
1answer
22 views

Problems with interpretation in zeroinflated models in R

My response variable is number of Fishing cat scats and I am using a zero-inflated poisson regression model to see the effect of the predictor variables on habitat use of Fishing cats. The predictor ...
0
votes
0answers
27 views

What to do with interactions that improve the model fit but are not significant?

I'm using Poisson loglinear regression (from Generalized Linear models, SPSS) to analyze different patient variables that influence LNT-lymph node yield-(poisson distribution). After removing the main ...
1
vote
0answers
19 views

Kruskal-Wallis test for factorial design [duplicate]

Is it possible to use the Kruskal-Wallis test for two factors and their interaction (i.e., two way ANOVA: Y~a*b)? And which post-hoc test is possible to use after ...
0
votes
0answers
13 views

PROCESS Hayes | Interaction Insignificant | 2/3 Conditions Significant

When using PROCESS by Hayes I get a insignificant interaction effect but 2/3 of the conditional effects are significant. Is there still something I can say about this in my results? So for instance, ...
0
votes
2answers
29 views

How many parameters in this specific linear model with interaction?

I have a question where I am not sure about the answer: A linear model has the following characteristics: *A dependent variable ($y$) *One continuous variable ($x_l$), including a ...
0
votes
0answers
27 views

Include interaction in multiple imputation - r

I'm doing some imputation models of time until recurrence of tuberculosis (Cox model). This model should include an interaction between the time and the outcome of the previous episode of disease (0- ...
0
votes
0answers
43 views

Logistic regression power analysis with moderation between categorical and continuous variable

I've been reading Simulation of Logistic Regression Power Analysis - Designed Experiments, http://sas-and-r.blogspot.com/2009/06/example-72-simulate-data-from-logistic.html, and Power analysis for ...
0
votes
1answer
39 views

Does the result of “interaction” tell whether nor not the moderator variable worked?

I’m reading a research paper and the author prepared two print-advertisements of jam, one with an old lady (Ad1) the other one with an exotic lady (Ad2). Both print-advertisements (Testanzeige) have ...
0
votes
1answer
21 views

Reparametrisation of a model when an interaction is significant to facilitate the interpretation

It is admitted that it is complex to interpret main effects when they are involved in an interaction. Lets take a regular linear model, with two categorical 2 level variables A and B who are ...
1
vote
0answers
51 views

Error in adding interaction in Cox model?

I'm doing a survival analysis and after plotting the Schoenfeld residuals and test the significance of the correlation of residuals with time, I've decided to incorporate a interaction in the model. ...
1
vote
0answers
46 views

Is it ok to transform a logarithm variable to z score

I have a variable that has 57 kurtosis, so I decided to transform it to log. However, I have multicolleanirity problem due to interacting this variable and others with another variable so I am using z ...
1
vote
1answer
80 views

Interaction in stepwise regression analysis

I did a stepwise regrssion analysis to predict energy expenditure using the variables, height, weight, age, gender and energy intake. The final model contains the variables gender and weight. Now does ...
1
vote
1answer
26 views

How to interpret constant with different dummy interaction terms?

I would like to analyse the impact of Fund Size on Mutual Fund Performance by using quintiles (based on fund size). My approach is to look at the effect within each quintile to conclude uniformity of ...
5
votes
2answers
39 views

Have population, use inferential statistics? Also, non-normal dependent variable, what to do?

Background: We are looking at parental leave in Iceland. We are particularly interested in whether the economic crisis and the resulting changes in parental leave legislation affected the time taken ...
0
votes
0answers
12 views

How to analyze a variable measured on a Likert scale and its interaction with another variable? [duplicate]

I have to analyze this variable which consists of scores given to 3 items (1-9 scale). This "Likert scale" measures "brand commitment" if thats important. 1) Firstly, should I compute 1 new variable ...
1
vote
1answer
58 views

What is the meaning of $A(B^2)$ interaction in a 3 level factorial with 2 factors $A$ and $B$, when the factors are qualitative?

I understand that when the factor is quantitative the $AB$ interaction can have a linear component and a quadratic component and so $AB^2$ makes sense there. But when we have qualitative elements how ...
0
votes
1answer
54 views

Multicollinearity with Interaction (high VIF)

When I check the VIF of my independent variables with the dependent variable, it looks normal and less than 5 but when I add the interaction variables, the VIF increase to 48 for some variables. I ...
0
votes
0answers
13 views

Cross level modeling in R, different levels of predictor, moderator and outcome variable

In the research that I am carrying out I have a moderation in which predictor, moderator and outcome variable are on the different levels: predictor and moderator on within level (the data were ...
2
votes
1answer
24 views

How to deal with non-normal heterocedastic data from a factorial experiment?

I ran an experiment with two factors each with two levels, 5 replicates each combination and one response variable. My data are non-normal and heterocedastic. Transformations didn't help. I ran a ...
3
votes
2answers
75 views

Removing attributes with few observations in R

I have roughly 15 variables / attributes characterizing 6k customers in my data set. As they are categorical I have transformed them into 1 attribute for each possible value (1-out-of-K coding). An ...
0
votes
1answer
61 views

Interaction in logistic models with R. Using * operator or create an interaction variable?

I want to test the presence of an interaction term in a logistic regression with glm(). The formula is: ...
0
votes
0answers
14 views

Three-way interaction in multilevel model

I am doing a multilevel Analysis in which I test whether the interaction between two Level 1-Predictors (IV1 and IV2) is moderated by a Level 2 predictor (IV3). The Level 2 predictor is a dichotomous ...
1
vote
1answer
40 views

Insignificant interaction makes variable of interest significant

I am having some strange results in a regression I am trying to run and I hope someone can help me to interpret them. Basically, first I regressed my dependent variable on a set of regressors which ...
3
votes
2answers
96 views

Logistic regression assumptions for a model with many binary independent variables

I am working on developing a logistic regression model that uses qualitative variables only ($n=990$). My remit is to define the equation that can identify the most relevant characteristics of a ...
0
votes
0answers
23 views

Multiple two-way interactions in simple slope analysis

Currently, I am working on a multiple regression model that includes a total of 9 variables: Two education dummy code variables (categorical) as a control, one target independent variable ...