Tagged Questions
1
vote
0answers
25 views
R module for creating plots of prototypical individuals from fitted models?
In order to help interpret fitted models — especially those with interaction terms and non-linear components — I've found it useful to plot predicted values of a dependent variables for what we might ...
2
votes
0answers
33 views
Ratios in Regression, aka Questions on Kronmal
Recently, randomly browsing questions triggered a memory of on off-hand comment from one of my professors a few years back warning about the usage of ratios in regression models. So I started reading ...
0
votes
1answer
22 views
How do I derive slope and intercept for each group in regression model with a categorical and 2 continuous predictor variables?
$IQ = b_0 + b_1Group + b_2Age + b_3Income + b4\times Group\times Age$
Group is dummy coded ($0,1$)
I assume that the interaction of Group x Age tests the group difference in the slope of the IQ vs. ...
2
votes
1answer
42 views
interaction terms in separate models?
I'm doing a multilevel mixed model with three cross-level interactions in LMER. Do all three interactions necessarily need to be included in the same model or can I evaluate them in three separate ...
2
votes
0answers
33 views
Few main variables in the best model still show multicollineairty. Should I remove them despite their importance?
I have a binary logistic regression with 5 IVs and all of their 2-way interactions. I have reduced/removed multicollinearity between main variables and their interactions by centering the main ...
1
vote
1answer
38 views
After centering, interactions' effects got reversed. It was not fixed by reversing the dependent variable. What should I do?
In a binary logistic regression, I centered all the independent variables (binaries, continuous, dependent, independent, all [I have 5 IVs: three binary and two ordinal]). Multicollineariy was ...
1
vote
1answer
44 views
How to choose interactions to test when there are many predictors?
If I have many covariates $X_1, X_2, ... ,X_{15}$ in a linear regression model, how do I determine which two-way interactions to include? Obviously there would be too many potential models to do a ...
0
votes
2answers
116 views
Is there a simple rule for interpretation of Interactions (and their directions) in binary logistic regression? [duplicate]
I have a binary logistic regression with Y (a disease) and 5 independent variables (and some of their 2-sided interactions which did not cause multicollinearity). All of my single IVs significantly ...
0
votes
1answer
50 views
When is it valid to include interaction terms in a regression model? [duplicate]
I am using logistic regression to analyze some categorical data (binary response variable and categorical -- mostly binary -- predictor variables). For my model, I have something like ...
3
votes
1answer
152 views
Interpreting interaction terms in logit regression with categorical variables
I have data from a survey experiment in which respondents were randomly assigned to one of four groups:
...
0
votes
0answers
39 views
How to control intercept of only one IV-DV relationship in multiple linear regression
If I have a relationship between three variables (survivorship (outcome), time and dose (continuous) with interaction) how can I control the intercept for time but not dose in MLR? The reasoning for ...
2
votes
1answer
162 views
Moderation in repeated-measures design?
Context: Both dependent $(Y_1,~Y_2,~Y_3)$ and independent $(X_1,~X_2,~X_3)$ variables were measured repeatedly at three time points, $\text{Time}_1$, $\text{Time}_2$, and $\text{Time}_3$. Moderator ...
0
votes
2answers
84 views
Should I keep the interaction term?
I am doing research on mortality. I am running cox regression and I am adjusting for 40 variables which are proven in the literature to be related with mortality. My main exposure is X. In my final ...
2
votes
1answer
144 views
Test whether simple slopes are different from zero in 3-way interaction in multiple regression
I'm trying to test whether 4 different slopes from a 3-way interaction in multiple regression are significantly different from zero. The four lines are plotted at 2 levels of each of the 2 moderators ...
2
votes
2answers
139 views
In my logistic regression model one of the independent variables is redundant with the interaction term. How should I deal with it?
In my logistic regression is the dependent variable a dummy variable and I also have two independent variables. One of those is a dummy variable and the other is a metric variable. I also suppose an ...
0
votes
0answers
18 views
Change in S.E of one variable when interaction term added to Binary Logistic Regression [duplicate]
I have 6 predictor variables and have carried out a binary logistical regression. I found that most variables significantly predicted the DV. However, I then wanted to find out if there was a ...
1
vote
2answers
94 views
Inconsistent beta values in regression analysis due to change in categorical coding
I have three terms in my regression models:
gender (categorical data),
centeredmeanB (quantitative data)
and the interaction term gender * centeredmeanB.
I noticed than the way I coded gender ...
2
votes
0answers
59 views
Swapping X and Y in a regression that contains a grouping predictor?
Suppose I'm doing a linear regression and I want to investigate how the association between a predictor X and a response Y changes according to levels of a 2-level factor G. The model would look like ...
1
vote
1answer
176 views
Interpreting this regression coefficient
Quick background:
I am working on a political science project that involves analyzing the impact of different variables on the extent to which a candidate mentions other users when he or she tweets.
...
0
votes
1answer
101 views
Problem with interaction variable for logit regression
I have a short question regarding interaction variables:
In a logit regression with 2 independent dichotomous variables (A and B), both variables are significant. By including the interaction (AxB) ...
0
votes
0answers
148 views
Regression with multiple endogenous regressors instrumental variables and interaction terms
I am running an two regressions one with a binary dependent variable (y) and one categorical.
My data is cross sectional so to deal with issues around causality, endogeneity (reverse causality) and ...
0
votes
1answer
52 views
Constructing a measure versus using an interaction
My dataset is sports data and the outcome variable is wins in a season and I am trying to see the affect of the characteristics of the players on the team on this outcome. My question is, is it easier ...
2
votes
3answers
86 views
What to do when the predictors do not accord with common sense/literature, but the model is fine/best according to log likelihood and LRT?
I would try to clarify the problem and then ask the questions.
The problem (variable names are masked due to confidentiality):
I ran a binary logistic regression, in which there were 5 ...
2
votes
1answer
109 views
Should I include an interaction term for a covariate if I expect it to be correlated with one or more of the variables?
I'm fitting a linear model where the response variable is a measure of physical performance-- running speed for example-- and the predictor variables are sex and drug treatment, with an interaction ...
2
votes
2answers
143 views
Interpreting main effect coefficient in different models
My interest lies in finding the "right" correlation between a continuous IV ($x$) and a continuous DV ($y$).
At first I ran a simple linear regression:
$$
y=a+b_1 x
$$
However, lots of other factors ...
2
votes
0answers
231 views
Dealing with multicollinearity when removing a highly collinear predictor reduces significance
In my experience with dealing with multicollinearity, often removing one collinear variable from the model results in the other collinear variable(s) becoming significant (assuming that all the ...
3
votes
2answers
149 views
Beta coefficients from stratified analysis when there are covariates?
Suppose I have a regression model shown below
Model 1:
$$
Y = \beta_0^\ + \beta_1SEX\ + \beta_2ALCOHOL\ + \beta_3SEX*ALCOHOL\
$$
The predictors I am interested in are SEX (binary: 0 female, 1 male) ...
1
vote
1answer
599 views
Interpreting multiple regression coefficients with 2 continuous variables interacting and 2 categorical variables interacting
I find it challenging to interpet interaction effects in OLS multiple regression where the interactions are between two categorical variables and between two continuous variables.
Say for instance ...
2
votes
1answer
126 views
What are the statistical assumptions, prior to running hierarchical regression to test interaction effects?
What are the assumptions that need to be met when using hierarchical regression, and subsequently simple slopes analysis to test and probe interaction effects and how can I test for them in SPSS?
I ...
0
votes
1answer
46 views
Testing Independent variables impact during different decades
I am trying to test the impact that independent variables, Growth, Inflation, and Z (good economy for several quarters), have on the presidential vote received by the incumbent party.
My alternative ...
1
vote
0answers
51 views
Can the Johnson-Neyman moderation interaction technique be used with a categorical moderator?
Can the Johnson-Neyman moderation interaction technique be used with a categorical moderator (3 categories)? 60%, 80% and 100%.
I am guessing that it could approximate the interaction effect at ...
0
votes
1answer
504 views
Interact categorical variables in GLM in R
I am trying to predict child nutrition (binary) using a set of variables. The two that I want to interact are maternal education (none, primary, middle, HS) and wealth quintile (1,2,3,4,5). Thus far ...
2
votes
1answer
216 views
OLS Regression: Interaction effect is significant by itself, not when included in full model--ok to report?
I have a sample with 400 cases. When I run my full model, which includes 13 predictors, the interaction term is non-significant. However, when I run a model only including the three variables involved ...
2
votes
2answers
472 views
How do I interpret the results from a basic interaction plot from the R effects package?
Using the method in this post, I have made a plot to visualize the interaction between two predictor variables using the effects package in r, but I'm not really sure what I am looking at.
Tide ...
0
votes
0answers
72 views
Comparing a single variable regression model to a model with interactions?
If I have a linear regression of the form:
$$y \sim 1+\beta_1x_1 + \beta_2x_1x_2,$$
where $x_2$ is a Boolean variable depending on another variable $x_{2cont}$, a positive variable:
$$x_2 = ...
0
votes
0answers
41 views
Response variables with interaction effects
Does anyone know of a statistical approach/method that lets you model linear regressions between 3-5 explanatory variables that are categorical or continuous and 3 continuous response variables that ...
1
vote
2answers
200 views
Interactions make terms significant in regression when they should not be
I am writing code to prepare for running a logistic regression on real data. I have sample data for all my IVs but not for the outcome variable. There are many strong dependencies among the IVs but I ...
0
votes
1answer
179 views
How do I interpret the results of a regression which involves interaction terms?
If I have a linear regression of the form:
$$y \sim 1+\beta_1x_1 + \beta_2x_1x_2,$$
where $x_2$ is a Boolean variable depending on another variable $x_{2cont}$, a positive variable:
$$x_2 = ...
0
votes
2answers
170 views
How to deal with differences in subgroup analysis but no significant interaction?
In case of a multiple linear regression I found a significant effect in a subgroup analysis (sample restricted to males). In the subgroup analysis restricted to females there is no effect. However in ...
1
vote
0answers
117 views
Correlation and coefficients in ols
I am trying to fit a simple linear model with OLS. I have say 4 terms and the number of data points is >>4, so no explicit overfitting.
1) My terms or my independent varibales do have a strong ...
0
votes
0answers
21 views
which interactions to include? [duplicate]
Possible Duplicate:
What terms should I include in a linear regression model?
In case of running a logistic regression, with multiple variables which result in strongly disagree to strongly ...
2
votes
1answer
47 views
Small Sample, Low Baseline in DV, Interaction anyway?
Please assume that I have two metric independent variables (e.g., two blood parameters), and a dependent variable (e.g., a disease). On the DV, 0 represents the absence from the disease, 1 represents ...
2
votes
2answers
204 views
Interpretation for simple slope analysis for curvilinear regression with interaction effects
When regressing income ($Y$) on age ($X$) moderated by gender ($Z$), I not only find significant effects for age ($X$), age squared ($X^2$), gender ($Z$), the interaction of age and gender ($XZ$), and ...
2
votes
1answer
621 views
Calculate standard errors: interaction between 2 factors, one of which has 3 levels in a regression model
I have the following model:
$y \sim b_0 + b_1x_1 + b_2x_2 + b_3x_1x_2$.
$x_1$ is a factor with 2 levels (0 and 1), and $x_2$ is a factor with 3 levels.
I know that to calculate standard errors for ...
1
vote
1answer
183 views
What's the appropriate way to calculate an effect size when there is an interaction?
I have a regression model with two significant main effects and a significant interaction. I'd like to calculate an effect size for one of the main effects.
I'm using the package ...
2
votes
1answer
229 views
Measuring the moderating effect in my analysis?
I'm trying to analyze if the volume and sentiment (valence) of tweets has an effect on the sales of a product (in my case movies). The DV is sales with IV NumberOfTweets, Valence, DaysSinceRelease.
...
3
votes
1answer
115 views
Include interaction regressors separately?
I was taught that if I include a regressor in an interaction, then I should include it separately, too. That is, if I regress $y$ on $x_1 \times x_2$, then I should also include $x_1$ and $x_2$ ...
2
votes
1answer
257 views
Can I use a difference score as my outcome variable (pre-post change) in a moderated multiple regression equation?
I am wanting to examine whether religiosity moderates intervention effects on stigmatized attitudes. Here are my variables:
X = group (1 = experimental; 0 = control)
Z = religiosity (14-item scale - ...
5
votes
1answer
437 views
How to calculate the interaction standard error of a linear regression model in R?
I have the following model and want to make a table with the interpretation of the interaction effects as suggested by Bambor and Clark in this paper. However, I have no idea on how to calculate the ...
1
vote
1answer
433 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 probing of ...
