Questions tagged [effects]
An R package for calculating graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors
80
questions
0
votes
0
answers
11
views
Effects package for plotting mixed models - what does it do?
I am trying to plot fixed effects of X1 and X2 from my lmer model, and I'm having trouble understanding the theory behind it:
...
- 121
2
votes
2
answers
77
views
Difference between Probability and Effects in Logit Models
when I run a logistic model I get log odds that I can easily convert to probabilities. What I don't understand is how can I use percentages instead?
Here's the code:
...
- 21
0
votes
1
answer
30
views
Serial mediation with 3 mediators and 2 predictors [lavaan]
I have constructed a structural equation model in R using lavaan, with 2 exogenous predictor variables, 3 mediators, and 1 endogenous response variable:
I tried to label it as conventionally as ...
- 3
1
vote
0
answers
32
views
covariance terms for random effects model
I have a random effects model with two groups.
$$
y_i = \alpha_{j[i]} + \gamma_{k[i]}+\epsilon_i
$$
Where $j[i]$ and $k[i]$ denotes the group memberships for individual $i$.
In R, I can estimate $\...
- 111
0
votes
0
answers
31
views
Extrapolate 95% CI for unit decrease and for percentage decrease from lmer outputs
I am testing the association between percentage of impervious surface areas (ISA) and number of eggs per breeding event. This is my model structure:
...
0
votes
1
answer
47
views
What kind of tests should I run for my master's thesis?
I am analyzing the effect of covid rates and covid lockdown levels on murder and suicide rates for the 50 most populous counties in the U.S. I am not sure what to do to analyze the question in ...
- 1
0
votes
0
answers
29
views
Regression for multiple point in time, ONE entity
I have multiple country-specific independent variables over time (annually). That is, each independent variable is measured one time for each year.
I am not sure what type of regression model to apply,...
- 15
0
votes
0
answers
24
views
linear mixed model: 2 fixed effects in a crossed(?) design? lmer
We have a continuous variable intensity as a dependent variable.
Three categorical variables: material(A,B,C,D), group(1,2,3,4,5,6,...), patient_id.
patient_id is supposed to be a random effect.
We ...
0
votes
2
answers
30
views
linear mixed effect model cross validated
Hi if I have lots of response variables that I want to use in a linear mixed effect model, do I have to run those separately by each response variable or is there a different model I should be using?
2
votes
0
answers
390
views
A recipe for removing confounding variable effect
I read a paper and it says "we regressed out the effect of a variable via linear regression".
Can someone provide to recipe to remove an effect of both numerical and categorical variables?
...
- 356
0
votes
1
answer
1k
views
Calculate total, direct and indirect effects in SEM with Lavaan package R
I wanted to ask if anyone knows how to obtain in a table the decomposition of the effect of the variables of a SEM model. I have made the model with the sem function of the lavaan package, but I don't ...
5
votes
2
answers
1k
views
Interpreting interaction effects for categorical reference group in regression
I am running a regression model in R including the following variables:
Intent = continuous DV
Attitude = continuous IV
Story = categorical
IV in 4 levels: Consumer, Heritage, Vision and Product
...
- 51
1
vote
1
answer
367
views
Making binary prediction with GPBoost (or MERF)
My question is regarding this post from 1.5 years ago: Modelling clustered data using boosted regression trees
My label is a binary variable (yes/no). Is it possible to use GPBoost / MERF in order to ...
- 23
0
votes
0
answers
6
views
Main effects switch direction when interaction terms are implemented? [duplicate]
I've got a conventional OLS-regression with some nested models, first specifying main effects.
In the first model, I get a positive b-coefficient on my main effect. However, when I add an interaction ...
1
vote
0
answers
200
views
How is that possible that SAS and R can test for main and interaction effects for the GEE if it has no likelihood?
I was taught, that GEE, being not likelihood based, has no way to compare models. That we cannot assess the main and interaction effects the way we do with ordinary GLM, OLS, GLS, mixed models and so ...
- 91
1
vote
1
answer
210
views
Interpretion natural spline function ov IV in ordinal regression
I know that this question was already posed several times but I am not sure If I really got the interpretation for spline functions right.
I have an ordered model that is regressed on an index ranging ...
- 19
0
votes
0
answers
312
views
Why are predictions from beta regression and linear regression identical?
I'm utilizing a beta regression to predict the relationship between x and y, since y is a proportion variable confined within the interval [0,1] but has no values of either 0 or 1.
Outcomes on y only ...
0
votes
1
answer
71
views
Fixed effects in OLS
I am new to R, so I apologize in advance if the question may sound inappropriate.
I have a sample of 484 M&A deals (each deal is unique) and I ran a regression ...
MS97
0
votes
1
answer
69
views
Why is allEffects from effects package excluding a level/value from my my model?
I posted this on stackoverflow but it was suggested I post it here.
I am running an ordinal logistic regression on data that is roughly like this:
...
- 11
2
votes
0
answers
163
views
Unscaling predictor variables from a GLMM using predictorEffect()
I'm running GLMMS on scaled and centered data, which has worked well. However, now I am trying to visualize my data using the Effects package and I cannot find a way to backscale my predictor ...
- 91
4
votes
1
answer
93
views
Random effects and random errors
Let's say that we have this simple model:
\begin{equation} \label{eq:gls_reg}
y_{ij} = x_{ij}\cdot\beta +{u_{i}} + \varepsilon_{ij} ,
\end{equation}
\begin{equation*}
u_i\sim N\left( {0,\sigma_{u} ^2 ...
- 315
1
vote
0
answers
225
views
Multinomial Regression Model with random effects
I have unordered categorical data (behavior with subclasses) as response variable with more than 2 classes. My independent variables are continuous and categorical. I would like to run a multinominal ...
- 11
1
vote
0
answers
65
views
Effects package equivalent for LCMM [closed]
The effects package helps in the analysis of predictor effects from LMER models. Is there an equivalent for LCMM models? (i.e. understand predictor effects of class ...
- 63
0
votes
2
answers
3k
views
Differences in differences, fixed effects and standard errors
I have a question on estimating a difference in differences model using Stata. As I understand this, also from other questions, when there are no covariates, estimating the diff in diff using a ...
- 3
1
vote
1
answer
549
views
Package 'effects': predictorEffects function customising the y axis with overprinting [closed]
I have this predictorEffects finction, which results in overprinting of the labels on the y-axis, however, I have tried many things and they don't seem to be working. Here's the code I used:
...
- 21
0
votes
2
answers
41
views
Which formula fits better for this Linear Mixed-Effects Model?
I am currently analyzing a dataset that contains a list of flight simulator tests performed by different pilots. I want to analyze if a certain flight parameter (i.e. amount of input errors during ...
3
votes
1
answer
88
views
Mixed effects logistic regression formula with one random effect
In our thesis, we have used a mixed-effects logistic regression and now we want to present it as a formula, however, we are not sure how to present a mixed-effects logistic regression?
Our binary ...
1
vote
1
answer
824
views
R Testing Simple Effects Using testInteractions() Not working for Mixed ANOVA
I am trying to use the R phia package to test Simple Effects for a mixed ANOVA.
It works fine if there is no term for the within subject factor:
...
- 69
1
vote
0
answers
128
views
Is it possible to have ANOVA-type assesment of main efects in quantile mixed linear regression?
As in the title. I would like to assess the main effects by applying a joint test to the quantile regression. In R it's done by lqmm(), but neither anova, Anova, emmeans, or multcomp support it. I ...
- 45
1
vote
0
answers
66
views
Relationship between Conditional R squared and random effect variance?
I have run a simple lmer with one fixed effect (day) and 3 random effects (athlete, infusion and sport). Model below.
...
1
vote
0
answers
236
views
Interpretation of effects plot in latent class regression
I'm fitting a latent class model with covariates using poLCA in R. It seems to work fine, but I have some trouble understanding ...
- 111
2
votes
0
answers
1k
views
How can I report the results of a two-way ANOVA on a 3x4 factorial experiment?
I'm trying to generate some sort of table that shows statistical differences between my X1 and X2 variables, using a 2-way ANOVA test.
I have a fertilizer experiment where I'm looking at the effect ...
- 23
1
vote
0
answers
52
views
Integrating the confint command to my default logistic regression output [closed]
I would like to hear of possible solutions to the following problem. I want to integrate the confintcommand with the general logistic regression ...
- 11
3
votes
1
answer
547
views
What do I do when my model prediction exceeds the limit of 100%?
I have plotted the effects of a model glm( A ~ B, family=poisson, data=data) both with the sjplot R package and with the ...
- 41
2
votes
0
answers
546
views
Am I getting the definition of partial residual plot right?
I am trying to make a partial residual plot of one quadratic predictor in GLMM (glmer in R). I tried to do it manually, from how I understood the definition of ...
- 6,133
0
votes
1
answer
180
views
Interpret contradicting output of lmer model with categorical interaction in R
I am struggling to interpret my output in R. It does not make sense to me.
I first regressed participants' ratings (= value) on manipulations (...
- 1
2
votes
1
answer
2k
views
Computation and interpretation of marginal effects in a GLMM
I am currently working on a GLMM model which uses a Poisson distribution and need to compute and interpret marginal effects from this model.
The model outcome consists of a count (COUNT) collected ...
- 19.7k
3
votes
1
answer
324
views
How to interpret effects of predictors with large confidence intervals in GLMM?
(This question is somehow related to my previous one)
My aim is to find out about which effect several predictors have on my response variable, I am interested in the direction and magnitude of the ...
user45065
7
votes
1
answer
3k
views
Calculating confidence intervals of marginal means in linear mixed models
I'm using different R packages (effects, ggeffects, emmeans, ...
- 103
1
vote
0
answers
724
views
How to plot predicted values for fixed and/or interaction effects? (different results of predict() function and effect() (from effects package))
I've applied a linear mixed model to my data:
...
1
vote
1
answer
7k
views
Differences between Simple Effects, Pairwise Comparisons, and planned/post hoc comparisons?
I am very confused as to the differences between simple effects, pairwise comparisons, and planned/post hoc comparisons. From what I understand, after running an ANOVA, you would use one of these to ...
- 197
1
vote
1
answer
84
views
Why does it not make sense to compute effects for lower-level interactions in the absence of higher-order interactions?
The documentation of effects package says
"If asked, the effect function will compute effects for terms that
have higher-order relatives in the model, ...
- 1,295
1
vote
1
answer
32
views
Macroeconomic effects. Effects of a time serie on another
I have a monthly time series for the provision in a financial institution. Take real data until december 2017 and predict it with a Bat model until June 2018 using R and I have an error of 0.12%. This ...
2
votes
0
answers
2k
views
random intercept, random slope plus intercept, no random slope alone? [closed]
I measured running speed of 70 individual lizards. The lizards were siblings born of 7 mothers, 10 offspring each. The Lizards ran at 3 different temperatures, A, B, and C, where A < B < C, and ...
1
vote
1
answer
236
views
Different standard errors under Mac and PC in "effects" R package [closed]
I ran a model with lme4::lmer() on my Mac, then predicted values and standard errors of the interaction with effects::Effect(). Then I tested the same code under Windows. Everything was identical ...
- 61
2
votes
1
answer
2k
views
How to simulate R data for a random effects model set-up?
Suppose we have $m$ schools chosen randomly from among thousands in a large country. Suppose also that $n$ students of the same age are chosen at each school. Let $Y_{ij}$ be the score of the $j$th ...
- 3,892
1
vote
0
answers
2k
views
Effect plot with lme model
I am building a mixed-effects model with nlme package.
The output of the model is as seen below, and includes the time variable, namely day and one categorical variable for treatment with 4 ...
- 325
2
votes
0
answers
4k
views
Conditional effects in a multiple regression model
I was told that if I have a regression model $Y=b_0 + b_1X + b_2Z + b_3(X *Z)$, coefficients $b_1$ and $b_2$ have conditional effects. What does this mean exactly? How do I know when I have main ...
- 129
1
vote
0
answers
483
views
Panel data ID and time level fixed effects with propensity score matching possible?
I have about 15000 observations on long term care centers per year, for a period of 10 years. My independent variable is binary and the outcome variable is continuous. I have performed ID and year ...
- 11
1
vote
0
answers
195
views
Comparison of coefficients in fixed effects vs. non fixed-effects regressions
I recently came across a paper that runs pairs of regressions, in which one regression includes unit fixed effects and the other regression does not include unit fixed effects. The paper then ...
- 11