Questions tagged [marginal-effect]
Marginal effects measure the change in the conditional mean of outcome $y$ when regressors change by one unit.
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How to interpret marginal effect for an ordinal probit model when the independent variables consist of factor scores?
I conducted an exploratory factor analysis on a 5-point Likert scale utilizing polychoric correlations, identifying and retaining 4 factors. Subsequently, I computed factor scores through the ...
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Hypothesis testing in moderation analysis after Propensity Score Matching
I would like to perform a moderation analysis after Propensity Score Matching with a binary outcome model. I estimate a logistic regression outcome model (following this vignette). I am wondering, ...
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Average Marginal Effect interpretation for probit Model
I'd like to have your feedback about the interpretation of the Average Marginal Effect (AME) for a probit model. Suppose we have the following model
\begin{equation}
P(y=1|x)= \Phi(\beta_0 + \beta_1 ...
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Marginal Effect for Poisson Model
I am using package marginaleffects for calculating the AME of an exposure variable on a count dependent variable. I am hence using Poisson (and Negative Binomial as robustness). The dependent variable ...
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Linear Model, Identification of Structural Parameter
I'm reviewing the foundations of linear regression using Wooldridge's Econometric Analysis of Cross Section and Panel Data and Cameron and Trivedi's Microeconometrics : Methods and Applications. The ...
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Determining maximum/minimum values at which marginal effect is significant
I am running the following regression:
reg stdnutrition stdlogdeficit stdinfrastructure c.stdlogdeficit#c.stdinfrastructure
where all variables are standardised. ...
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Do I want the linear regressions fixed, random or marginal effects as the "adjusted values"?
my apologies ahead of time if it's not as clear as I would like it to be. I'm using a linear mixed effect (nlme package) to determine the association between a modularity score (on a range of -1 to 1)...
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Interpreting a coefficient for a matched/weighted data set for non-linear outcomes
Prior research has demonstrated that the interpretation of a regression coefficient no longer represents the marginal effect once non-linear term transformations (logs, interactions, etc.) are ...
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What are the comparative advantages and disadvantages of interpreting regression output using marginal effects vs. ratios?
In models with a discrete dependent variable and/or linear models with non-linear right-hand specifications (interactions, polynomials, etc.), interpreting the association between Y and BX becomes ...
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Bootstrap for nonlinear regression (quasibinomial GLM) using `marginaleffects::inferences` after matching
Background
Looking into the MatchIt articles made me realize that using Bootstrap with BCa is a better practice for assessing uncertainty estimation (since: "For nonlinear models (e.g., logistic ...
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How to do the post-hoc analysis for three predictors (two factor variables and one numeric variable)
I'm using a linear mixed effects model to analyze the reaction time of learners of English as a Second Language (ESL). I have two factor variables: grammaticality (grammatical v.s. ungrammatical) and ...
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GAM plots: partial effects, shifted y-axis, or predictions - which representations/interpretations are correct/accurate?
I have two GAMs fitted with a Gamma distribution, with the same model structure with a continuous response variable and one continuous covariate, two categorical covariates, and one random effect:
<...
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Interpretation of coefficients in fractional response (probit) model
I am learning about the estimation of fractional response models (those with a lower and upper bound, say 0 to 1), using Stata. I came across this example on the Stata page, which I'm copy-pasting ...
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Why do emtrends and summary(model) provide different coefficients for a linear effect?
Let's say we run a model with a three-way interaction that includes a quadratic term with its associated linear term:
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Can we estimate ATE (average treatment effect at the population level) using both marginal or conditional models?
If I understood correctly, in principle when we estimate an unconditional/unadjusted treatment effect, it means marginal effect and vice-versa. If so, I wonder if the average treatment effect (ATE) at ...
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Estimating and Interpreting the ATT with Regression Adjustment and Marginal Effects
I am beginning a project that will employ regression/covariate adjustment to estimate the average effect of treatment on the treated (ATT) and I realize that I have two questions concerning how one ...
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Holding covariates constant to plot MLR model on 2d scatterplot in R
I am currently working with a MLR model comprising 1 numeric/continuous predictor variable (x1), several nominal categorical variables (x2 ... xi), and an interaction term between the continuous ...
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Pairwise marginal effects at specific quintiles STATA-like in R's marginaleffects
I would like to estimate marginal effects of two different variables.
In STATA, I have a two-way fixed effects model of type:
...
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Predicting with GAM (mgcv) and categorical/factor covariate in R
I have some data for multiple users and I want to generate some marginal effects for each user using GAM modelling. If I do this exercise for just a single user (John) as:
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What is the name of a plot that looks at the effect of ony one variable in a regression model? [duplicate]
In short: what is the name of the type of plot below? These seem like standard plots, so I don't want to rename them by accident (I'm giving a presentation on this). The code itself does not matter ...
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(Marginal) least-squares estimate of an individual marker effect
I am reading the paper from Vilhjálmsson et al (2015), Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores, at the "Phenotype Model" section, they said:
Let Y be a N ...
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are the marginals of boosted trees consistent if we can assume unconfoundedness?
given outcome $y$ and data $X$ with data generating process $y = f(X)+\epsilon$ where $\epsilon$ independent of $X$ and gradient boosted trees as the algorithm approximating $f$, does $\partial \hat{y}...
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Computing the standard error of a marginal effect
I'm trying to grok how the standard errors for a marginal effect are computed.
I know that if $\eta_i = x^T\beta$, then the square of the standard error of $\eta_i$ is $x^T \Sigma x$, where $\Sigma$ ...
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Elasticities and their interpretations when dependent variable is on a percentage scale
I am trying to estimate in Stata the elasticity of my outcome variable y with respect to income in cross-sectional data.
y is censored at 0, and it is between 0 and almost one, which suggests the use ...
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Should the marginal effect of a model which includes interactions be the marginal effect of a model without interactions?
When companies run an AB test, stakeholders will often ask two questions:
i) What was the effect of the intervention, and
ii) Did the effect vary by strata (e.g. mobile vs. desktop)
Additionally, the ...
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Estimate marginal effect of poisson regression with individual fixed effects
As in the title, does anyone know how to estimate the marginal effect of a Poisson regression model with individual (multiplicative) fixed effects?
I've been struggling with this for a few days but ...
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Marginal effects in logistic regression and subgroup analysis
I am conducting a research project implementing exact matching to seek to isolate a marginal effect of a binary exposure variable on a binary outcome (via MatchIt in R). I am using logistic regression ...
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Average Marginal Effects interpretation problems [duplicate]
I am running a probit regression model to test my hypothesis. As one cannot deduce the magnitude of the effect of the independent variables on my dependent one, I have calculated the average marginal ...
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Modelling predictor as quadratic term lowers BIC but marginal effect plot shows linear distribution?
I am using a modified Hosmer Lemeshaw approach, culminating in all possible combinations model selection, to conduct multiple logistic regression that should distinguish between use (1) and available ...
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How to interpret coefficient and marginal effect in probit when $\beta$ is not identified
Say we have the latent variable $y_i^*=x_i\beta-\epsilon_i$ and $\epsilon_i \sim N(0, \sigma^2)$.
$y_i^*/\sigma=x_i\beta/\sigma-u_i$ where $u_i=\epsilon_i/\sigma \sim N(0, 1)$, and so can use Probit ...
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Stata's margins and R's marginal effects' comparisons
I was looking for an equivalent for Stata's command lincom in R. I tried the comparisons() function from marginaleffects package. However, I get different ...
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R: DALEX::model_profile vs PDP::partial
I am comparing partial dependence values on the churn data using DALEX and pdp packages in R.
The first bit is a caret model
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Regression on dataset whose features form a DAG
I have a dataset with the feature set X that comes in a hierarchical fashion. In other words, X forms a DAG that ends at the dependent variable y. The question is, is there a regression model that can ...
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svyglm and margins - variable not significant anymore as marginal effect
I run a logistic regression with survey weights (only raking) with svyglm.
Thereafter, I calculated marginal effects with package margins (svyglm.margins).
However, one variable that is significant in ...
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Translating marginal effects for layperson
In a setting with a binary outcome logistic model focusing on a binary treatment, how would you translate the average marginal effects to make it understandable to a layperson?
Let’s suppose the ...
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Average marginal means with marginaleffects
Is there a way to obtain averaged marginal predictions (predict then average like the margins command in Stata, not average then predict like emmeans in R) using the marginaleffects package?
I am ...
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Counterfactual marginal effects using the marginaleffects package
I'm experimenting with the marginaleffects package trying to calculate counterfactual marginal effects for the species variable. I'm just wondering if someone could help to show me what I'm doing ...
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Interpreting Average Marginal Effect in raw numbers
I fitted a logistic regression model with a binary exposure variable X, trying to understand the effect it has on a given outcome Y, which measures infection (yes/no). I calculated the odds ratio of ...
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Marginal effects of exposure variable in logistic regression with matched dataset
I have a question related to the estimation of effects of a certain binary exposure variable on a binary outcome via logistic regression after an exact matching procedure.
Originally, I followed ...
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Calculating trends with `emtrends` for three-way interaction model results in same slope estimates
I have fit a multilevel gam (mgcv) that includes a three-way interaction between a continuous variable (prev.rain) and two ...
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Average marginal effects for censored regression (Tobit) in R
I would like to calculate average marginal effects for a Tobit regression in R.
margEff.censReg can calculate marginal effects at the mean, but not average marginal ...
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How to compute marginal hazard rate from parametric survival models?
Suppose that the conditional hazard rate for subject $i$ follows a proportional hazard model in the form of:
$h_i(t)=h_0(t) exp(\beta_1X_{i1}+\beta_2X_{i2}+\beta_3X_{i3})$
$X_i$ are subject-specific ...
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Problems with emmeans if RE-adjustment and backtransformation from logit
In an experiment (4 sessions, 2 groups), subjects try to remember words.
We want to test
H1: the overall (marginal) main effect of group
H2: the specific interaction contrast of group and sesson1 _ 2
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Marginal Effect in a Gamma GLM with Quadratic Terms
I am building a gamma GLM regression model with a log link function. The model I fit is below:
I understand that I can calculate the marginal effect of x on log(y) by taking the derivative with ...
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Computing and simulating average marginal effect standard error using Delta Method with reproducible codes
I am trying to simulate calculating Average Marginal Effects on a basic linear regression with interaction on a binary variable and compare the empirical standard deviation I get from simulations and ...
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Why marginal effect and average marginal effects are the same for NB regression?
Using the margins() function from the margins R package, I fitted a negative binomial model (...
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Interpreting main effect with significant interaction term in continuous by continuous multiple regression
I have the classic multiple regression model $Z=β_0+β_1X+β_2Y+β_3XY$ that produces output with a significant interaction term. There's a lot of advice out there (and the formal principle of ...
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Can confidence intervals be found for the difference in marginal probabilities from two different logistic models of the same sample?
So, I have two multivariable logistic regressions for the same sample. They differ in one independent variable: Model A has a dummy variable for membership in the top 50% (compared to the bottom 50%) ...
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How to measure marginal effect of interdependent variables on a binary outcome?
My data represents observations on a possible sequences of events that may lead to a positive outcome (y).
Each event (A, B, C, D) is dependent on the previous event; for D to occur C must occur, for ...
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A specific marginal effect for logistic regression
For the logit estimate of the slope parameter,I would like to obtain the marginal effect of the regressor ndisease evaluated at $\Lambda (x'\beta)=\bar{y}$.
I obtain the logic estimation as follows:
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