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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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Hurdle Poisson Post Estimation - Partial Effects [closed]

I'd like to calculate partial effects after fitting a hurdle poisson model. ...
Terrie's user avatar
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Why am I getting Negative Marginal Effects for Coefficients that are Positive?

I've run a hurdle Poisson model in R on the pscl package and used the marginaleffects package for the marginals and I'm getting ...
Terrie's user avatar
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Extracting (true) marginal effects from nonlinear mixed effects models [closed]

I am modelling a binary data set using what I believe should be termed a nonlinear mixed effects model logit(pi) = mu + beta*x + U_1 + U_2 + U_3 where ...
fair21comic's user avatar
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Interpretation of average marginal effect logistic regression model [duplicate]

I am currently writing a master thesis on the relationship between the unemployment rate (measured in percentage points) and first birth hazards (i.e. the probability of having a first child) using ...
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Calculating contrasts of marginal effects with marginaleffects for brms model

I have fitted a logistic model with brms and want to calculate the average marginal effects (AMEs). ...
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Estimated marginal trends after regression of isometric log ratio transformed compositional data

I have longitudinal compositional data with four base response variables. I would like to compare the slopes of groups across time, but not for the ilr-transformed composition. I wish to compare the ...
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Estimating Average Marginal Effects with Ordered Logistic Regression

I am estimating a series of ordered logistic regression models for a 4-level ordered dependent variable and I am trying to estimate the average marginal effect (using {marginaleffects}) of moving from ...
Brian Lookabaugh's user avatar
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What are average comparisons in the `marginaleffects` package?

I am confused about what the avg_comparison function does in the marginaleffects package. ...
Carol Eisen's user avatar
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Calculation Interaction Effects, Plot of Fixed Effects Model with interaction terms

I'm working with panel data using the plm package in R to estimate a fixed effects model that includes interaction terms. I'm currently able to get my model results using plm and display them with ...
Kati's user avatar
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Is the effect in a Cox proportional hazard collapsible if the covariates are normally distributed and the baseline hazard is constant?

Since the Cox PH model is a non-linear model, we would expect the effect to be non-collapsible. i.e., the marginal and conditional effects differ. I did some calculation for a setting where the ...
hehe's user avatar
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Is the link for a marginal trend in a logistic model the logit?

Exactly as in the title. If I estimate marginal trends for a logistic model, are these expressed as a log odds ratio? How does one express that in a way that makes intuitive sense? Change in odds ...
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Marginal Treatment Effects using MTEFE - postestimation discrepancy

I am currently calculating Marginal Treatment Effects for an outcome Y (earnings) and a treatment D (joining sector 1 vs sector 0), using the MTEFE package from Stata. I use a separate approach with a ...
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estimating effect with marginaleffect package

I want to estimate ATE. first of all I used MatchIt package for full matching for propensity score and then I used logistic regression with all of variable in propensity score model after that I used ...
Mahboobeh Taherizadeh's user avatar
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How to estimate interpretable treatment effects using a marginal structural model?

Say that I estimate a marginal structural model with weights obtained by inverse probability weighting. Imagine that my model looks something like: $Y_t = X_t + X_{t-1}$ again, with observations ...
Brian Lookabaugh's user avatar
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Sensitivity Analysis for Raw Model Output or Model Predictions?

For a variety of reasons, many researchers have suggested that, for attempting to make causal inferences with non-linear statistical models, one should generally avoid endowing a causal interpretation ...
Brian Lookabaugh's user avatar
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Average marginal effects using the linear probability model

I read that when calculating average marginal effects using the linear probability model, you should always use heteroscedasticity robust standard errors. Why is that?
Marlon Brando's user avatar
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Signs for marginal effects and regression coefficients are inconsistent for beta regression

I have conducted a zero-one inflated beta (ZOIB) regression using a logit link function for explaining tenure incidence in colleges and universities. Tenure incidence is a proportion in the interval [...
Jeffrey Royer's user avatar
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Marginal means (or "adjusted predictions") with categorical predictors

Goal My analysis goal is to estimate the expected value of the outcome variable under three different conditions defined by a set of 3 categorical explanatory variables with two levels each. However, ...
user3084100's user avatar
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Interpreation - Log tranformed dependant variable and model with square term of predictor (inverted U)

I am estimating a model of the following form: log(y) = b1 x + b2 x^2 + b3 log(z1) + b4 z2 This is an econometric model with a focus on the impact of ...
user917983's user avatar
2 votes
1 answer
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Implications of very low but statistically significant average marginal effects

I built a multivariate logistic regression model, which is largely a replication of a published paper (I just some different data). My regression table (with the coefficient reported as log odds) ...
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Converting PanelMatch Estimates to Marginal Effects in Non-Linear Outcome Models

I am interested in using the {PanelMatch} package for a project that I am working on where the conventional matching/weighting framework is expanded to account for the complexities of the panel data ...
Brian Lookabaugh's user avatar
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Does marginal effects change depending on the size and heterogeneity of the population?

I am trying to predict the probability of receiving treatment using a logit regression. I have two regressions with the same explanatory variables: Regression 1: I predict the probability of ...
Stata_user's user avatar
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2 answers
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What to plot when main effect significant but interaction insignificant?

This may be a silly question but: Given a regression model that includes both main effects and an interaction term (Score of participants predicted by their attitude and motivation): ...
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Can I calculate the change of the bicycle's modal share from marginal effects obtained by logistic regression?

I want/need to analyse the influence of certain parameters on the share of cycling in the total number of trips. What I have is a database of more than 960,000 trips within Germany in 2017, containing:...
FesterShinetop's user avatar
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1 answer
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Compute standard error in the group difference in marginal effect [closed]

I am running a fixest effects regression of the following model. $$Y_{it} = \beta_0 + X_{it}\beta_1 + T_{1it}\beta_2 +T_{2it}\beta_3 + X_{it}T_{1it}\beta_4 + X_{it}T_{2it}\beta_5 + \alpha_{it} + \...
Michael Lachanski's user avatar
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How to interpret margins in percentage points when the independent variable is a percentage?

I have 2 research questions, dependent variable of 1st question is a binary variable and I use logit regression to estimate it on STATA. The dependent variable of second research question is in ...
LKho's user avatar
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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 ...
Marble's user avatar
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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, ...
Isabella 's user avatar
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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 ...
Maximilian's user avatar
2 votes
1 answer
388 views

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 ...
Giant Steps's user avatar
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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 ...
ECON10105's user avatar
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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.  ...
Jakob Abekhon's user avatar
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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)...
Confused_not_a_statistician's user avatar
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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 ...
Brian Lookabaugh's user avatar
2 votes
1 answer
103 views

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 ...
Brian Lookabaugh's user avatar
2 votes
1 answer
167 views

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 ...
arielhasidim's user avatar
1 vote
1 answer
162 views

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 ...
Yang Cao's user avatar
1 vote
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291 views

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: <...
mto23's user avatar
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1 vote
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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 ...
Spotty Giraffe's user avatar
1 vote
1 answer
502 views

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: ...
bee guy's user avatar
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4 votes
2 answers
573 views

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 ...
user332276's user avatar
3 votes
1 answer
629 views

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 ...
Brian Lookabaugh's user avatar
1 vote
1 answer
40 views

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 ...
PhelsumaFL's user avatar
0 votes
2 answers
110 views

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: ...
Enrico Bergamini's user avatar
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1 answer
1k views

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: ...
Telis's user avatar
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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 ...
cgmil's user avatar
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3 votes
1 answer
74 views

(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 ...
Hillary's user avatar
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2 votes
1 answer
37 views

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}...
generic_user's user avatar
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3 votes
0 answers
188 views

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 $\Sigma$ ...
Demetri Pananos's user avatar
2 votes
0 answers
102 views

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 ...
Demetri Pananos's user avatar

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