Questions tagged [fixed-effects-model]

In biostatistics, fixed-effects may mean population-average effects. In econometrics, fixed-effects may represent the observed quantities in terms of explanatory variables that are treated as if the quantities were non-random.

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330
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9answers
622k views

What is the difference between fixed effect, random effect and mixed effect models?

In simple terms, how would you explain (perhaps with simple examples) the difference between fixed effect, random effect and mixed effect models?
180
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3answers
107k views

R's lmer cheat sheet

There's a lot of discussion going on on this forum about the proper way to specify various hierarchical models using lmer. I thought it would be great to have all ...
53
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2answers
47k views

What is a difference between random effects-, fixed effects- and marginal model?

I am trying to expand my knowledge of statistics. I come from a physical sciences background with a "recipe based" approach to statistical testing, where we say is it continuous, is it normally ...
16
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4answers
12k views

Fixed effect vs random effect when all possibilities are included in a mixed effects model

In a mixed effects model the recommendation is to use a fixed effect to estimate a parameter if all possible levels are included (e.g., both males and females). It is further recommended to use a ...
27
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6answers
6k views

What is the mathematical difference between random- and fixed-effects?

I have found a lot on the internet regarding the interpretation of random- and fixed-effects. However I could not get a source pinning down the following: What is the mathematical difference between ...
22
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2answers
36k views

REML or ML to compare two mixed effects models with differing fixed effects, but with the same random effect?

Background: Note: My data set and R code are included below text I wish to use AIC to compare two mixed effects models generated using the lme4 package in R. Each ...
15
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4answers
22k views

How to keep time invariant variables in a fixed effects model

I have data on a large Italian firm's employees over ten years and I would like to see how the gender gap in male-female earnings has changed over time. For this purpose I run pooled OLS: $$ y_{it} = ...
10
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3answers
21k views

Difference between fixed effects dummies and fixed effects estimator?

I started to read about panel regression models. However, I am a bit confused about the different model specifications in the fixed effects model: Does a fixed effects panel regression always mean ...
38
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4answers
50k views

Standard error clustering in R (either manually or in plm)

I am trying to understand standard error "clustering" and how to execute in R (it is trivial in Stata). In R I have been unsuccessful using either plm or writing my ...
12
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2answers
16k views

Difference-in-differences with individual level panel data

What is the correct way to specify a difference in difference model with individual level panel data? Here is the setup: Assume that I have individual-level panel data embedded in cities for multiple ...
14
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3answers
6k views

Concepts behind fixed/random effects models

Can someone help me to understand fixed/random effect models? You may either explain in your own way if you have digested these concepts or direct me to the resource (book, notes, website) with ...
8
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1answer
22k views

How do I interpret a “difference-in-differences” model with continuous treatment?

How do I interpret the ATE coefficient (i.e., the post-treatment indicator interacted with the continuous variable)? Does it make sense? Should I break it down into subgroups and just run a fixed ...
19
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2answers
3k views

Big disagreement in the slope estimate when groups are treated as random vs. fixed in a mixed model

I understand that we use random effects (or mixed effects) models when we believe that some model parameter(s) vary randomly across some grouping factor. I have a desire to fit a model where the ...
7
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3answers
6k views

panel data - within-group estimate - individual fixed effects retrieved

I am analyzing panel data. First, I have to decide whether to use a random or fixed effect estimator. The Hausman test suggests to use the fixed effect estimator (also named within group estimator). ...
8
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1answer
4k views

Interpreta​tion of main effect when interactio​n term is significan​t (ex. lme)

As an example I use Pinheiro, J. C. & Bates, D. M. 2000. Mixed-effects models in S and S-PLUS. Springer, New York. page 225. Rats whose body mass has been measured are fed by 3 different diets ...
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1answer
4k views

Hausman test: the larger the sample the more significant the Hausman test statistic?

Hausman test statistic formula: $$ H=(\beta_{f}-\beta_{r})' \left[\mathrm{Cov}(\beta_{f})-\mathrm{Cov}(\beta_{r})\right]^{-1}(\beta_{f}-\beta_{r} ) $$ where $\beta_{f}$ is the beta of fixed effects ...
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5answers
4k views

What is the upside of treating a factor as random in a mixed model?

I have a problem embracing the benefits of labeling a model factor as random for a few reasons. To me it appears like in almost all cases the optimal solution is to treat all of the factors as fixed. ...
13
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1answer
27k views

difference-in-differences with fixed effects

I have two questions related to having fixed effects in the DD model. I have a treatment that occurs at different times (e.g., 2001, 2005, etc.). I want to fit a DD model, so I standardize the ...
11
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2answers
17k views

Why do random effect models require the effects to be uncorrelated with the input variables, while fixed effect models allow correlation?

From Wikipedia There are two common assumptions made about the individual specific effect, the random effects assumption and the fixed effects assumption. The random effects assumption (made in a ...
10
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5answers
5k views

Bootstrapping hierarchical/multilevel data (resampling clusters)

I am producing a script for creating bootstrap samples from the cats dataset (from the -MASS- package). Following the Davidson ...
15
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4answers
585 views

How can I improve my analysis of the effects of reputation on voting?

Recently I had done some analysis of the effects of reputation on upvotes (see the blog-post), and subsequently I had a few questions about possibly more enlightening (or more appropriate) analysis ...
4
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1answer
1k views

Use of fixed effects and random effects

When can we do a linear regression without fixed or random effects and when do we need to use those in the regression analysis? I have tried studying a lot but have got only a vague idea. I would be ...
6
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1answer
14k views

Difference between fixed effects models in R (plm) and Stata (xtreg)

I'm trying to re-create an analysis done using Stata function xtreg (though I don't have the code) with ...
19
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1answer
17k views

Incidental parameter problem

I always struggle to get the true essence of the incidental parameter problem. I read in several occasions that the fixed effects estimators of nonlinear panel data models can be severely biased ...
11
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1answer
58k views

Panel Data: Pooled OLS vs. RE vs. FE Effects

We had some discussion about the usefullness of Pooled-OLS and RE Estimators compared to FE. So as far as I can tell, the Pooled OLS estimation is simply an OLS technique run on Panel data. Therefore ...
5
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2answers
4k views

Interaction suppresses the main effect? How to interpret it?

I have a simple model without interaction and it stated significant effect for all the explanatory variables (continuous variable rok and categorical variables obdobi (levels hn and nehn) and kraj: <...
5
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2answers
9k views

2 period difference-in-differences fixed effects versus OLS

I have a question on the difference-in-differences estimator. Suppose my data consists of two periods and the treatment is administered to some of the individuals in period $t = 2$. I estimate this ...
8
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1answer
29k views

Difference between one-way and two-way fixed effects, and their estimation

Consider a basic linear unobserved effect panel data model, e.g.: $$Y_{it}=\beta x'_{it}+c_i+\lambda_t+u_{it}, \quad t=1,\dots,T$$ where the vector $x_{it}$ contains the independent variables and $u_{...
7
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2answers
3k views

Zero-inflated two-part models for semi-continuous data

I am trying to study predictors of companies' pollution output of some specific chemicals. The data I am using have many 0's (i.e., the company did not pollute at all with those chemicals) and then ...
2
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1answer
637 views

Is subtracting individual means in pre-processing an appropriate alternative to dummy variables for fixed effects panel data estimation?

Is subtracting individuals means during pre-processing of panel data exactly equivalent to including dummy variables for fixed effects estimation? If not, what are the differences, and is there some ...
6
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1answer
277 views

The difference between DID and fixed effect model

It is said that the DID (difference-in-difference) is a special case of the fixed-effect model. However, in my understanding, they solve different problems: In the case of DID, there is an unobserved ...
5
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1answer
3k views

Presenting marginal effects of logit with fixed effects

I have a traditional logit model with a dichotomous dependent variable and several independent variables. One of the IVs is categorical and in my R code, I treat it as a factor. In the past, I've ...
5
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1answer
1k views

Difference-in-differences with no pre-treatment?

The typical difference-in-differences estimator (as fixed effects) fits a model of the form $$ y_{it} = \alpha_i + \delta T_{it} + X_{it}'\beta + \epsilon_{it} $$ where $T$ is some treatment that ...
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1answer
557 views

Is adding a time dummy the same as estimating by within-time fixed effects?

Is it the same to estimate the time fixed effect by the within estimator and by simply adding time dummies in my regression equation? Why would that be the case mathematically? edit $$\text{Y}_{...
7
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1answer
518 views

Three way fixed effects vs combining two of the effects

I have panel data on employment that varies by year, sector and location and thus would like to run a fixed effects regression considering these 3 dimensions. The issue is that I use R and the ...
4
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1answer
143 views

How do random effects adjust for confounding in a model?

How do random effects adjust for confounding in a model? This post explains that they do just as fixed effects do. This makes sense intuitively. However, I don't understand how the inclusion of a ...
3
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1answer
680 views

Does Frisch–Waugh–Lovell theorem change the covariance matrix on regression coefficients?

I know FWL theorem allows you to compute a subset of the regression coefficients, i.e. for fixed effects models. It can give you identical regression coefficients as you solve the whole regression ...
3
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1answer
702 views

Does random effect always produce the same result as fixed effect?

I have two models - one is including a categorical covariate as a fixed effect, the other includes it as a random effect: ...
0
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1answer
217 views

Is this logit model a multilevel model, and what is the correct way to model it?

I am analyzing a sample of about 6000 actions carried out by about 500 multinational companies in about 80 countries during a 6 year period. Actions are carried out randomly, and are not longitudinal ...
0
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0answers
105 views

Difference in intuition: threeway fixed effects vs interaction of two of the effects

my question is a follow-up on a previous question of mine: What is the difference in using, as I said in the previous link, I have the possibility of using either area $(a)$, time $(t)$ and sector $(...
27
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3answers
48k views

When to use fixed effects vs using cluster SEs?

Suppose you have a single cross-section of data where individuals are located within groups (e.g. students within schools) and you wish to estimate a model of the form ...
16
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1answer
11k views

When is it necessary to include the lag of the dependent variable in a regression model and which lag?

The data we want to use as dependent variable looks like this (it is count data). We fear that since it has a cyclic component and trend structure the regression turns out to be biased somehow. We ...
13
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2answers
269 views

What is the Frequentist definition of fixed effects?

Bolker (2015) writes on p. 313 that Frequentists and Bayesians define random effects somewhat differently, which affects the way they use them. Frequentists define random effects as categorical ...
4
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2answers
60k views

Using pooled OLS when running a model with panel data?

How bad is it to use pooled OLS instead of fixed effects when you have 7 years of panel data? From what I have understood, the risk is that the coefficients will be correlated with the error term, ...
14
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3answers
5k views

Removing factors from a 3-way ANOVA table

In a recent paper, I fitted a three-way fixed effects models. Since one of the factors wasn't significant (p > 0.1), I removed it and refitted the model with two fixed effects and an interaction. I'...
7
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3answers
8k views

What is the intuition on fixed and random effects models? [duplicate]

Now I'm having a hard time having a grasp on the difference between fixed and random effects of regression models. I believe I understand it's recommended to use random effects if you consider ...
5
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1answer
5k views

Fixed-effects using demeaned data: why different standard errors when using -plm-?

I am fitting a Fixed-Effects model, with intercepts at cluster level. One of the most direct ways is probably to use the -plm- ...
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1answer
579 views

Fixed/Random effects model

I am trying to understand/visualize it in my head how fixed/random effects models work. Can someone explain how can I infer something about the population from which I drew the sample with random ...
12
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3answers
5k views

Is the Mundlak fixed effects procedure applicable for logistic regression with dummies?

I have a dataset with 8000 clusters and 4 million observations. Unfortunately my statistical software, Stata, runs rather slowly when using its panel data function for logistic regression: ...
4
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1answer
2k views

Two-way repeated measures linear mixed model

This is my first endeavor into linear mixed models, and I haven't found an example that uses a fully repeated measures design, so I was hoping that I could get some help. I have a dataset that looks ...