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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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Subtracting fixed effect term for visualization

Suppose that I run a fixed effect model $$y_{ij}=\beta_0+\beta_1x_{ij}+d_i+\epsilon_{ij}$$ where $d_i$ is the fixed effect model for group $i$. Now that I want to show the data, is it appropriate ...
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10 views

Panel regression with multiple fixed effects and heterogeneity

For a research project I am supposed to estimate a panel regression model on a dataset with user data over observation time (the sample is assumed to represent general population). The supervisor is ...
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21 views

Standard error implications when combining IPTW and difference-in-differences

My question is about combining Inverse Probability of Treatment Weighting (IPTW) with a difference-in-difference regression with two periods (pre and post treatment). Basically, I first computed the ...
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14 views

Multiple fixed effects logit regression [closed]

I have a panel data set containing weekly observations of products in stores. I am trying to model the failure of products in a store using logistic regression, where the dependent variable is a 0/1 ...
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1answer
35 views

Understanding whether to use two-way effects [duplicate]

Using plmtest, I find that individual effects are significant (p: 7.327e-05); time effects are not significant (p: 0.1263); and two-way effects are significant (p: 0.0001197). Based on these results,...
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5 views

Mixed effect model for data with paired/unpaired data

I have tested individuals on the number of parasites (ranging from 1 till 3) they have. For each parasite I described the severity of infection (ranging from 0.5 till 3). As an example, here a part of ...
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20 views

Degrees of freedom using nlme

I'm having a very similar issue to this post: Degree of freedom with mixed model , using nlme package? But unfortunately the post does not contain a real answer. I am not understanding how the nlme ...
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7 views

R | Large-Sample Fixed-Effects Interaction using plm

How can I model Interactions with fixed effects for a large sample using plm? I have a panel data set with > 100,000 observations and I am trying to model a dummy-interaction with one of two fixed ...
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8 views

lme4 How to interpret a random slope effec while there is no fixed effect?

I have a question regarding the interpretation of multi-level models. This is my first model: m1 = lmer(Y ~ x1 + x2 +(1| class), REML = FALSE, data=dataset) In ...
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0answers
18 views

Proving First Difference is more efficient than OLS

I am trying to prove that the First Difference method is asymptotically more efficient than OLS when the error term follows a random walk. Assume the following model $$\begin{align}y_i&= \mathbf{...
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13 views

How to deal with unbalanced data in time fixed effect models

I'm dealing with a time fixed effect model with unbalanced panel data. Specifically, I am trying to predict the probability of default with fundamental data. Let's say I have a panel of 10 firms with ...
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1answer
60 views

Clustered standard errors are completely different in R than in STATA

I'm trying to reproduce a study in R. Here are its core elements: study wants to measure the effect of a transit strike on highway delay independent variables: strike: binary dateresidual: ...
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8 views

Should geographic location always be included as a random model effect?

Under what sort of experimental conditions and/or objectives might someone be justified in modeling geographical location as a fixed effect (assuming that most times location is included as a random ...
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12 views

moderators, control variables and time-fixed effects for panel data using plm package

I have panel data that consists of 33 companies, 70 CEOs and 30 years. I want to measure the effects CEO narcissism (=x) has on the internationalization (= y) of companies. the fixed effects model is ...
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19 views

Regression with varying weights within fixed effect units

I'm running a regression where within the fixed effect groups, the weights are not constant. However, since there are many fixed effects, I would like to use an estimation method as implemented for ...
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0answers
12 views

The Within estimation with multiple Fixed Effects

I'm trying to understand the logic of the within-interpretation with multiple fixed effects. I already found a helpful post (Fixed Effects and Within Variation) for the case with individual fixed ...
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1answer
73 views

OLS, Fixed effects or Random effects Model?

I am a little bit confused about type of model to apply because my type of data. I am interesting in get regression parameters for time (dependent variable) with independent variables= sex + age+ ...
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0answers
10 views

standard error adjustment in pooled panel regression with time fixed effect

I am fitting a pooled-panel cross-sectional regression with a time fixed-effect: \begin{align} Y_{i,t}=a_t+X_{i,t}b+e_{i,t}. \end{align} But I have $E(e_{i,t}e_{j,t})\ne0$ for $i\ne j$, $E(e_{i,t}e_{i,...
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17 views

Analysing change over time

I have a panel data set with 5 ways. I'm working with the dependent variable X and the independent variables X1, X2 and X3. I'm interested in only the change of my variables on an individual level: E....
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0answers
15 views

Cook's Distance for FE Panel modell in R

My question is strongly related to this one, but I would need a more specific answer. I am running a FE regression with year dummies using the standard plm package ...
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34 views

same variable as both random and fixed effect in mixed models

Let's say I have a variable with 6 levels, for example, different tasks which are just a subset of all possible tasks. I am interested in differences between the tasks so should add it as a fixed ...
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18 views

How can I evaluate with R the interaction between a within-subject effect and a continuous variable at the subject level?

Scenario: 62 subjects did a selection task composed of 128 items, that can be divided into four conditions, because each item has a cue and a target (also other options but thats not of interest in ...
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20 views

lagged explanatory variable interpretation

I'm using a conditional fixed effects ordered logit model (blow-up and clusete namely) and a panel dataset to estimate the effect of a life-event (x) on ones preferences (y). My explanatory variable ...
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1answer
23 views

glmer categorical fixed effects estimate missing? -R

I posted a question recently regarding general linear mixed effects models, and I think I may have finally specified the glmer model correctly. I am interested in finding any differences in home range ...
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28 views

Fixed Effects for fractual response variable with many zero observations

I am investigating the impact of some independent variables on educational expenditure shares, which is given as the proportion of $\frac{educational\_expenditure_i}{total\_expenditures_i}$. The ...
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19 views

What is the difference between HAC and PCSE?

I have data consist of 88 companies in 5 year (440 observations) and used 3 independent variables with 3 control variables (total 6 variables). I have already test the best model for my data and the ...
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0answers
4 views

Absorbing continues-categorical variable interaction term and predicting ex-post

Is there a way of absorbing categorical and continuous variables and then predicting them, because I can not create so many dummy variables in any software somehow I have to obtain the coefficients on ...
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0answers
32 views

Wikipedia says that “The random effects model is a special case of the fixed effects model”. Why?

I understand that the assumption made in a fixed effects model is that there is a basic understanding of the included parameters, e.g. there is a proven theory or previous experiments have shown non-...
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40 views

“ANOVA on a non-random non-Normal sample from a Normal Population”

How can I run ANOVA or tests for statistical significance on a bi-modal sample that came from a normal population? Context: I was tasked with running an ANOVA to see if genotypes (treatments / ...
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0answers
16 views

Which regression model in appropriate when dependent variables are at individual level and independent variables at national level?

This is actually a panel data where dependent variables are in binary figures y1 ... y4 exhibiting thousands of entries for a single country. On the other hand few independent variables are on the ...
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0answers
21 views

HLM, MLM, LMM: How to approach this problem? (in R)

I'm trying to do a HLM analysis on a current project. Basically is data collected from surveys where each person gives a "grade" (as integer) to an specific business X. Also, this business belongs to ...
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1answer
43 views

Multiple regression with a factor variable in R

I'm trying to run a multiple regression on a dataset in R. The structure of the data that I want to use for the regression is as followed (only showing the variables I want to use): ...
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30 views

Which is better- lsdv model or the xtreg Fe model?

Are the results of lsdv and xtreg Fe model same? Or if there is any difference, then which model is better?
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22 views

Any efficient way to solve the problem of panel regression' coefficient become insignificant

This is my very first time to post my question in this forum, so let me go straight my problem. In my research project, I am examining the impact of temperature and precipitation on growths of per ...
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0answers
14 views

Panel Data with time values within panel

I have data that consists of daily prices of $n$ products in $m$ stores. I want to make a panel regression, where the price is the explained variable using some other variables. I managed to do it so ...
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0answers
8 views

Decomposition of time common shock and idiosyncratic shock in Panel VAR (with fixed effects?)

After a good run through the literature on what estimation procedure to follow on the following problem without finding an answer I resort to the stats community. The model originates from Darrell ...
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28 views

Using interactions with time variable in fixed effects modelling (PLM package R)

I'm trying to run some fixed effects models for housing stress using the PLM package in R. Based on the existing examples/documentation time variables are often used as part of the index to identify ...
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0answers
14 views

Terminology of fixed vs random effects panel data?

In short, in a fixed effects model, the individual effect is correlated with the regressors, while in the random effects model it is uncorrelated. But what does "fixedness" have to do with the fact ...
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85 views

Year fixed effects for cross-sectional data

I would like to know whether I can add fixed effects to my linear OLS regression model using cross-sectional data. My regression model is $$ Performance_{n,i} = β_0 + β_1 (Performance_{n-1,i}) + ...
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0answers
16 views

Ability of fixed-effects analyses to enable generalisation of results

Is it correct to say that, when making inferrence on the results of an experiment, using a random-effects (RFX) rather than a fixed-effects (FFX) model merely makes the results more generalisable, as ...
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33 views

Which test is the most convincing?

Brief background: I’m examining mediation rates in China. I have a panel dataset with N=24 provinces and T=30 years (1985-2014). For each province-year, I observe mediation rates and host of economic/...
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0answers
100 views

Is it possible to fit a quantile regression fixed effects model on a repeated measures, panel data, with a nested structure?

In the rqpd package manual it is demonstrated how to fit a fixed effects model on a repeated measures data structure. I am looking for ways to extend this to a repeated measures nested structure, i.e. ...
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36 views

How to solve a well fitted model - Model Misspecification

I am currently writing a paper, analysing the impact of goldprice movements on the capital structure of gold mining firms. My basic model is a simple OLS model with (y=leverage and x=ln(goldprice)). ...
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48 views

Comparing the regression coefficients of two time periods using unbalanced panel data and a fixed effects model

I'm currently trying to investigate how investors change their asset allocation due to liquidity risk and if their behaviour has changed since the financial crisis. My data contains the asset ...
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0answers
102 views

Interpreting stata output of regression with multiple fixed effects

I am running a regression of a variables $Y$ on $firm plant$ and $firm \times time$ fixed effects. There are no independent variables in the regression except for the fixed effects. Here is the ...
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1answer
21 views

Are random effects used for explanatory variables measured with inaccuracy or for explanatory variables designating a subset of groups?

Quote I am reading from Quinn and Keough's book. In chapter Correlation and Regression, section Fixed X, at page 94, they say Linear regressions analysis assumes that the $x_i$ are known constants,...
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0answers
26 views

identical results for fixed and random network meta analysis

I performed a network meta-analysis in r package netmeta using the netmeta function and the results are identical for the fixed and random effects analyses. Is this possible or did I do something ...
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0answers
21 views

Interpreting coefficients in linear regression when controlling for multiple levels of fixed effects

Suppose I'm estimating the effect of putting in-store advertisement on supermarkets to sell my brand of bread. Let the demand at store $s$ at time $t$ be $$D_{st} = \beta A_{st} + \gamma_s + \...
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2answers
88 views

Sensible to remove interaction term in this instance, to interpret a main effect?

Predictor A is a continuous predictor. Predictor B is a dummy coded categorical predictor with three levels. I run a regression including PA, PB and PA*PB. The results indicate a significant ...
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23 views

Estimating Panel Data by Fixed Effect Model with Lagged Dependent Variable(s)

When estimating panel data, to control for time-invariant effects, the fixed effect model is suggested. However, due to the issue of the degree of freedom, it is also suggested to use demeaning of ...