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Questions tagged [panel-data]

Panel data refers to multi-dimensional data frequently involving measurements over time in econometrics. It is also called longitudinal data in biostatistics.

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Interpretation of lavaan SEM growth coefficients and covariates' influence on slope

Hello and thanks in advance for advice. I am running the growth() command in lavaan. This is a follow-up to my previous post on this topic (wow, a whole year ago!). ...
Jeanne Sinclair's user avatar
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GLM for longitudinal or time-series -- how to model and interpret a binary logistic regression over time controlling for covariates using R

I work with the risk of delays (0 = no risk, 1 = risk). I want to run a binary logistic regression considering panel data over time. I have data from 4 years (4 time-points) and some covariates (...
Luis's user avatar
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Why do dynamic panel data models with random effects yield different effects depending on the R package (plm vs lme4)?

[Edited for clarity and detail] Summary: A random effects model should produced biased estimates for a dynamic panel, but the lmer function of the R lme4 package ...
Hernan's user avatar
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Interaction of endogenous variable with binary predictors (feols)

I would like to inquire about the correct way to specify interactions of endogenous variable with binary predictors (time and treat) with the feols function. Ideally I would like to specify a 3 way ...
Shen Shen's user avatar
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Can you use a binary outcome variable in a longitudinal latent-growth mediation model

I am wanting to create a LGCM in which I am assessing whether two latent factors (the intercept and slope) mediate the relationship between a continuous predictor and binary outcome variable but am ...
user417995's user avatar
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The difference between conditional and unconditional models when developing a longitudinal mediation latent growth curve analysis

I was just wondering if anyone could advise me on what the definition of an unconditional and conditional model when you are taking a stepwise approach to developing a mediational latent growth curve ...
user417995's user avatar
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Fixed-effects using demeaned data: Why are the demeaned predictions different from original data w/ fixed effects?

I'm hoping someone can help me understand why a fit regression model making predictions on panel data with group fixed-effects, outputs different results than the same model predicting on the same ...
hayfreed's user avatar
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Missing data in longitudinal study; SPSS; Python

I have a dataset in psychology field with 3 measurement points (longitudinal data), 4 questionnaires, and about 120 participants. There is a lot of missing data in this dataset. I need to clean the ...
eagersquirrel's user avatar
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small sample size (need some advice)

I have a prospective longitudinal study. We track and observe a group of people over a two-year period to learn about their cognitive ability. The event variable is binary, and the primary aim is to ...
elisa's user avatar
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Tobit estimation on panel data in combination with an IV approach in R?

I have panel data (country by year) and my dependent variable is left-censored (many countries have zero values, other countries have very large numbers). So, I think that I should implement a Tobit ...
TFT's user avatar
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Centering Variables in Multilevel Models with Longitudinal Data

Enders and Tofighi 2007 provide a discussion on the various ways users can center variables in multilevel models and when each situation is appropriate. While they largely focus their commentary on ...
Brian Lookabaugh's user avatar
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If two IV yield distinct F-statistics in the first-stage regression, does it indicate that they are different IV, regardless of the correlation?

Suppose we are in a panel context where we are estimating while controlling for fixed effects. Let's assume that we have two instruments Z1 and Z2 for the X endogenous variable and both instrument are ...
msc's user avatar
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1 answer
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Clustered standard error - intuitive explanation

I understand that the standard error is standard deviation of the sampling distribution about some parameter, for example the sample mean or a coefficient in a regression model. I also know that when ...
jbuddy_13's user avatar
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time trend interaction

I have a panel dataset, and I want to perform some econometric analyses on it. I want to use a trend that interacts with the initial value of certain economic variables. For the trend, does it make ...
fernand's user avatar
1 vote
2 answers
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Modelling longitudinal pre-/post-intervention data

I have longitudinal data of a number of patients for which some biomarker was measured at irregular time intervals over the course of several years before treatment and over a shorter period of time (...
Gods_gift_to_biostatistics's user avatar
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How does the pvarfeols function from the R panelvar package handle fixed effects?

I have been using the pvarfeols function (Fixed Effects Estimator for PVAR Model) from the R panelvar package. It seems like the ...
catin's user avatar
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Diff-in-diff with an unbalanced panel

Say I want to study the effect of some intervention using a diff-in-diff setup. I have a panel of units observed during some period. I can identify treated/non-treated groups and pre/post periods (...
chris_chris's user avatar
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Matching on actual earnings versus matching on the kind of unexpectedness in earnings

For simplicity, lets assume this is a question about linear modeling, although I am actually looking at some non-linear models and am willing to consider other models if they would be more ...
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Panel Data logistic regression

I am working with a panel dataset that describes company code as an id variable and fiscal year as a time variable (1500 firms from 2013-2022). The dependent variable is binary. First I checked for ...
Lou's user avatar
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Appropriate analysis to determine who benefits more and less form a program

Around 150 participants attended a 3 months program (no control group). I have their scores before and after the program on several measures (T1 and T2). Participants went to a program in 4 different ...
Me123's user avatar
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How to cluster standard errors in R studio for mediation model?

I have a simple mediation model: IV: Experience (binary - yes1/no0) Mediator: Trust (5 point likert scale measure) DV: Offer (continuous, values can be anything between 5 and 15) Each respondent (ID) ...
breeks's user avatar
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1 answer
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Standardized or unstandardized coefficients to report? The covariances and regression of a multivariate latent growth model

I am currently running a second-order latent growth curve with multiple constructs. This multivariate latent growth curve demonstrates how two (or more) constructs travel together across time. My ...
EmH's user avatar
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Cross-lagged panel analysis many variables

I'm planning an analysis to look at individual coping strategies, specifically what predicts well-being at follow-up (or vice versa). I think cross-lagged panel analysis might be the best approach so ...
Stats begginer 's user avatar
6 votes
2 answers
213 views

Joint Models for Longitudinal and Time-to-Event Data vs Survival analysis with a time dependent covariate

I need some help to understand the difference between survival analysis (cox regression) with time-dependent covariates and Joint Models for Longitudinal and Time-to-Event Data (JM package in R). ...
Stat2024's user avatar
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A prospective longitudinal study with time dependent covariate

My question is similar to Sample size calculation for multivariable Cox regression for treatment comparison. I have a prospective longitudinal study over three years. The purpose of the study is to ...
user413503's user avatar
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Longitudinal analysis

I have a question. Suppose that I want to analyze if a particular variable "X" affects the incidence of a disease "D," but I do not have the information about "D" at the ...
user99751's user avatar
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workflow to analyse FAERS longitudinal data

The FDA adverse event reporting system (FAERS) data is a database that contains information on adverse event and medication error reports submitted to FDA. It is published quarterly from 2004 to 2024. ...
Jenn0804's user avatar
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Observational pre post design and confounder adjustment

I have observational data with baseline, and two follow-up measures with a binary treatment. Dependant variable is questionnaire scale score ***. I am planning on fitting a linear mixed effects model ...
user167591's user avatar
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What happens to the data when entity- and time-fixed effects are applied?

Let us assume that the true data generating process is as follows: Y_it = beta_0 + beta_1 X_it + u_it What happens exactly when I apply both entity- and time-fixed ...
TFT's user avatar
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how should i analyze panel data if all units are treated simultaneously?

I possess a dataset of 273 companies from the time period 2001-2017, and i want to study whether the effect of the policy (that was implemented in 2009) on profit was moderated by industry type. My ...
user413005's user avatar
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1 answer
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statsmodels: Update OLS' degrees of freedom when absorbing 3+ fixed effects

I want to run an OLS regression with 3+ fixed effects. (Whether this is a good idea is out of the scope of this question). I can do it using Stata: ...
ebosi's user avatar
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1 answer
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Should I use mixed effects model?

I have a sample of real sales data about plant-based products. These data are collected across a monthly period from 2019 to 2023. So I have some labels for this like "1-2019", "2-2019&...
Margherita's user avatar
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How to deal with exposure status change and outcome contribution in different exposure status?

I want to estimate the risk of cardiovascular events in patients with diabetes (exposed group) compared to patients without diabetes (unexposed group). How do we deal (in the analysis) with patients ...
Nao's user avatar
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Cut-off based on an ordinal variable in unbalanced panel data

I am currently looking for an appropriate statistical analysis for my research questions. I have a continuous variable (score) and an ordinal variable (test). Score is quadratically related to Test, i....
a.henrietty's user avatar
1 vote
0 answers
43 views

How to deal with outliers in panel data? [closed]

When we have cross-sectional data, we can easily detect and remove outliers. But how should one approach outliers when we are dealing with panel data? Since we have $i$ entities and $t$ times periods, ...
TFT's user avatar
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pooled time-series regression

Suppose I am running country-level time-series regressions of stock market returns $r_{i,t}$ on some global predictor $p_{t-1}$ , where $i$ and $t$ denote a country and a month, respectively: \begin{...
Daniel Pinto's user avatar
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39 views

Do first and second stage regressions combined with fixed effects have to follow the same model?

I suspect reverse causality between Y and X1, therefore I'm applying an instrumental variable approach to panel data. My main regression consists of country- and year-fixed effects. Do I have to also ...
TFT's user avatar
  • 345
1 vote
1 answer
62 views

Normality of residuals in panel data

I ran a linear regression containing country- and year-fixed effects from a sample containing panel data (country by year). Since I'm using OLS, do my residuals have to look approximately normally ...
TFT's user avatar
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Firm Fixed Effects Model dropping Sector Dummies? Potential Solution?

For my thesis, I am using panel data with stock returns and other firm data. I first used an event study to calculate abnormal returns (with event window of 7 days so 7 observations for 500 firms) ...
mek1401's user avatar
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0 answers
22 views

Clustering multiple longitudinal variables

I wish to do longitudinal cluster analysis of 51 individuals, each with 11 variables, each measured 23 times at even intervals. What I have been able to find of longitudinal clustering seems to ...
Bryan's user avatar
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1 vote
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57 views

Event study: Group periods at margins

For an event study (staggered Diff-in-Diff with different treatment periods) I would like to group the periods at the edges so that we get the coefficients for <=x / >=x , such as: For starters,...
kemajuan's user avatar
4 votes
2 answers
92 views

Mixed Model for Repeated Measurement (mmrm) - Assumptions

I want to fit a mixed model for repeated measures (mmrm) on a set of panel data with 6 visits and N = 1200. I want to estimate the effect of time passing on the outcome, without any intervention since ...
Lea's user avatar
  • 123
4 votes
2 answers
112 views

How to split and sample "Panel Data" when training a Logistic Regression to predict future outcomes

Introduction I have panel data where customer behavior is observed over time. For each customer at a given reference date, I have a lookback window of 12 months for generating features, and a look ...
Esben Eickhardt's user avatar
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0 answers
21 views

Addressing Scaling Bias in Panel Data Analysis

I am running an (unbalanced) panel data analysis, where the dependent variable is, $fixed\ cost\ (per\ ha)$ for an agricultural firm $i$ in period $t$. The explanatory variables are the hectares per ...
Tom's user avatar
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4 votes
1 answer
113 views

Instrumental variable with measurement error

I have a question related to measurement error bias and the use of instrumental variables. Assume I have a continuous outcome variable $Y$ which is observed with no error and an endogenous (continuous)...
Panagiotis's user avatar
0 votes
1 answer
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Principal Component Analysis using Panel Data

I have a panel data with identifiers(a,b,c,....z) and different times(t=1,2,3,....100) I have 6 different variables (A,B,C,D,E,F) for every identifier-time observation. I attempt to use those 6 ...
Ken's user avatar
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2 votes
0 answers
27 views

RI-CLPM - do we need to restrict residual variances of factors to 0?

I am currently exploring Random Intercept Cross-Lagged Panel Models (Hamaker, 2015) using the lavaan code provided in this website https://jeroendmulder.github.io/...
ckl's user avatar
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Weighting procedure in longitudinal design

I am currently trying to figure out what to do but I can´t seem to find a proper solution. My problem is the following: I have a longitudinal design. For each day I have a variable stating whether an ...
Laura's user avatar
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1 vote
0 answers
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Comparing assessment methods in longitudinal design

I am currently trying to figure out what to do but I can´t seem to find a proper solution. My problem is the following: I have a longitudinal design. For each day I have a variable stating whether an ...
Laura's user avatar
  • 49
1 vote
1 answer
27 views

Different time trends of groups: quadratic vs. linear decline

Suppose we have two groups of individuals A and B that we observe over time on a parameter, say blood pressure. We want to compare the group effect over time in a GLMM using ...
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