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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Constrained baseline analysis in R [closed]

I have a longitudinal dataset for a randomised controlled trial with a continuous outcome, where there are two arms (arm), and an outcome (...
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Modeling single binary outcome (end-point only) with longitudinal covariates

My dataset: I have a binary outcome variable (dispersed, not dispersed) that I would like to model using several explanatory variables. Some of the explanatory variables are single time point (e.g., ...
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How to decide whether to treat the time variable as categorical or continuous?

I collected data at four waves (i.e., four time points), and I want to use a linear mixed model to analyze the data. Is it better to treat the time variable as categorical or continuous?
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combining the data in longitudinal study

In longitudinal studies, there are two longitudinal projects with the same measurements. Study A: (Wave 1) 2015 -> (Wave 2) 2019 (4-year longitudinal) Study B: (Wave 1) 2018 -> (Wave 2) 2023 (5-...
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Linear Mixed Models or Structural Equation Modeling, which one to use?

I am currently trying to figure out whether to use LMM or SEM (or something else?) for my longitudinal mediation study (3 time points). I want to investigate the effects mentioned below, and I am ...
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Is a MSM with no lagged values equivalent to simply using IPW to balance a data set?

I am working on a project employing a panel data set with a large N but a fairly small T (5 time periods). MSMs seem like a good strategy, but I am wary of the incorporation of lagged values since ...
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Panel vs Pooled OLS

My sample comprises of data on accounting performance of companies that had their IPOs between 2009-22. I want to examine if companies which had more foreign investor participation in their IPOs ...
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IPW Weights for Marginal Structural Models for Different Estimands

As Blackwell and Glynn 2018 note, an interesting property of marginal structural models is their ability to estimate treatment effects that account for the dynamic properties of panel data. For ...
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Bad model fit for a second-order growth curve with time-varying covariates. Do I have to find a way out or will it depend on the aim of the analysis?

I am running a second-order latent growth curve model with seven repeated measures. I have 2 time-invariant covariates (TIC, country and sex) and 2 time-varying covariates (TVC, both are latent ...
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What is the difference between linear regression on two time periods with a time dummy variable and two separate regressions for each time?

I have panel data with two time periods on individuals aged 50+. I am interested to see if if the coefficients on dependent variables $X_{it}$ (e.g, age, gender, health) change from one time period to ...
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Interpretation of coefficients in panel data

A colleague asked me a question about the interpretation of coefficients in a panel data regression. I'm not familiar with this field but I want to help. The question is this: In our project, we ...
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Difference in differences when treatment status is revoked

I am trying to analyze the effect of receiving "elite" status on a university's number of international first-year students. I have a perfectly balanced panel of 17 universities over an 18-...
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Is there a way to make a latent class a predictor of a latent growth model?

I was wondering if it is possible to run a second-order latent growth model, where latent classes can be added as a covariate? I have three variables of which I have 7 repeated measures, say, variable ...
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Linear mixed models with factors as interaction terms: what is being compared?

I am struggling to specify my linear mixed models, as I am relatively new to interaction terms. Subjects were given a drug after the first observation, and the aim is to identify time points for which ...
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Test serial correlation for panel data

I have a set of panel data (including variables X1, X2, X3. and N=193; T=22) these variables are used as independent variables in the model. I want to check the autocorrelation of each of these ...
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Total N patients for precision around a rate, with varying FU times

To design a retrospective longitudinal study (outcome: certain event after drug exposure), we know that the annualized rate of that event is 0.06%, aka 0.0006/person-year (possibly underestimated as ...
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A complex crossover study: addressing unbalance and time effects

I'm analyzing a crossover study, where subjects are measured at two time points during each treatment phase (Placebo or Treatment). Additionally, baseline measurements were taken before the experiment ...
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Interpolation on bond issuance data

I am currently working on an analysis on bond issuance during the COVID pandemic. I will run a linear regression of spread on multiple bond issuance characteristics but also on multiple firm key-...
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Which approach (probably similar to 2SLS) should I use in order to estimate effects of fitted and residual components? Thinking about CF but not sure

I assume that the growth of variable $Y$ depends on variable $X$, and that the variable $X$ depends on variable $Z$. I would like to estimate the effect of $X$ on the growth of $Y$, but to ...
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Multiple imputation: deleting cases before imputation

Note: The question has been edited to make it more focused, and the title has been changed to make it clearer. I have read questions/answers about how to select variables for imputation. This question ...
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Is the design matrix in a panel regression model a tensor?

In a panel regression model of the form $$Y_{it} = \mathbf{X}_{it} \pmb{\beta} + \epsilon_{it}$$ where $Y_{it}$ is the dependent variable for unit $i$ at time $t$ $\mathbf{X}_{it}$ is a vector of $K$ ...
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How to deal with heteroskedasticity in my regression [closed]

I did a fixed effects panel data regression for a dataset consisting of ~$3000$ entries from firms within different industries and countries over a span of ten years. My main dependent variable is ...
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dummy variable approach versus fixed effect and first difference approach

While studying Panel data analysis I came across the following reasoning. We have the following general model $$ Y_{it} = \beta_0 + \beta_1 X_{it} + v_t + \alpha_i + u_{it}$$ where $v_t$ is the fixed ...
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Robust Difference-in-Differences: What is the propensity score doing?

Callaway and Sant'Anna (2022) describe a doubly robust difference-in-differences (DiD) method that is attractive in staggered DiD (multi-group treatment times) for several reasons. It can prevent &...
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month level fixed effects model

I am trying to understand the effect of migration of a male member on the employment outcomes of left-behind women. I have monthly observations for 5 years. I am using a fixed effects model with month ...
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Deriving log-likelihood contribution involving fixed effects (panel model)

I would appreciate some help with the following problem: We have the following panel model: $y_{it} = h(x_{it}\beta + c_i) + \epsilon_{it}, \quad t=1,\ldots,T, \quad i=1,\ldots,N $ where \begin{align*}...
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Firm fixed effect with lagged dependent variable

Let $r_{it}$ be the asset return at time $t$ of company $i$. Now consider this model: $$ r_{it} = \alpha_t + \delta r_{i,t-1} + \beta \, \text{Size} + \lambda T + \gamma_\text{TEC} + \varepsilon_{it} $...
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p values of latent basis models

I am running a latent basis model and wondering if anyone could provide insight on how to interpret the p-values of the basis coefficients. The basis coefficients are set to 0 at T1 and 1 at T9 and ...
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Normality assuption violation of time series data in the presence of outliers

I have a dataset containing information on district wise monthly dengue incidence from 2010 to 2021. I have found that there is a sudden increase in the dengue incidence due to a new variant in 2019. ...
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System GMM Estimator

Consider the dynamic linear model given by: \begin{equation} y_{it} = \rho y_{i,t-1} + \alpha_i + \nu_{it} \end{equation} where $\alpha_i$ represents individual fixed effects. The GMM two-step ...
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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 ...
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Can you consult modification indices of a fixed-factor approach of longitudinal invariance to aid decision making in other scaling approaches?

I am learning how to test measurement invariance with different scaling approaches and came across a book chapter that said that modification indices of a fixed-factor approach are more trustworthy ...
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Multilevel Marginal Structural Models and Centering Predictors

I have read that centering the values of predictors (subtracting the individual, $i$, value from the group mean, $j$, value or the grand mean) in a multilevel models aids in the interpretability of ...
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Treating longitudinal data as a repeated cross section

Can you introduce bias by treating longitudinal data as a repeated cross section? Suppose I have two data sources measuring the same variables. The first is a balanced panel dataset $\{y^{long}_{it},X^...
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How to deal with missing longitudinal outcome and longitudinal covariate?

I have data with a continuous longitudinal outcome and one of the covariates is a categorical longitudinal variable. Both of them have missingness and were collected at the same time. So this means if ...
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Time dummies - Intuition

Consider a simple two-way fixed effects model: \begin{equation} y_{it}= x_{it} \beta + \alpha_i + \delta_t + u_{it} \end{equation} where $x_{it}$ is a row vector of regressors of size $K$, and $\...
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What are other measures to consider when you don't have modification indices in your invariance test?

I have a question considering longitudinal invariance testing. The software I use is Mplus and I have tried three different scale application approaches; reference indicator approach, fixed factor ...
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How to calculate standard errors in the finite mixture model

I have a panel dataset, and I am estimating a self-defined likelihood function using finite mixture model. $$ L_i(\theta)=p\prod^T_tL(y_{it}(\theta)|type1) + (1-p)\prod^T_tL(y_{it}(\theta)|type2) $$ $...
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Which statistical tests should I use for predicting one variable with another one?

I want to investigate the association between the serum glucose level of a patient with type 2 diabetes at the baseline (continuous) and distal neuropathy (categorical), $5$ years after the diagnosis. ...
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Least-Squares Dummy Variables Estimator

Is the Least-Squares Dummy Variables Estimator always strictly less efficient than the fixed effects estimator?
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Understanding the Distinctions: Fixed Effects vs. Random Effects in Panel Data Analysis [duplicate]

I'm seeking clarification on the distinction between fixed effects and random effects in the context of panel data analysis. My understanding is as follows: Fixed Effects: In a fixed effects model, ...
The One's user avatar
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Natural log of ratios and two-way fixed-effects model bias

Bartlett and Partnoy (BP) (2020) show that OLS with natural log dependent variables that are ratios must include the $\ln(denominator)$ on the RHS in order to avoid bias (see pages 24-28) unless one ...
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Moderation analysis with longitudinal data?

My data is a from a family-based weight loss intervention. One of the intervention goals is to reduce intake of energy-dense, low-nutrient foods (we call these RED foods). One major behavioral ...
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Natural logged dependent variable and the ratio problem with two-way fixed-effects panel model

In a non-peer-reviewed (yet?) paper, Bartlett and Partnoy (BP) (2020) discuss some under-appreciated issues related to using ratios as the dependent variable. Some but not all problems are dealt with ...
dcoy's user avatar
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Estimator for Dynamic Panels with Individual Specific Slopes

I'm working on some economic stuff and the objective is to conduct a panel data analysis. I assumed the following data-generating process: \begin{equation} y_{it} - y_{i,t-1} = \eta z_{i,t-1} + \...
Maximilian's user avatar
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Bayesian Methods for Causal Inference with Observational Panel Data [closed]

How comprehensive is the toolkit for Bayesian inference when trying to make causal inferences with observational panel data? I can see an easy application with the incorporation of fixed effects or ...
Brian Lookabaugh's user avatar
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Variable Selection for Longitudinal Data with a Binary Outomce

I have a large longitudinal dataset (100,000 observations) with firm IDs and Years with about 1000 features (most numeric and ...
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1 answer
28 views

Is it alright to place equality constraints on the items loadings for assessing configural invariance using effect coding approach?

I am wondering if somebody can help me out with the syntax to run a longitudinal invariance test using effects coding approach in Mplus. I have figured out that to run a CFA with effects coding, I ...
EmH's user avatar
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Time being a mediator of sort but planned on used time varying cox ph model?

I am working on a project where literature has traditionally treated the exposure as a time-dependent exposure and used a time varying cox ph model. During the logistic, and normal cox PH analysis ...
user402261's user avatar
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Best Textbook for a Rigorous Treatment of Panel Data

I was wondering which book you recommend for a treatment of panel data that is both rigorous and intuitive. What do you recommend among Wooldridge(2010), Baltagi(2021), and Hsiao(2022)? I studied ...
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