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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Using Bayesian statistics in time series forecasting
I would like to forecast demand count time series of taxi fleets at different locations on the map at different points in time. I.e. multivariate demand Time series forecasting.
Given hierarchinal ...
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Should I adjust for inflation in a staggereded DiD with money as outcome and if so, how?
This question is currently making my head spin, and I haven't been able to find a discussion on it so far:
Suppose I am interested in the effect of an intervention, such as a healthcare reform, on a ...
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What is the difference between autocorrelated residuals and controlling for the previous time point in mixed effects models?
I have several dozen observations from about 100 people who participated in an ecological momentary assessment study. I am using mixed effects models to estimate the effect of $X_{t-1}$ on $Y$.
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Specifying a mixed effects model with repeated constructs but cross-sectional observations (crossed vs. nested data at three levels)
I have a question about specifying a mixed model with crossed data across multiple levels. Consider the following situation:
Let’s say I collected data on Americans’ perceptions about the importance ...
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interactions between variables using Generalized Linear Mixed Model in SPSS
I want to study which factors have an effect on the hormone PTH. PTH is used as a dichotome variable and is our outcome variable, the dependent variable.
We're using generalized linear mixed models in ...
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Two-Way Fixed Effects Model in R - Error - Multicollinearity
I am trying to build a two way fixed effects model (entity-specific and time-specific fixed effects). However, when I run the fixed effects code in R, I get the following error message:
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Longitudinal Studies with a Binary "Since Baseline" Variable
I came across a study design that I can't seem to find specific literature on:
Like most longitudinal studies, the subjects are re-measured at different time points
There is a binary outcome variable,...
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Equivalence between Mundlak and FE estimator: what with the generalized residuals of the control function?
I want to model the effect of an endogenous (left-censored) explanatory variable on a continuous outcome variable using an unbalanced panel dataset. For this, I use a control function approach.
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Logistic regression with industry×year fixed effects on Panel data in Python
I would like to use Python to run a logistic regression with industry×year fixed effects on Panel data (firmID, year). data contain the following variables :
firmID: firm ID (1000)
year : Year (2010-...
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longitudinal model vs anova
Does anyone know why longitudinal regression models are still able to work when you have a different number of observations for each person (non-balanced design)... but ANOVA models are not able to ...
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How to run a nested logit model with fixed effects in R or Stata?
I would like to run a nested logit model with panel data in R or Stata, but I am not sure how to proceed. I want to understand which factors influenced a person's choice to work full time, work part ...
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asking for synthetic control method with multiples outcomes and multiple treated units stats command please
I am trying to do synthetic control method with 2 treated provinces, 10 non-treated provinces, and 7 outcomes. Can anyone let me know which stata command I can use?
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Constructing a meaningful regression model
I'm developing a probit model to predict the partial effect of independent variables on the expected probability of my dependent variable being one (that is the event that a strong growth in GDP ...
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Is it possible to have an Indicator-spesific Trait factor model within a multiple indicator second order growth model?
I am running a multiple-indicator growth curve model over 7 time points.
One of my items has a large residual variance and seems to covary very well among themselves.
Thus, I assumed that it has a ...
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Time Series Modeling Question
I am trying to model the effect of volume traded on implied volatility of weekly options. I have the data for 52 weekly expiries at 5 minute intervals.
However the key insight is that each weekly run ...
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is there a way to to account for time-varying covariates in a negative binomial hurdle model?
i am investigating smoking exposure (0,1) and caries outcome (count data, 0-28). I am using a negative binomial hurdle regression model (considering excess zeros in outcome) for my analysis
Model 1:
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Accounting for repeated measurements vs cross section with averages
If I had repeated measures of the units in my sample, is it always preferable to analyse as is and account for these with a method such as GEE or a multi-level model - because of the gain in ...
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Possible to add Stochastic trend, seasonality and AR(1) term in mixed model? (Prediction in Joint Models) Short version
If I have a biomarker time-dependent variable sampled as a whole time serie, instead of few repeated measurements, and I want to fit a joint model to predict time-to-event as a function of the time-...
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Differencing and Stationarity in Panel Data Analysis
As far as I know, the source of randomness is different in cross-sectional and time-series analysis.
The following is my understanding.
When we use a cross-sectional data set $\{X_i\}_{i=1}^{N}$, the ...
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Path analysis for longitudinal data
I want to conduct a path analysis for longitudinal data with t = 13 (the model is presented below). Is it possible to make a path model for each individual at each time point? I am quite familiar with ...
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log-linear model and lmer function
I am running a mixed effects model (random intercept, fixed slope) for panel data with the same entities reporting for several years of data. I have read about running a mixed effects model using lmer ...
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Using feols() vs plm() vs lm() in panel regressions in R
I am using panel data at the district level. My outcome variable is the share of employed individuals in a given district. I am regressing this variable on a binary treatment dummy called "treat&...
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lmer() for the case when the independent variable ( covariate ) has only one measurement and the dependent variable has multiple measurement
How can a linear mixed-effects modeling approach using the lmer() function be applied to investigate the relationship between a single-measured independent variable ...
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Panel data analysis
GEE is one of the models that used in panel data, one example is
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I want to know if my use of fixed effects (PLM) is correct
I have a panel dataset (Young Lives Dataset) which follows children from age 8-22 in five different rounds. I am using information about the children's time-use in rounds 2-4, when they are still ...
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Which model for panel data with non-random observation numbers per person?
I did an experiment where I randomly assigned participants to control and treatment group. All performed a task in which they had to illustrate images and then select one image in the end to be payoff ...
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Best way of splitting panel data for machine learning
I am trying to train a machine learning model to predict the probability that a given credit card customer defaults within the six-month window after the observed date. In this context, default means ...
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Any way to test if the association between X and Y could be causal, reverse-causal or non-causal (just correlation)?
I'm doing a regression between Institutional Investment and Total Debt for 500 companies over 2000-2022. Basically, it's panel data. I get the results of the regression and I see that the two are ...
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HAC Standard Errors - Number of Lags in an Unbalanced Panel
I am working on a panel dataset with a lot of missing data. Because I have reason to believe that the error terms are autocorrelated, I want to use HAC (Newey West) standard errors. I am unsure how to ...
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How to estimate the effect of time series on a variable sampled irregularly and much less frequently for multiple subjects
I’ve been struggling for several days to find the proper statistical analysis tools for my problem, and I’m hoping for some valuable tips and insight from the internet. I’ve read up on ARIMA(X), ...
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Questions about efficiency of estimators with longitudinal data
I'm modelling data with repeated observations; I'm reading up on options and pitfalls, and have a few questions.
Coefficient estimates are still unbiased and consistent in the presence of ...
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Cox regression with binary time-varying covariate
I am researching the association between menopause and the incidence of diabetes(outcome).
I have a baseline and three follow-up assessments. Given that women transition from non-menopausal to ...
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Which observations should I use for my panel data analysis?
I am currently working on my Master's thesis and for this I would like to examine the impact of the geographical location of Mutual Funds on their performance. For this I have panel data of mutual ...
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Reusing reg model for panel data
When running panel regression, I have multiple equations with shared independent variables, control variables, and dependent variables, but different sets of interactive variables.
For the main model, ...
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Difference between left censoring and interval censoring
I'm dealing with some medical data which is made up of all admissions to hospital in a certain area, where each row is one patient admission alongside the various tests and demographic data done. Also ...
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Different amounts of observations for individuals - Which model to use?
I have a dataframe which is structured in a way, that it includes a different amount of observations (trip chains) for each person. A trip chain consists of all the trips an individual took from ...
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Estimating treatment effect using panel data and absorbing binary treatment
I have a panel dataset of a large N and T = 24. I want to estimate the effect of a treatment (in this case, taking on a certain type of credit product) on Y which is an individuals credit score. I ...
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Dynamic panel data model with treatment
Consider a simple dynamic panel model with a single lag: $$y_{it} = \alpha_i + x_{it}'\beta + \rho y_{i,t-1}+\epsilon_{it}$$
Now assuming that $x_{it}$ is most ordinary covariates, this can be ...
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Matched panel data regression in R: clustering on three dimensions (firm_id, year, matching value) with plm package
I'm new to working with panel data in general. While I work with R my coauthors work with Stata. So naturally, I'm running into problems that they can't relate to but I also can't fully explain them ...
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How to include random effect to ivreg model in R?
I have an endogenous variable X with instrumental variable Z and want to predict outcome variable Y. For this I have longitudinal data with user_id. Currently my model is:
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How to test for effect modification and mediation by time-varying factors in a longitudinal context?
I have longitudinal data with measures of an exposure, outcome, variables that may be mediators or effect modifiers, and confounders at 3 time points. I would like to account for time-invariant and ...
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Invariance coding for running a latent growth model running under partial (scalar or metric) invariance
I am running a second-order latent growth curve with 7 time points.
The model has a four indicator latent variables at the measurement level so I ran a longitudinal invariance test.
The model holds ...
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Cross mixed effects model in R as a Mathematical Formula
Mixed effects models(MEM) can be nested or crossed. For crossed models specifically, how would the below R code look as a mathematical formula in an academic paper? There are multiple random and fixed ...
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Why are lags of the dependent variable a no-no in traditional random effects models?
This post says:
Lagged versions of the dependent variable are a no-no in traditional random effects models. The problem is that they are correlated with the random intercept and produce inconsistent ...
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Multivariate Longitudinal Multi-level Model: What is the hierarchy structure?
I am interested in running a multivariate multi-level model with longitudinal data, and I'm having a hard time conceptualising the hierarchy levels.
My variables are:
Multivariate outcome: Quality of ...
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How to keep time-varying but entity-invariant variables in a panel regression fixed effects model?
I am working with a panel dataset that spans 2000Q1 to 2020Q3 and captures quarterly capital flows to 35 different Emerging Market Economies (EMEs). Along with the capital flows data, I have several ...
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Event-study with continous treatment in R using fixest
I have a panel dataset with "id", "year" (1970 to 2000), and "post" a dummy which takes a value=1 if year > 1985. The treatment variable ("treatment") is a ...
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Why are FGLS standard errors so low when estimating linear regression on panel data?
I am currently writing my master thesis an the effect of academic publication on anomaly returns. The idea is that in finance literature anomaly - factors/portfolios are proposed. After the factor is ...
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Are there any viable alternatives to linear mixed models when the independent (predictive) variable lacks follow-up data?
I am attempting to conduct a longitudinal analysis on a dataset with one independent variable and five dependent variables. We aim to determine whether the independent variable can predict changes in ...
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Longitudinal, repeated measures, multivariate meta analysis
I am trying to carry out a meta analysis with proportions in which I calculate the % of patients
with response and/or remission (measured with the same scale) to a treatment at determinated time ...
