Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [longitudinal-data-analysis]

60 questions
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What machine learning and deep learning models are used for longitudinal studies (panel data)?

As the title suggests, I have a longitudinal database (also called panel data). (I have over 100.000 observations. The time period is X years. This means that for every year I have the values of the same variables. So I can see how every variable…
Cedric Standaert
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How to split longitudinal data into training and testing sets

I'm trying to model the likelihood a customer will be delinquent on their loan by next month based on their most current data at the time. Currently, I have longitudinal data and am having some trouble understanding the correct way to split my data…
rayven1lk
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How to account for temporal autocorrelation in logistic regression with longitudinal data?

I am attempting to perform a logistic regression on longitudinal data (game camera footage of nesting birds, with a photo taken every 5 minutes for a period of 10-28 days, depending on whether the nest was abandoned part way through the nesting…
C.H.
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Simulate longitudinal, curvilinear, convergent data in R

I would like to simulate data that is similar to a few given observations of longitudinal data (28 measurements per unit) in two groups (see below). The distribution of initial values could be normal or lognormal, and the two groups converge on…
caracal
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Centering in longitudinal linear mixed modeling - center by participant mean, timepoint mean, or participant by time grand mean?

EDIT: I was incorrectly looking to center my outcome variables. Only center predictors, and decide on group mean or grand mean centering by how you want to interpret your intercept. I have 150 participants with 7 repeated-measures each that are…
Craig K. Van Pay
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How much of a problem are autocorrelated residuals of a binary GAM (Generalized Additive model)?

I'm trying to predict high or low crime rate in municipalities (binary 1/0 response variable) using a range of socioeconomic variables. Im doing this with a panel dataset with 300 municipality over 17 years (2006-2016). To be more specific I train…
Niltzable
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Estimating the effect of different histories of exposure, on a scalar response measured at the end of a study

I have a cohort of $N\approx 20000$ subjects, for which a continuous variable (blood pressure) was measured at the end of a study spanning 5 years (so I have one value of blood pressure for each subject). Also, for each subject I have a time series…
Gux
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Can I use a mixed model even when my independent variables are all fixed effects?

I need to use longitudinal data for my model. Two possible options to deal with the lack of independence between observations: GEE and Mixed models. But, how Mixed model can even be an option if all my potential explanatory variables are fixed…
Magkey
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Must a subject participate at least twice to be considered in longitudinal analysis?

I am currently analyzing longitudinal data that was repeatedly measured (four times) but 1000 participants were lost to follow up after the first survey. Shall I include or exclude these participants in the longitudinal analysis that have only…
Eshetie Dres
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Meta-analyzing rates of change in one variable observed in one group over time

I'm working on a meta analysis of prospective studies assessing changes to mental health in the year following an event. For the purposes of example, say it's the prevalence of major depressive disorder (expressed as a proportion) and the severity…
Emily
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Three way interactions for generalized linear mixed effects model and interpretation of post hoc comparisons

The data I am working on has three categorical variables and one continuous variable. I am using a generalized mixed effects model across four time points before and after administering a drug. The drug responses are modeled as: y ~ A * B * C +…
AMC
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What are the common methodology can be used to find the parameter of the fixed and random effect in a nonlinear mixed effect model?

Recently, I am doing some research about nonlinear mixed effect model. However, most of the time, they will just straight away use the R language nlme package and fit the model into it to get the result. Therefore, I am wonder what is the algorithm…
Ng WS
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Longitudinal panel data classification

My problem context specifically lies in churn modeling, where accounts have account-specific attributes (like industry, number of employees, etc), but also have longitudinal yearly data (product usage data, contract premium costs, etc). One example…
Jong Ha Lee
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In MIXED models for RM, is it necessary to include interaction effects between covariates and time?

I am currently analysing data of a cohort study where we try to model change in a dependent variable (say, academic grades) over three time-points based on a number of continuous independent variables. The change in grades occurs due to a single…
Haplorrhini
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Should grand-mean centering happen in long or wide dataset?

This seems like a simple question but I've been having a hard time finding an answer. In a long daily diary dataset where each day has a row, the person mean for a given level-1 variable is repeated in each row. As a result, if I were to take the…
Emily
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