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Questions tagged [longitudinal-data-analysis]

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How to compare age-distributions across years within longitudinal datasets?

I'm a bit uncertain and I would be very grateful for some assistance. I have a longitudinal dataset of patient medical records between 2000 and 2016. These records contain clinical event dates and ...
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27 views

Using longitudinal income data to predict cross-sectional outcome measure

I have the following data: income data measured yearly from 2004 to 2011 in households occupied by adolescents a single variable denoting households where parents have divorced (divorced vs non-...
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Does lifestyle index score mediate relationship between cognition and biomarkers

I am wanting to calculate a lifestyle index score for participants (based on various variables relating to health beahaviours and diet). I will also measure 1) cognitive performance and 2) bio ...
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What machine learning and deep learning models are used for longitudinal studies (panel data)?

As the title suggets, 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 ...
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How to do longitudinal analysis of random timepoints of data

I'm attempting to do a longitudinal analysis from a dataset collected over a multi-year period, to explore time-of-year effects. The dataset has ~1600 subjects who have data for at least two time ...
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2answers
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Is the panel (PLM in R) approach appropriate when observations within panels vary in location and number between time steps?

Setup: We have 10 connected but distinct wetlands within a study area. The wetlands are not totally independent, there is some exchange of water and organisms between them. Perhaps comparable to ...
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Pre-whitening longitudinal MLM

I am conducting longitudinal multilevel models (Level-1 = Daily observations; Level-2 = PARTICIPANT). Predictors and outcome variables are measured every day. Do I need to pre-whiten my data (and why)...
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6 views

The function of TIME in longitudinal MLM

I am conducting longitudinal multilevel models with Daily observations as level-1 variable and PARTICIPANT as level-2 variable. Predictors and outcome variables are measured every day. I am confused ...
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16 views

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 ...
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panel IRF and FEVD from panel vector autoregression in r

The package panelvar in r can estimate panel vector autoregression models. It can also produce IRFs and FEVDs the aggregate endogenous variables. How can I get IRF and FEVDs for panel units/...
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13 views

Model for missing data at baseline?

I am interested in looking at the effects duration of a certain medicine has on an outcome over time assuming the effects to be nonlinear. Some people would have baseline data of before starting ...
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23 views

How to plot disease incidence within an individual over time

I have a longitudinal cohort of patient medical records, events of drug and clinical intervention are defined by a code and a date. There is no definition for remission or relapse. I would like to ...
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interpreting HLM coefficients

I have created the following model of longitudinal observations in HLM7: ...
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23 views

Logistic regression using Longitudinal Data

I want to know the factors affecting stunting status among children. My data was taken from year 2003 data and the same children in year 2011. So my data was a longitudinal data. I want to know which ...
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1answer
40 views

Unbalanced longitudinal model with lmer

I would like to asses the treatment effect on blood hormone concentration. Data are collected in 10 centers, at 4 time points (0,6,12,and 18 months). However four centers used both treatments a and b, ...
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3answers
121 views

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 ...
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13 views

Standardised effect size and CI for non-independent longitudinal data in a linear mixed-effect model (LMM)

I would like to calculate standardised effect sizes with confidence intervals for fixed effects in a linear mixed effect model (LMM) for data that have an unbalanced repeated measures longitudinal ...
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1answer
69 views

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 ...
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1answer
27 views

Can you compare average differences over time as an alternative to mixed models?

I have data that looks at the rate of crime for four countries over a three year time period. I would like to see whether the rates per 1000 people for each country are significantly different from ...
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1answer
22 views

Are direct effects between latent variable indicators ever appropriate?

I have a longitudinal structural model regressing 1 endogenous latent variable at Time 2 on 4 exogenous latent variables at Time 1. The modification indices in Mplus suggest including a direct effect ...
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1answer
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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 ...
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1answer
44 views

Propensity Score Matching over time?

I have two surveys of households in the same metropolitan areas about the number of transit trips they took. I would like to compare the change in number of transit trips taken by households, between ...
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2answers
35 views

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 ...
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0answers
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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 ...
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14 views

Longitudinal sequence of observations to predict a single target

So we observe a population every month and observe set of features $X_{month}$ number of features monthly $X_{Mar,2018}$, $X_{Apr,2018}$ and we want to predict the end-of year value $y_{2018}$, which ...
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1answer
125 views

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 ...
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15 views

Longitudinal Study with variable sampling periods

I came across a dataset of a longitudinal study that has the following characteristics: Participants enter at any time in the study They can exit the study at any point for various reasons but cannot ...
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1answer
64 views

How to control for age in analyzing longitudinal data using mixed effects regression

I am analyzing a longitudinal dataset. Elderly subjects perform a cognitive test once a year, for five consecutive years. I want to know if there is a decline in their performance through the study ...
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24 views

Model subgroup- and covariate-specific effects for binary outcome over time

I am currently planning an analysis, in which I try to separate the change in the level of a binary outcome into a subgroup- and a covariate-related effect. Let's say there are three kind of ...
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2answers
19 views

Combine longitudinal data to increase power?

I have a set of data of ~13 people. We collect their data every 2 months for 2 years. I'm interested to see if a variable A in the data affect people's performance as well as their growth rate. So ...
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7 views

What model should I use for a longitudinal analysis of an index (0-100)?

I have a longitudinal survey (5 waves) that collects a health index (from 0 to 100) and some risk factors and socioeconomic characteristics. I want to develop a model that will predict this health ...
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1answer
137 views

What is the main difference between GLM and GEE?

From my understanding, glm(not glmer) and GEE both handle binary values. But GEE is a marginal model and glmer is a random effects model (mixed model). So then what is the main difference between GLM (...
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1answer
61 views

What is the impact of unbalanced longitudinal data?

I'm quite new to the concept of correlated data still, and I was have a few questions about unbalanced longitudinal data. Let's say we are using a linear mixed model: 1) what is the impact of not ...
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29 views

What do my mean and standard deviation tell me?

I have American State level unemployment rates in 3 waves of longitudinal data. When I describe unemployment rates for my descriptive table I get the following: ...
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1answer
22 views

How can I analyse repeated cross-sectional data where some respondents occur in multiple cross-sections?

I'm working on a project with a polling company. I have access to some of the micro-data from their voting intention polls. I'd like to link these to GDP figures to test how economic change affects ...
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1answer
24 views

Single DV with repeated/clustered measurements of IV

I have an analytical dilemma wherein I have a single DV with multiple categorical and continuous IVs (one of which is a continuous IV that has multiple measurements across time). I'm not sure the best ...
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1answer
41 views

Random effects specification in modeling panel (longitudinal) data

I am fitting a negative binomial model with mixed effects on a dataset with repeated measures in time. Each observation is a province-year combination, meaning province 1 year 1, province 1 year 2, ......
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1answer
55 views

Is Repeated Measures ANOVA appropriate for flower production over time?

I wanted to check here to see if a repeated measures ANOVA would be a good option to analyze my data, or if you have any other suggestions? I have read that GLMM is another option for time series data,...
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1answer
271 views

R lmer, 3 time point longitudinal data, non linear, messy residual help!

I am new to mixed models so please go easy on me! I am attempting to longitudinally model a normally distributed continuous outcome with values in my dataset from -30-10. I have data collected at 1, ...
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2answers
22 views

NPS daily survey data

I have daily surveys sent to users of several of my organization´s services, the surveys consists only on NPS question (How likely would recommend X? on a 0 to 10 scale), number of respondents vary by ...
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How to correctly plan for Missing Data in Longitudinal / Repeated Measures Design?

Using an hierarchical questionnaire for a longitudinal study, I face strict constrains in how many items can be processed by each subject per week. The questionnaire contains 51 Items in total, but ...
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2answers
146 views

Time series analysis - Seasonal variation problem [closed]

I am having trouble with taking out seasonal problem in the data. If you see the picture, the error messg saying "non-numeric argument to binary operator". How should I fix this problem?
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95 views

K-means clustering for longitudinal data with fixed effects or other non-time dependant covariates

I am looking to run a k-means clustering analysis over some time series data and am currently using the kml3d package with three different variables that have been repeatedly measured over 3 weeks. ...
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1answer
20 views

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 ...
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0answers
14 views

covariance of longitudinal measures under random intercept/slope model

I am considering a model where I have repeated/longitudinal measures over a number of timepoints from baseline (probably evenly spaced - perhaps with 2 groups) and I assume a random intercepts and ...
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32 views

How can I conduct meta-analysis on longitudinal data?

Meta-analysis is a good way to synthesize data from multiple studies. Is it possible to conduct meta-analysis which contains a number of datasets, including longitudinal data (data was measured on the ...
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1answer
215 views

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 ...
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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....
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Can total least squares be used to account for uncertainty due to measurement timing?

Suppose we have a dataset in which we wish to perform regression analysis, and where the response/dependent variable is a measurement at time T. But due to pragmatic sampling we do not have ...