Longitudinal data consists of data that are collected repeatedly on the same subjects. When there is a long series of data, time series analysis may be appropriate. For shorter series, mixed models (aka multilevel models) may be appropriate.
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387 views
Is there an R package for continuous time longitudinal binary responses?
The bild package appears to be an excellent package for serial binary responses. But it is for discrete time. I would like to specify a smooth function of time ...
2
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1answer
254 views
Repeated measures ANOVA
I have to apologise about my lack of experience but hopefully someone can clarify things for me.
I am interested in looking at change in psychosocial functioning over time and compare it between ...
2
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0answers
33 views
Clustering longitudinal (trajectory) data
I am hoping to implement an unsupervised technique that identifies distinct clusters of individuals based on longitudinal data: 100 continuous or categorical variables measured at different ages.
A ...
2
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0answers
49 views
Structural equation model with very small samples
I have two sets of a longitudinal data that I hypothesize to measure same latent construct.I am trying to test this hypothesis using Structural equation modelling technique. Basically, I am trying to ...
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1answer
44 views
Is there a statistical model for modelling variables that are measured in varying amounts and in different time points per individual?
I have been trying to model a dataset of variables where each individual is measured a different number of times, and on different point in time. Most of my variables are count, but some are not (the ...
4
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1answer
81 views
SVM regression with longitudinal data
I have about 500 variables per patient, each variable has one continous value and is measured at three different time points (after 2 month and after 1 year). With the regression I would like to ...
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1answer
173 views
How to model repeated measures with time-varying covariates in SPSS?
I wanted to test the effectiveness of a particular type of "talking" therapy on depression. I envisaged selecting ONE group of people and measuring their heart rate and scores on depression scale for ...
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1answer
41 views
How to predict the time gap between two conditions
Could anyone suggest the best method to predict the time gap between two events, e.g., given that diabetics are at higher risk of developing hypertension, I would like to predict the time gap for the ...
4
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1answer
151 views
What is an acceptable value of the Calinski & Harabasz (CH) criterion?
I have done a data analysis trying to cluster longitudinal data using R and the kml package. My data contains of around 400 individual trajectories (as it is called in the paper). You can see my ...
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1answer
162 views
Moderation in repeated-measures design?
Context: Both dependent $(Y_1,~Y_2,~Y_3)$ and independent $(X_1,~X_2,~X_3)$ variables were measured repeatedly at three time points, $\text{Time}_1$, $\text{Time}_2$, and $\text{Time}_3$. Moderator ...
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2answers
172 views
Plotting and presenting longitudinal data, options?
Hypothetical Scenario: A few continuous variables, each measured repeatedly at, say 12 time points, each with say, 150 observations. There are small fluctuations from one time point to another (i.e. ...
2
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1answer
115 views
Modelling longitudinal data
We have longitudinal data on children(n<20) in which we measure different quantities A,B,C,D (like distance walked, time spent in school etc.). These are all continuous variables. We measure these ...
12
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2answers
483 views
What are the differences between “Mixed Effects Modelling” and “Latent Growth Modelling”?
I'm decently familiar with mixed effects models (MEM), but a colleague recently asked me how it compares to latent growth models (LGM). I did a bit of googling, and it seems that LGM is a variant of ...
4
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1answer
343 views
Multiple regression with repeatedly measured independent variables?
Design and hypothesis: we measured wellbeing at Time-1 and Time-2, we want to see whether factor A (measured at Time-1 and ...
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0answers
135 views
Interpretation of interaction and main effect in a mixed model when one is significant and the other is not
I have repeated (x4) measurements on 90 subjects. The outcome is zero inflated.
The model output gives these estimates:
...
0
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0answers
37 views
Time series analysis for disease management
I am trying to do time series analysis to see the management of diabetes in the country. I am taking mean of blood glucose measurement recorded in the labs country wide by the patients in every month. ...
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2answers
40 views
Repeated categorical measures in a survey
Last year, we did a survey that asked people a question about their belief in climate change. The respondents could select 1 from a list of 5 categorical responses.
In the fall, there was an event ...
2
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2answers
88 views
“weird” results from multilevel analysis
I am examining the effect of a group variable (with five levels) along with other predictors on achievement growth using SPSS Mixed Model. The descriptive statistics showed a consistent pattern on ...
2
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1answer
141 views
Regression with 3 measurement points (in R)
I have a regression in which I try to understand how much variance of the metric dependent variable each of the regressors explains. I use the package R relaimpo (Grömping, 2006) for that purpose, ...
2
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0answers
81 views
Nested repeated measures analysis
I have a nested repeated measures question. I have 20 individuals grouped into 5 families. For each individual I have measurements on subsequent days pre, during, and post-treatment for a total of 6 ...
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184 views
How to specify in r spatial covariance structure similar to SAS sp(pow) in a marginal model?
I'm currently translating existing code from SAS to R. I'm working on longitudinal data (CD4 count over time). I have the following SAS code :
...
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46 views
NLME regression & curve comparison
I have two groups (patients & control) and each person was measured 3 times.
I use the nmlefitsa function of MATLAB for doing a regression over time for these ...
1
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2answers
64 views
Testing interaction b/t group & longitudinal change for only part of the age range
I've fit a mixed linear model to some longitudinal data. I'm interested in the differences in patterns of decrease in the dependent variable according to group status, and my hypothesis particularly ...
2
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1answer
69 views
Effect of varying outcome duration in longitudinal studies
I have a supervised classifier model (regularized discriminant) which predicts the probability of an event occurring within two years.
This model was developed using sensor data measured from a ...
1
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1answer
159 views
The test procedure of significant differences in count data over time
The data below are from a health testing centre over 8 years so there are different people being tested there each year. All I really want to show is that the amount of females being tested is ...
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3answers
282 views
Identifying the time lag between cause and effect
What approaches exist to observe the time lag between two variables?
I need to analyze the relationship between blood pressure and some other factor, such as exercise. The data set I am drawing from ...
2
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1answer
77 views
A good summary measure on analyzing repeated measures of longitudinal data?
I have an interesting question on longitudinal data and I'm looking for a proper summary measure that enables me to answer my question of interest without knowing/using anything about correlated data. ...
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2answers
204 views
How to do time series ( longitudinal) clustering based entirely on Shape of the curves?
I have a longitudinal (panel) dataset for investment growth for 120 countries covering the time from 1960-2008. Essentially it's viewed as 120 time series.
What I am interested in is to group ...
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2answers
797 views
Longitudinal data: time series, repeated measures, or something else?
In plain English:
I have a multiple regression or ANOVA model but the response variable for each individual is a curvilinear function of time. How can I tell which of the right-hand-side variables ...
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3answers
3k views
What is the difference between using aov() and lme() in analyzing a longitudinal dataset?
Can anyone tell me the difference between using aov() and lme() for analyzing longitudinal data and how to interpret results ...
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41 views
Looking for pointers on how/if to model a “low t and high n” longitudinal data set to evaluate outcome-predictors
Say you have a longitudinal data set with 5 measurement points, which begins at 200-300 participants and declines to about 50. There is an intervention between time-point 2 and 3. There's 3 continuous ...
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1answer
126 views
Time series from experimental measurement
I've got a couple of time series obtained from a small number of replicates,where many variables (all of them continuous) are measured at various time points (longitudinal study). I was looking for a ...
3
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1answer
178 views
Interpreting the change in random effect variance over time in a GLMM
I am measuring the change in random effect (random intercept) over time by running models such as
...
6
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1answer
166 views
How to analyze GEE with unevenly spaced observations?
I am interested in using Generalized Estimating Equations (GEE) to model longitudinal count data. I recorded animal count observations on the same sites on many days but the spacing of the ...
2
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1answer
184 views
Is there a software package to fit grouped (aggregated) logistic panel regression models?
I have a dataset that looks like the following
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3answers
449 views
When is it appropriate to pool data?
Let's say I have some data on the amount of money spent on tv ads and total revenue from all sales. The data is available for three separate month.
...
3
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3answers
260 views
Mixture model fixed effects
One standard model used with panel data is fixed effects: $y_{it} = \mu_i + \theta_t + \epsilon_{it}$, where $i$ is the individual and $t$ is time subscripts. This can be estimated easily with OLS and ...
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31 views
Labeled multidimensional sequences
I'm trying to find similarities in 3-dimensional sequential data.
The sequences are 3-uples $(t,r,d)$ each sequence is generated by one subject during a 3-6 months period:
$t$ is a task ...
2
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2answers
268 views
repeated measures regression
I was hoping that I could get some feedback in terms of keywords I should searching for, or concepts I need to consider with the following:
I have non-experimental data that I would like to model in ...
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0answers
57 views
Inferential methods on large panel data with sparse clusters and rare outcomes
Using longitudinal survey data on children using psychotropic medications, we are interested in estimating associations with medication classes, their persistence and adherence (longitudinal ...
2
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0answers
238 views
How to impute data without missing at random?
Recently I got a global longitudinal data from several countries, and each county has one outcome variable and two predictors from 1995 to 2008. I found one of the predictors is always missing in each ...
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52 views
Clustering trajectory patterns with lot of missing values
Is there a problem looking for clusters of trajectory patterns in longitudinal data, when much of the longitudinal values were imputed from the baseline data?
8
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1answer
5k views
How to interpret variance and correlation of random effects in a mixed-effects model?
I hope you all don't mind this question, but I need help interpreting output for a linear mixed effects model output I've been trying to learn to do in R. I am new to longitudinal data analysis and ...
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3answers
604 views
Longitudinal models in R and WINBUGS or JAGS
I've tried to use R to fit some longitudinal models, mostly via lmer and nlme packages. However, it seems that many standard ...
6
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3answers
511 views
Repeated measures structural equation modeling
I need to analyse a dataset of clinical rehabilitation data. I am interested in hypothesis-driven relationships between quantified "input" (amount of therapy) and changes in health status. Although ...
1
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2answers
178 views
Clustering of stock market returns
I am trying to cluster the companies listed in a stock market on the basis of the risk and returns.
I have about 100 companies (categories) and two variables (risk, return) under each category. The ...
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2answers
117 views
Is this a valid approach to testing a hypothesis about the relationship between two variables?
I am trying to test a hypothesis I have about consolidation in the real-world market for a certain machine. (My apologies in advance for obfuscating a bit here, but some of the data is proprietary and ...
9
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3answers
1k views
R/Stata package for zero-truncated negative binomial GEE?
this is my first post. I'm truly grateful for this community.
I am trying to analyze longitudinal count data that is zero-truncated (probability that response variable = 0 is 0), and the mean != ...
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0answers
221 views
Logistic regression with longitudinal data
I have longitudinal data (one measurement being continous and the other ordinal) and I want to fit a model which takes into account the correlation between these two measures. I am using stata. Can ...
6
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0answers
601 views
How to analyze longitudinal count data: accounting for temporal autocorrelation in GLMM?
Hello statistical gurus and R programming wizards,
I am interested in modeling animal captures as a function of environmental conditions and day of the year. As part of another study, I have counts ...
