Questions tagged [time-varying-covariate]

A variable that records something about a study unit in a longitudinal study that changes over the course of the study.

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10
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2answers
237 views

Test if people drop out or decrease bets after repeated losses

I have data on a series of winning and losing bets over 5 rounds of betting with attrition after each round. I am using a decision tree like the following to display the data. The nodes towards the ...
9
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1answer
3k views

How to generate survival data with time dependent covariates using R

I want to generate survival time from a Cox proportional hazards model that contains time dependent covariate. The model is $h(t|X_i) =h_0(t) \exp(\gamma X_i + \alpha m_{i}(t))$ where $X_i$ is ...
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4answers
1k views

Is there a way to allow seasonality in regression coefficients?

Say I have a time series, Gt, and a covariate Bt. I want to find the relationship between them by the ARMA model: Gt = Zt + β0 + β1Bt where the residual Zt follows some ARMA process. ...
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1answer
7k views

How to use time dependent covariates with cox regression in R

I don't know how to generate time dependent covariates in R for use cox regression. I know you need to reorganize your dataset into intervals between event times. This I believe I can do with the ...
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2answers
1k views

Time Varying System Matrices in Kalman Filter

Kalman filter can accommodate time varying system matrices. Equations to run the filter are the same and it preserves its optimality under linear gaussian model. My question is the following: Can ...
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2answers
707 views

Does the proportional hazards assumption still matter if the covariate is time-dependent?

If I estimate a Cox Proportional Hazards model and my covariate of interest is dependent (continuous or categorical), does the proportional hazards assumption still matter? I recently went to a ...
5
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2answers
506 views

What Survival Analysis Model Should I Use?

I'm sorry if this question is too broad for this board. I'm trying to figure out a survival model for my data. Right now I have it organized by country, year, "cur" which is my main IV, and event. I ...
5
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1answer
60 views

Ways of modeling the same variable as both a time-invariant and time-varying predictor

This question has been asked and not answered before here. I am building a model attempting to predict heroin use over time in patients based on their use of amphetamine-type substances (ATS). ATS ...
5
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1answer
651 views

Testing residuals from a cox model with time dependent covariates

I'm doing survival analysis with time dependent covariates, using the counting process style. I already have a set of models and I want to test de residuals. I'm having trouble with the lack of ...
5
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1answer
678 views

interval censored survival analysis with time dependent covariates

I'm working on a long-term, large tree data set from Africa. I have data on the same set of individuals from year 2006, 2008, 2011 and 2015. The data consist of tree status (alive/dead) at each time ...
5
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1answer
950 views

Time varying predictors at higher aggregation levels in multilevel survival analysis

The case: I am trying to estimate event history models (also known as survival models) with time-varying predictors at two different levels of (geographical) aggregation. More precisely, I am using a ...
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0answers
247 views

Ensemble learning with time-varying covariates and effects

We are interested in replicating several duration studies in the literature using ensemble learning methods. After some experimentation, we opted for random survival forests (Ishwaran et al. 2008) for ...
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2answers
343 views

Does the Cox proportional hazards model process past values for time-varying covariates?

I am currently working on a survival analysis project and am struggling regarding the inner workings of the coxph function of the ...
4
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2answers
289 views

Does an accurate “noise” model help when using a Kalman filter?

I've been trying to use a Kalman filter to estimate slope of a line (this is a simplified version of my problem for discussion). So basically time-varying regression. State Equation: $$ \left[\begin{...
4
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1answer
2k views

Time-varying Coefficients

I have time series data on fish catches from 1950-2011. I wish to implement a regression model with varying coefficients. I'm aware that cox models etc. exist and implementation via the ...
4
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1answer
2k views

Extended Cox model with continuous time dependent covariate - how to structure data?

I need to run an extended Cox model with a time-varying covariate in R: let’s call it the "number of doses" (X). I am interested in the hazard ratio associated ...
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0answers
131 views

Time varying (auto)correlation estimation

I would need to estimate a time varying autocorrelation of a variable. Do you have any references or examples? I've tried to search for a package in R but I wasn't ...
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2answers
2k views

How to make predictions with time-dependent covariates with Cox regression

I learned about time-dependent covariates in Cox regression in R using the function survSplit of the package survival. I use this as an interaction term for covariates which do not follow the Cox ...
3
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1answer
630 views

Main effect required for time-varying covariate?

I'm modeling a multivariable proportional hazards model (competing risks), and I want to include an internal time-varying covariate. Should I include a main effect for this time-varying covariate in ...
3
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1answer
160 views

How to solve a classification problem when the independent variables/covariates/feature vectors form a time series?

Say we've a time indexed sequence of feature vectors/covariates/independent variables $x_t$ at time $t$. Say also we've a corresponding time indexed sequence of variates/dependent variables $y_t$. Now ...
3
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1answer
4k views

Determine if a time-dependent Cox model is appropriate

Before the description, here are my questions (1) Is the set-up of my time-dependent data correct? (2) Are the ways I run my Cox proportional hazard model with a time-dependent variable/ non time-...
3
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1answer
760 views

Schoenfeld residual test for model with time varying coefficients?

I'm working with the survival package in R. I fit a Cox proportional hazard model (coxph) and did a scaled Schoenfeld residual test (...
3
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2answers
980 views

Time-dependent variable in survival analysis using R

I am conducting a retrospective study where I have a cohort of cases who underwent the same surgical procedure. The primary outcome of the study is the recurrence incidence rate during a follow up ...
3
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1answer
108 views

Is series cointegrated if residual is stationary under time-varying coefficient regression?

Traditionally, if $x_t$ and $y_t$ are both $I(1)$, they are cointegrated when there exists some linear combination $z_t=y_t-$$\gamma$ $x_t$ such that $z_t$ is stationary or $I(0)$. My question is if ...
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1answer
92 views

Time dependent variable in survival analysis using Cox regression

Trying to determine how to analyse a time dependent variable (rainfall) in a survival analysis. Two rows of example data for animal A and animal B as below: Each value next to the animal represents ...
3
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1answer
107 views

Latest development in online learning and causality inference

The context is this - I'm considering doing a part time PhD in statistical learning and today I've met up with a prospective supervisor who suggested that I think about causality in machine learning ...
3
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1answer
378 views

Do multiple observations per individual imply pseudo-replication in time-varying Cox proportional survival model (coxme in R)?

I’m running a survival analysis using a cox mixed-effect proportional hazard model with time-varying covariates (using package and function coxme in R). My ...
3
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1answer
2k views

Which is the best graph to describe a survival analysis with a time-dependent covariate?

I am analyzing a randomized trial, and aiming at appraising the impact of a given treatment on a non-fatal outcome, followed occasionally by death. I am thus conducting an event-free survival analysis ...
3
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1answer
2k views

Time-dependent coxph output and making predictions in R

I'm trying to use a Cox proportional hazard model to predict the time until an employee terminates from an organization. There are a bunch of covariates (~20), some of them time-dependent. So I've ...
3
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1answer
101 views

Interpretation of functional regression models for scalar response

I have an application scenario in which I want to determine a single outcome from the course of a series of measurements. I decided to give functional regression a try, so I read and ran the example ...
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0answers
59 views

What plots and summary statistics are usually used for exploratory data analysis of multivariate time series? [closed]

For multivariate cross-sectional data, tools such as scatterplot matrices, the five numbers summary, faceted boxplots and so on, allow an efficient exploration of a new data set, and can suggest how ...
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2answers
149 views

Predicting recidivism for male prisoners [closed]

The following question takes ground in the this example with time varying covariates. The following code will read data from a url, parse it to the right format (allowing for time varying covariates) ...
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0answers
35 views

Modeling true number of sales based on reported number of sales

I have a sequence of numbers of quarterly sales spanning a decade, say $\{Z_i; 1\leq i \leq m\}$. These numbers are not observed until much later. I do have incomplete observations of this sequence ...
3
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0answers
116 views

Time varying covariates and Interpolation issue

Based on my reading on time-varying survival analysis, I am encountering two different and conflicting sets of advice with regards to time-varying covariates and interpolation. The first advice is ...
3
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1answer
94 views

How do I model the variation over time?

The data: Each year, during the months from January to July, a select number of plants had a certain "thing" measured. Each month, this was done almost every day for some plants, and maybe weekly or ...
3
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0answers
588 views

Interpretation of scaled Schoenfeld residual for time dependent coefficient

https://cran.r-project.org/web/packages/survival/vignettes/timedep.pdf I've been following the vignette on implementing time dependent coefficient in addressing non proportional hazards in a cox ...
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0answers
100 views

Are interactions between continuous predictors a problem in mixed models?

I am interested in the effect of within-subjects treatment Z (two levels) on my dependent variable Y (which is measured under various conditions). I measured Y at the start of the experiment as a '...
3
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0answers
155 views

Survival analysis with time dependent covariates and cured fraction

I have a problem specified in this way, I'll make a fictional example, because the actual data requires quite a bit of domain knowledge to be understood. There is a series of newborn babies (let's ...
3
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0answers
335 views

What are the independence assumptions of Cox models with time varying covariates?

In longitudinal studies, you might be observing time-to-event endpoints with some covariate that changes as a function of time. When covariates are fixed at baseline, the only independence assumption ...
2
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2answers
70 views

Including Time Invariant Covariates in a Random Intercept Model

Let us say we have a random intercept model for $n$ individuals $$y_{i,t} = x_{i,t}'\beta + \alpha_i + \epsilon_{i,t} \hspace{35pt} i = 1,...,n$$ where $x_{i,t}'\beta$ is a set of time variant ...
2
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3answers
381 views

Can we perform matching on post-treatment variables?

I want to match followers of some seed accounts with some random users on Twitter based on observed covariates using the coarsened exact matching method. My goal is to test whether following those ...
2
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3answers
2k views

Proportional hazards assumption and time-dependent covariates

Is there a way to check that the proportional hazards assumption is correct for a Cox model with time-varying covariates ?
2
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2answers
2k views

DLM package, issues about specifying models with time-varying coefficient

I've been working on DLM package for the past few weeks. I've read the package manual and the paper written by Petris "dlm: an R package for Bayesian analysis of Dynamic Linear Models", but I am still ...
2
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1answer
33 views

How to control for within-subject covariate in a single-arm, mirror image study design?

I have a mirror image study which consists of one group of subjects, and they have a measure before and another measure after an intervention. Depiction: Single group: Measure#1 -> (Intervention) ->...
2
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1answer
84 views

Interpretation and Prediction in Longitudinal Models with an Interaction between a Time-Varying Predictor and Time Itself

I am trying to develop my intuition about how to interpret an interaction between a time-varying predictor and time itself. I have several years of routinely collected outcomes data from a drug and ...
2
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1answer
50 views

Interaction of Time-Varying Predictor and Time: How its inclusion changes the meaning of coefficients

I am interested in how an interaction between a time-varying-predictor and time changes the interpretation of other coefficients in a model. I am modeling the effect of amphetamine-type substance (...
2
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1answer
167 views

Repeated measures mixed model correlation between measurements

I am interested in looking at the correlation between two types of heart function measurements over time. test1 can be considered the true value. The true value (<...
2
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4answers
551 views

Regression model with time-varying covariates and fixed y

I want to fit a logistic regression model for discriminating between two groups (Control and Cancer) and one of my covariates is measured in five different times (it's a curve with concentrations of a ...
2
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1answer
739 views

Formatting data for Cox PH with time-dependent covariates

I was hoping for some guidance on the appropriateness of my modeling approach to the following problem. Problem: I'd like to know whether the days receiving nutrition support (cumulative days on ...
2
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1answer
498 views

Event Prediction With Time Varying Covariates

I work with learning and predicting events (of various kinds) in time and space. The data is completely observable without censoring. Even so, survival analysis is a useful tool to learn a ...

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