All Questions
Tagged with predictive-models mixed-model
92 questions
2
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0
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35
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How to model data where an individual could be in more than one group within the data, but is more likely to only appear once?
I have multiple cohorts of patients with different index symptoms/events, and am looking to predict cancer risk for each separate cohort, including certain covariates of interest to see which ...
- 21
3
votes
1
answer
165
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How to use and interpret results from glmer() in R, when the predicted risks are lower than observed
I previously asked this question on stack overflow, but was redirected here.
I have a dataframe of patients, with an outcome of cancer flagged, and other variables to be used as covariates (around 20 ...
- 31
1
vote
1
answer
35
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GLMM for Inference vs Prediction
I am assessing cross-sectional repeated measures data using a mixture of linear mixed models (LMM) and Generalized Linear Mixed Models (GLMM). I see in various places that GLMM is used primarily for ...
- 135
0
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1
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56
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Advice Desired: Predicting US Tornado Counts Via Multi-Level Model
I wish you good health and the best in life (whatever that means for you in particular).
Context
I want to model aggregated (monthly) tornado counts in the United States for a question on Metaculus. ...
- 101
0
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0
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48
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Application of mixed-effects model for unbalanced sample size and repeated measures
In my experimental design I have 4 treatments, 3 replicates per treatment and 3 blocks. In each plot I measured whether a plant is infested or not ("Infestate" variable). This measure has ...
- 67
0
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0
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48
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predicting using only certain terms in a mixed-model regression via lmer or glmer via predict()
When using lm() or glm(), the predict.lm() or predict.glm() functions allow one to obtain predictions from the model using only a subset of the predictor variables, while setting the coefficients of ...
- 111
1
vote
1
answer
181
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inverse.predict for $lmer$ models in R [closed]
In $lm$ models in R it is possible to use inverse.predict for predicting input value given a output value. But I can't find code making it for $lmer$ models. Do there not exists code for that in R?
- 313
2
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0
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43
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How to solve MME [closed]
I have spent an entire day trying to figure out how to solve these mixed model equations without any luck. I am therefore reaching out to this community. The assignment is as follows:
Using the ...
- 21
1
vote
1
answer
76
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Mixed effects model for prediction
I have a dataset where I collected cortisol samples 3 times a day, for 3 days at 2 timepoints. I am interested in looking at changes in cortisol right after awakening, at 0 min after awakening, 30 min ...
- 35
0
votes
1
answer
96
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What type of predictive analysis should I use in R?
In my study, there are a continuous dependent variable (fluency scores) and a continuous independent variable as a predictor (anxiety scores). I also include some task conditions (e.g., simple vs. ...
- 1
0
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0
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195
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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 ...
0
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1
answer
160
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Interpreting linear mixed effect model results with log transformed dependent variable and log transformed predictor w/ normal predictors as well
I have a linear mixed effect model that I built using longitudinal country level data to help me predict TB incidence based on country level diabetes prevalence, HIV incidence, prevalence of ...
- 11
1
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0
answers
11
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Time-to-event prediction in the group with pre- and post-diagnosis records and the group without event occurrence as control
I study the triggering of the difficult form (ineffective two treatments) in patients with joint disease. In this retrospective study, we have collected the dataset of ~150 patients diagnosed with ...
- 21
1
vote
1
answer
812
views
Zero-truncated negative binomial model in glmmTMB predictions
I have a dataset of counts of a vocalisation per hour. I am interested in fitting a model to see if the count of the vocalisations of a given category per hour is effected by noise. My response ...
- 11
3
votes
1
answer
121
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What type of prediction model will be suitable in this case?
We have 100 subjects (A,B,C....) in total.
We took 2000 tissue
samples from each subject.
For each subject, we evaluated the outcome(PASS or Fail), but we only evaluated the outcome on the subject ...
- 445
0
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0
answers
37
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Prediction errors for OLS with unevenly distributed covariate
Suppose I have a simple OLS model for a covariate that is not evenly distributed. Is there a way to get a prediction error estimate that reflects that greater uncertainty for covariate values with ...
- 172
1
vote
1
answer
341
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How to make predictions from a GLMM model where the prediction space has fewer independent variables than were used to generate the model?
THE PROBLEM
I have a Generalized Linear Mixed Effects (GLMM) model that is relating counts of an organism to relevant environmental covariates. Once this model is generated, I intend to apply it to ...
- 164
2
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1
answer
42
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Can I improve linear model coefficient estimates using group information without working it into model?
I am fitting a linear model in order to predict future observations. The training data consists of about 1000 observations. Each observation comes from one of 10 individuals, which means I have about ...
- 376
0
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0
answers
44
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Modeling a binary outcome based on multiple predictor variables (when measures within subjects exclude one another)
The study design is as follows:
N subjects received MRI examinations. In a subset of cases, one or more sequences (i.e. separate “components” of the examination) were of insufficient image quality (e....
- 1
0
votes
1
answer
210
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Predicted values from a linear mixed model don't form a straight line even though no (higher order) transformations/polynomials have been specified
To assess if age is related to my continuous_outcome in my repeated measurements data, I've specified a linear mixed model with ...
- 149
1
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1
answer
42
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Searching for an authoritative answer about the implications of holding random effects to zero in predictions of mixed effects models
Let's say a large population was sampled, and data to construct a model to predict Y were gathered at part of the sample units. To account for correlation among individuals from the same site, ...
- 21
4
votes
1
answer
2k
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Predicting survival/event probability with multi-level Weibull model and time-dependent covariates
I am still a beginner when it comes to survival analysis. I have fitted a parametric (Weibull) survival regression model with time-dependent covariates using the R package flexsurv via:
...
- 97
1
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0
answers
514
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ggpredict random intercept logistic model: What does `ggpredict` actually predict? What does the manual mean by "population-level"?
In R, function ggpredict can be used to generate model-predicted values for a random-effect model, like a random intercept logistic regression model. For such model,...
- 1,918
3
votes
1
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204
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What statistics can be used to analyze and understand measured outcomes of choices in binary trees?
I am conducting biological research on animal behavior. There is an arena set up like a binary tree. End nodes are sources of food (e.g. smells) or stimuli that can mix. The animal (or a group of ...
- 31
2
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0
answers
23
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Method for Predicting Longitudinal Diagnostic Switching and Instability
Context
Within my field (neuropsychology), there is a well-known issue for some individuals to have very unstable diagnoses overtime. My area of interest is in dementia where the ideal diagnostic ...
- 836
1
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0
answers
240
views
Model to deal with multiple observations (prediction)
I want to predict how much time it will take to go from a place to another on a given week day (Monday, Tuesday,...), in a given time of the day(morning/evening).
My data looks like this (of course ...
0
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0
answers
89
views
Graph of model predictions vs observed data when testing a hypothesis
I have used mixed models to test a hypothesis and have checked residuals for normality. I was planning to graph the observed data and present it with model outputs (coefficients, p-values). However, ...
1
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0
answers
560
views
Should se.fit = TRUE in predict.merMod() be used, now that it is functional again?
I know the functionality of se.fit was removed from the predict() function in lme4 for mixed effects models a long time ago (due to not properly accounting for variations due to the random effects and ...
- 11
4
votes
1
answer
565
views
r Mixed model formula - help! (edited)
I am struggling with defining my mixed model formula and would love some help. This is a gene expression data where I want to see if each gene can predict Response — and I am comparing mixed model and ...
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3
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1
answer
744
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How does multilevel model make predictions for levels not in test data?
Multilevel models are able to make predictions for levels that are not in the test data, but I'm unsure why or how this is possible. Here's an example to illustrate where I use a test data set with ...
- 105
1
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0
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68
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4
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2
answers
96
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Dealing with groups of high dimensional data
I've got a dataset that follows patients who underwent different treatment options for aneurysms. They can have more than one aneurysm and each may be treated differently.
So I have variables like:
<...
- 43
3
votes
1
answer
756
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Making predictions manually from a mixed effects model
I have a mixed effects logistic regression model that is a bit more complicated than I've done in the past and just want to know if I'm thinking things correctly. I am crossing B_A (a within-subject ...
- 63
1
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0
answers
465
views
How to calculate predicted probability for each level of a random effect?
I've specified a generalized linear mixed effect model (using glmmTMB) with success of taking a seed as the response variable (Yes/No). Individual id is specified as a random effect because each ...
- 81
1
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0
answers
33
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predict interaction effect when raw data doesn´t cover the whole range of the interaction
I'm trying to model one binary response (y) as a function of one continuous variable ("size"). I'm using a generalized additive mixed-effects model using bam (library mgcv) because I have a random ...
- 125
2
votes
1
answer
40
views
Mixed models question
Let's say that i have data with 5000 participants(rows) and their scores on some sports, their age, weather on each event, location etc. Is it appropriate to use linear mixed models(lmer in R) if i ...
- 115
3
votes
1
answer
1k
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Filling missing data points with lmer prediction model
I'm trying to interpolate the missing data point using lmer model prediction.
Subsetting to a table without any na to the missing column of interest:
...
- 79
0
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2
answers
394
views
Predictive performance of joint models versus standard survival models
I am trying to show that predictions based on repeated measures of markers (using joint modelling of repeated markers and time to event models: JMbayes package) are better than those based on only one ...
- 31
2
votes
1
answer
744
views
Estimate random effects for a new individual with a linear mixed effects model
Consider repeated observations $\mathcal{Y} = (y_{i,j})_{i,j}$ obtained for $p$ individuals ($1 \leq i \leq p$), at different time points $t_{i,j}$ $(1 \leq j \leq n_i$). The "random slope and ...
- 137
6
votes
2
answers
489
views
Predicting a new observation: marginal mean, estimated marginal mean, or fixed effects estimator?
I'm interesting in making predictions using a random-effects model on new data that occur in new groups. Which estimator is most appropriate?
I fit a Poisson random effects model on some fake data:
$...
- 1,063
1
vote
2
answers
6k
views
generalized linear model with log link using log transformed fixed/random effects?
I am modelling a longitudinal dataset consisting of a continuous response variable (mutation count) with a binary predictor (medical history, ie previous medications) while accounting for time and ...
- 163
3
votes
0
answers
195
views
How do you evaluate the prediction accuracy of linear mixed models?
How does one evaluate prediction accuracy with uncertainty for linear mixed models? Let's say I do bootstrapping and do train/test each time, and want to generate confidence intervals for some ...
- 492
4
votes
2
answers
169
views
Explaining Fixed and Random Effects
Let's say that I am trying to predict the Sepal Length in
Iris data from Sepal Width, ...
- 201
3
votes
1
answer
917
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GAM factor-smooth interactions and model selection [closed]
I'm working with a dataset which is a long-term animal abundance survey collected from 11 sites, which have different average temperature(also there are some missing years for some sites). Here, the ...
- 65
1
vote
2
answers
247
views
Mixed models: predict random intercept with partial data
I have a dataset with growth data for teens between 12 and 18 years old, where I want to predict throwing speed for all ages using a couple of other predictors. These predictors have been collected in ...
- 23
2
votes
1
answer
2k
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Can MAD (median absolute deviation) or MAE (mean absolute error) be used to calculate prediction intervals?
From my understanding, RMSE (root mean square error) estimated through cross-validation can be used to calculate the prediction interval of a mixed-effect linear model with gaussian error. In my case, ...
- 375
1
vote
1
answer
68
views
Repeated measures in a mixed model
I'm trying to fit a mixed model for data from different medical centers, where "center" is thought of as random. I have data over 2 years on how many patients they receive each day. I have several ...
- 45
3
votes
1
answer
187
views
Out-of-sample predictions for mixed model are the same as naive model (ignoring the random effects)
I have a dataset that consists of subjects coming into the clinic (for treatment of another disease) and they are screened for Tuberclosis (as they are a high risk population). Every time they are ...
2
votes
1
answer
630
views
How can I better predict with (g)lmer with missing values?
Suppose I'm building a mixed model in R, and I want to use that model to predict new data for which I might not know the value of all the features. Or in some cases, it might not be so much that I don'...
- 4,791
1
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0
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140
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My ASReml GLMM is predicting "NA" values for one of my variables, any suggestions on how to fix this? [closed]
My question is: What is the relationship between malaria and schistosomiasis?
Therefor, I have plotted this GLMM;
...