All Questions
1,273 questions with no upvoted or accepted answers
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163
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multilevel modeling (lmer)
I'm trying to run some main effects models with the lmer function (lme4 package) in R but they keep coming out as a singular fit. It's possible this is because the model is overfit, but even when I ...
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28
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Shall I further belive DHARMapackages whan dignosed?
Today , I get the terrible resulits from the glmer.nb(). I tried a plent of methods to change the variables. However, When I finaly fitted a model with FUll variable . qqPlot(resid(Model)) tell me I ...
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234
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How to fit a power curve for a glm with simr
My response variable is counts of turtles at sea surface per aerial survey (possible values: 0,1,2) and I use a Poisson distribution for it (since my data are not overdispersed neither zero inflated). ...
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267
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Need R help with an HLM model with 2 level 1 (categorical) predictors and 1 level 2 (continuous) predictor
I am trying to create a HLM in R where I have one outcome measure: Y; two dummy coded Level-1 predictors: A and B; and 1 continuous Level-2 predictor: Z.
Investigating a 3-way interaction with this ...
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39
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Is it valid to build a binomial hierarchical model with skewed observations between random effect levels?
I am trying to model the relationship between vegetation growth and insect outbreaks (binomial: 0=non-outbreak, 1 = outbreak) by bioregion and season. To do this, I am constructing a hierarchical GAM (...
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128
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Clustering Algorithm for data where each type has multiple observations?
I am trying to segment football teams based on their playing style using multiple features. I want to see which football teams have similar playing styles using cluster algorithms.
For each team I ...
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408
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conducting a multilevel model with a continuous variable and categorical variable in r (+ post hoc)
I conducted a study in which I presented three types/blocks of visual stimuli (neutral stimuli in baseline, negative stimuli, neutral stimuli following negative stimuli).
To examine the relationship ...
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252
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Binomial Logistic-Normal Updating
I've been considering how sports with binary outcomes might be modelled e.g. the probability of a tennis player winning a point on serve.
In text books the usual Bayesian approach uses the beta-...
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36
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Is a GLM the best option to analyze my data with R?
I would like to see which factors can better explain the success of a particular event to happen. I'm interested in 4 factors, being before, ...
- 177
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21
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Proper use of multilevel analysis in team settings [conceptual question]
i am faced with the following question: I sit on a data-set of about 200 teams, that contains information about the mental health of the individuals (i.e., GHQ-12, ex: sleeplessness and so on.) and ...
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44
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Four level mixed model (multi-level linear model) - formal model specification with mathematical annotations
I am running a mixed-model in nlme (R) with momentary assessments (5 times, L1) nested in days (4 days, L2) nested in trimester (3 Trimester, L3) nested in participants (152, L4) from a longitudinal ...
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93
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Could this variable be modeled by a poisson regression?
I have a pc experiment and an ordered response variable with 8 levels (from 0 to 7). I have also a factor (different types of stimuli) to include as a predictor in the model. So in each trial, the ...
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50
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Unusual residual artefacts in GLMM, is GAM or another model more appropriate?
I'm having trouble finding an appropriate model for my data. The data comprises behavioural observations of chimpanzees, where I instantaneously sampled their locomotor behaviours and parameters of ...
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67
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Generalized linear (logit) mixed-effects model with the random (crossed) effects drawn from a bivariate normal distribution
I am trying to implement a generalized mixed-effects model specified as:
Dependent variable $y = \log(\frac{p}{1 - p})$ where $p$ is a quantity measured for a pair of individuals ($i$ and $j$).
$E(...
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How can parameters be modeled differently if they share hyperparameters?
In one popular example of multilevel Bayesian models (2007 Gelman et. al paper), radon exposure in a household is modeled as a function of the county and whether the house has a basement.
In this ...
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108
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Multi-level survival modeling
I'm struggling with choosing the appropriate model for a study I'm doing where I determine the survival times of certain technological applications. The goal here is to estimate how long individuals ...
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124
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Explanatory variable on group level in mixed model
I'm looking at how the scoring procedure influences individual behaviour in competitions. The independent variable (scoring procedure) is measured on the competition level, while the dependent ...
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38
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Determining Link for GLM
I am having a great deal of difficulty understanding how to use the Generalized linear model for my data set. The response variable of interest is hatch success of sea turtles, which is a %. The ...
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45
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How to test significance of difference between regression coefficients for multiple interaction categories?
Suppose I have N multiple categories (a discrete interaction variable) and
representative samples of which. I'm fitting a multi-variate X linear regression model to response variable Y for each ...
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19
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Multi-level data query
We want to find the relationship between supervisor's narcissism and subordinate's job commitment. We have collected data from 600 supervisors and 1800 subordinates reporting to them (three ...
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81
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On how to interpret paired comparisons for model-adjusted means in GLMM
I have been trying to learn how to obtain the model-adjusted means (or least-square means) from GLMM, and come across some counterintuitive results.
Below is the data I am currently using. It's the ...
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148
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HELP: LM shows no relationship, but LMM does
My research question is assessing if a variable (let’s call it ‘x') can predict another variable (let’s call it ‘y’). The two variables x and y are in the same units, but they just come from ...
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308
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Why are the confidence intervals so large for the difference of differences?
I have run a generalized linear mixed effects model with the glmmTMB package to determine if there is an interaction between two categorical predictors, treatment and location, in predicting the ...
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233
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Multilevel analysis - interpretation not significant at level 1
I'm doing a multilevel analysis for the first time for my master thesis.
The goal of my study was to create behaviour change through an intervention. Participants are measured for behaviour at 3 ...
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1
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117
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Mixed-effects models for within-subject psych experiment (in Stata)
I have a question about how to best analyze data from an experimental psychology study. Briefly, 250 participants were asked to assign four different pictures (Pictures A - D) to two different ...
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81
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Multilevel model with nested groups
I am making a multi-level linear model in R using lmer
Structure of my data is a bit convoluted
There are 8 Bogs with 6 squares where damage is evaluated and 3 sweeps for insects. Squares 1,2 ...
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385
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Linear Mixed Model Failing to Converge
I am attempting to run a Multilevel Mediation in R with overtime data (4 time points, 50 participants). I was hoping to create two new columns for each outcome and predictor variable, a baseline ...
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33
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How to choose the independent variables in a GLMM without performing stepwise selection? With a global model? How to decide then?
I am trying to conduct an inferential binomial GLMM with a large dataset and many independent variables. I was attempting to do a stepwise AIC selection but keep reading it is a bad idea. However, ...
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777
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confused about effects vs. means parameterization in R - which is right for Anova?
I'm running a few GLMs and using the effects (e.g. glm(var1~var2...) ) and then means parameterization (i.e. glm(var1~-1+var2...) -- the one without the intercept). I understand that effects gives you ...
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127
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Generation of synthetic data for Hierarchical clustering
I wanted to test various hierarchical clustering algorithms to check which algorithm performs best. For this, I was considering simulating some ground truth. Is the possible to generate a correlation ...
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21
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How to formulate a generalized linear mixed model?
I have a data set like this:
population: numeric
country: categorical
city: categorical, nested in country
century: categorical, crossed by city and country
year: categorical, nested in century, ...
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66
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forced fixed intercept but lattice plot showed random intercept
I was running a model and something weird pops up.
I ran a multi-level regression using the code below:
...
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54
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In a Multi-level Bayesian Hierarchical Model, would higher level parameters be affected by how they are jointly modeled in lower levels?
Suppose we have a Multi-level Hierarchical Model where:
$$
\begin{equation}
Y_{0i} \sim Bin(\theta_{0i}, n_{0i}) \\
Y_{1i} \sim Bin(\theta_{1i}, n_{1i}) \\
\theta_{0i} \sim Unif(0,1) \\
log\left(\...
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20
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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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1
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145
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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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625
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Predicting individual-level outcome with only group-level data
Suppose I have summary data from a number of different classrooms, and I want to model a binary outcome (pass/fail) for individual students. I have no individual-level data. I have some classroom ...
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198
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Posterior distribution of ATE with Bayesian propensity score model?
I am using propensity score weighting (PSW) to estimate the average treatment effect (ATE) of some treatment $D$ on an outcome $Y$ with covariates $X$. I have seen several ways in the literature (both ...
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115
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random effect variance as pseudo-rsquared in GLMM
Suppose I have data on the abundance of a species across multiple sites that differ in some covariate of interest. Suppose that the logarithm of the abundance (logAbun) meets assumptions for linear ...
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66
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If change is DV and Pretest is covariate, should random effects take the form of (1|subjects) or (Pretest|subjects)?
I have Change from Pretest to Posttest (gain, no_gain, decline) as the DV.
Pretest and Group as covariates. This called for a multinomial regression
...
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55
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How to run a nonlinear repeated measure multilevel regression?
I'm working with a colleague on a project that requires analysis a fair bit beyond my expertise.
Background We are looking at recall of events in films. We broke down the film by Events and by shots ...
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384
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3 Level Hierarchical Models in STATA; Null model fails to converge
3 Level Hierarchical Models in STATA; Null model failed to converge
About the Dataset
I am working with DHS (Demographic and Health Survey Data) data. DHS uses a two-stage cluster sampling process. ...
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1
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105
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How to interpret the output when one or two levels are significant in the seemingly insignificant categorical predictor in logistic regression
I am running a multilevel binary logistic in SPSS.
The predictor variable in question is a categorical variable with four levels. In the first fixed effect table, it seems like the predictor variable ...
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26
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Analyse interaction/moderators first and then adjust for confounding
In my research I am interested in subgroup analyses.
I am looking at a general association between two variables (environment and health outcome) with interaction terms (personal factors, which are ...
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2k
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How to Interpret the result of generalized linear mixed model?
I ran a generalized linear mixed model using lmer in R, and I'm struggling how to interpret the result. The response variable is a result of 25 consecutive binary choices. The point where I'm stuck is:...
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32
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Different significance in GLMM interactions
I am confused about different significance results obtained in GLMM's.
First, my set of relevant variables:
...
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26
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Compare treatment effects across Levels of aggregation
Suppose I am running an experiment to see if a treatment changes the mean weight of a group of people. Note that I am specifically interested in the mean weight: if half the people get heavier, and ...
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88
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Multilevel Model Application / Specification
I have some multilevel-data-structure, where I want to regress top 10 music chart listings (dependent variables: downloads and rank) on some song characteristics (Xi). The problem for me now comes ...
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128
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linear mixed model gives wrong results
I am currently learning Stan (MCMC C++ engine with wrappers in python and R) and implemented a linear mixed model
$y_{i,j} = \beta_0 + \mathbf{x}_{i,j}^T\beta + \alpha_i + \epsilon_{i,j},\ 1\leq i\...
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434
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Paired sample t-test equivalent for intensive longitudinal assessments
I am a bit new to multilevel and mixed-effects modeling. I have a dataset, where I have sensor measurements throughout the day for 4 weeks on N participants. I have some prompts on their smartphones ...
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349
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Why am I getting low effective samples and high rhats with multilevel Bayes models using brms?
I've been using the brms package in R to run some multilevel Bayes models. I've been getting some strange results however (such as extreme predictions and not ...
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