Questions tagged [multilevel-analysis]
Statistical analysis of datasets comprising several levels of hierarchy (e.g., students nested in classes nested in schools or hierarchical forecasting). For questions about mixed models use [mixed-model] tag. For nested random effects, use [nested-data].
0
votes
0answers
8 views
Coding nested factors for 3-level in rma.mv function of metafor package
I'm working collaboratively on an arm-based, network meta-analysis in the agricultural sciences. After carefully reviewing the Konstantopoulos walkthrough and Viechtbauer's slides to develop the code, ...
0
votes
0answers
10 views
Bayesian parameter estimation with varying subsets of data?
I'm currently working on a model in which I have 2 measurements, taken at different temperatures. The covariance between these measurements with temperature is assumed to be linear and therefore a ...
0
votes
1answer
13 views
Analysis crossover clinical trial
I have data from a six-sequence 3-drug 3-phase crossover trial that had a 7-day baseline period pre-study (used to generate mean baseline value). My outcome is a non-parametric continuous variable ...
0
votes
0answers
14 views
GLMM - determining proper comparisons
I am working with a dataset that has 3 independent factors (group: 2 levels, lift: 2 levels, type: 3 levels) that I am running a GLMM on to determine their effect on a continuous dependent variable. ...
0
votes
0answers
9 views
Is it viable to run multilevel analysis on variables nested conceptually, and not necessarily by participants-groups?
I am trying to devise a model which predicts people's demand for more information.
The model I'm contemplating has 2 levels of predictors that are not nested in terms of participants (for example, ...
2
votes
1answer
20 views
Forecasting sales (in units) for thousand of products
I've got into this internship in a retail company and they asked me to think a way to forecast their daily sales (in units) in all their stores (with thousands of skus each one).
At first I thought ...
0
votes
0answers
15 views
How is it that when I reverse-score an item I get completely different results in a MLM? [closed]
How is it that when I reverse-score an item I get completely different results in a MLM? I reverse-scored an item so that a high score would represent high national identification instead of it ...
0
votes
0answers
15 views
How to interpret interplots with marginal value of an cross-level-interaction
I need help regarding the interpretation of a plot created with the interplot function in R. The dependent Variable is the dummy Variable "Employment of mothers" (yes/no). The variable whose ...
1
vote
0answers
14 views
Different variables for different subgroups of linear model
Let's say I have a multiple linear model for a population of the form
$y = \beta_0 + \beta_1x_1 + \beta_2x_2 + e$
There is a third variable I want to introduce that I believe significantly explains ...
1
vote
0answers
22 views
What model should I use? Time series count data grouped into provinces. R
I have daily observations on the count of a variable, with 1,000 daily observations across 15 different provinces, for a total of 15,000 observations. On certain days, there is an exposure, which may ...
0
votes
0answers
23 views
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:
...
0
votes
0answers
12 views
Are Generalized Linear Models with random effects the frequentist version of a Bayesian Hierarchical Model?
In the Hierarchical Bayesian Model literature I often read of comparisons of the methods to GLM models, but with random effects. In the literature, is this the general consensus?
2
votes
0answers
14 views
In a Hierarchical Bayesian Model, how can we sample and see how a prior distribution looks like if it contains hyperparameters with hyperpriors?
I have a Bayesian Hierarchical Model that looks like:
\begin{equation}
Y_i \sim N(\mu, \sigma^2) \\
\mu \sim N(\mu_0, \sigma_0^2) \\
\sigma^2 \sim Gamma(1,1) \\
\mu_0 \sim N(0,1) \\
\sigma_0^2 \sim ...
1
vote
0answers
19 views
Interpretation Output lme (Intr)
I`m getting this output from R for my mixed model with lme package. The output seems to be making sense so far and I can interpret it. However I am wondering how I should interpret the correlation (...
0
votes
0answers
2 views
How does RJags handle situations in which we have a constraint on combined parameters, but the parameters may take on values outside the constraints?
Suppose we have the following model for the difference in two proportions from a binomial.
...
0
votes
0answers
19 views
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(\...
1
vote
1answer
17 views
When is the best to add control variables in multilevel modelling?
Is it better to add control variables before or after the main predictor variable while conducting a step-wise multilevel model?
0
votes
0answers
12 views
Chi2 or multilevel?
I am predicting smartphone app use. The research question is: do people use the smartphone app more when they get a reminder.
If I have a dichotomous predictor (smartphone reminder) and a dichotomous ...
0
votes
0answers
9 views
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)...
2
votes
1answer
42 views
Understanding nested random effects - why is an interaction between factors involved?
I have read this question and answers:
Crossed vs nested random effects: how do they differ and how are they specified correctly in lme4?
however, I am struggling to understand why, provided that ...
0
votes
0answers
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 ...
0
votes
0answers
12 views
Calculating ICC using z-scored standardized or unstandardized DV in Multilevel Linear Model?
I am doing multilevel linear modelling and I am calculating my ICC for my random intercept model. However, when I use the z-scored standardized DV (reaction time), the intercept and residual variance ...
0
votes
0answers
5 views
Testing whether subject-level slopes in two different random slopes models are correlated across-subjects
Sorry for this poor title.
Let's say 50 subjects each did 20 trials of an experiment, and I recorded 4 variables from each trial, W, X, Y, Z. For each subject, I want to measure the correlation ...
0
votes
1answer
15 views
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 ...
0
votes
1answer
143 views
lme4 lmer() multilevel model: why do I have singular fit and a -1 correlation between random effects slope and intercept?
I'm running a varying intercepts varying slopes multilevel model with the lme4::lmer() function with no group level predictors and only one predictor: FilingFee to predict evictionfilingrate.
I ...
0
votes
0answers
31 views
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 ...
1
vote
1answer
22 views
“Multi-level” social network analysis?
I am very new to social network analysis and working on a project here that I am not sure what's possible to model.
I don't want to quite call this multi-level because I am not exactly looking at ...
0
votes
1answer
90 views
Long data format for Mixed linear modeling
I have a data set from an experiment with two conditions: a control condition, and a testing condition. It's an experiment performed in pairs. Each condition was undertaken by 20 pairs of subjects (...
0
votes
0answers
14 views
Multilevel modeling: many groups, mostly one sample each
I have a modeling problem in which customers can have multiple accounts on a website. Roughly speaking, 50% of customers have one account, 25% have two accounts, 12.5% have three accounts, etc. There ...
0
votes
0answers
9 views
Checking ICC in MLM when DV is level 2
I'm running a multilevel model in SPSS where my data is grouped by teams. The DV is a level 2 variable since the team as a whole got a score (1 - 10) for completing a task. The IV is level 1 such that ...
1
vote
1answer
44 views
can I use a multilevel model for my situation? Pre/post, no control group
I have a question about whether multilevel modeling is appropriate in my situation. I’m working on an analysis looking at the effect of a treatment for patients with a disease. There is one pre ...
6
votes
0answers
184 views
Regression with dependent data with low dependence
Suppose you have data that is grouped in one way or another and therefore the assumption of independence is suspect. But you look at the intraclass correlation (or autocorrelation) and it is very ...
0
votes
0answers
10 views
How does explained variance in within level variables influence across-level-relations in multilevel SEMs?
Firstofall: I am sorry I cannot provide a minimal example code. I am trying my best to generalize the problem, but yet I just couldn't recreate it with dummy data. I try to provide any information ...
0
votes
0answers
23 views
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
...
4
votes
0answers
19 views
Simple trend analysis with unbalanced & short panel data
I have the following (unbalanced) panel data: yearly sustainability ratings (ESG) of ca. 2000 individual firms over a 11-year period. The average observations per firm only covers 5.3 periods. These ...
1
vote
2answers
21 views
I have an insignificant beta weight of a predictor, which the only predictor in a step with significant R-square change and significant F-value
I am running a hierarchichal multiple linear regression with 4 steps containing theoretically justifyable variables:
Outcome: pain rating
Step 1: demographic variables (age, gender)
Step 2: Pain ...
1
vote
1answer
21 views
How to test whether changes in x track changes in y over multiple time points for multiple individuals
So I'm wondering how to analyse this data:
I have 30 people. for each person I have 2 normally distributed variables, x and y. I want to see whether x and y are linearly related, but 30 data points ...
0
votes
0answers
6 views
Multilevel generalized linear model (MGLM) with rank dependant variable : Specification issues
I am currently trying to estimate a multilevel generalized linear model (MGLM) on rank data using clmm function from "ordinal" R package.
My dependant variable is a ranking variable repeatidly ...
1
vote
0answers
48 views
Receiving singular fit error while using lmer on one computer but not another [closed]
I have a script with a multi-level models that appears as follows. X1 is continuous, X2 is dichotomous, there are 45 of subID and 296 trials for each subID.:
Y ~ X1 * X2 + (X1 * X2| subID)
When I ...
0
votes
0answers
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 ...
0
votes
0answers
9 views
Multilevel modeling, constraint for positive values
I'm currently trying to fit a shifted inverse gaussian to reaction time data (always postive). My paramterization of the model includes 3 parameters, alpha, gamma and tau, which must always be ...
1
vote
3answers
65 views
How do I model a dependent variable that is a proportion?
Problem
I am trying to test gender differences in the risk propensity of investors related to specific kind of stocks. More specifically, I want to the test the hypothesis predicting that female ...
0
votes
0answers
35 views
Investigate whether hospital infections tend to have common etiology in the same ward/hospital
I have data from a national prevalence study on healthcare-acquired infections (HAI).
I would like to know whether two patients being in the same ward (or in the same hospital) have a higher risk of ...
1
vote
1answer
44 views
What are some good examples of working through a multilevel model by hand?
I've been learning about multilevel models lately, and I understand the concept of shrinkage and partial pooling (I think), but I'm still confused to some extent on how partial pooling actually ...
1
vote
1answer
42 views
Multilevel modeling when observations are clustered but clusters are not random
I am working on a project where I am trying to model a continuous outcome, y, in an organizational setting. In this particular organization, employees are nested within teams, which are nested within ...
0
votes
1answer
23 views
Longitudinal study - generalised linear mixed model - dealing with very wide confidence intervals due to sparsity in the outcome
I am conducting a treatment evaluation using administrative data. It is a population-based study of all people diagnosed with a specific disorder in two calendar years (N = 2300). I have run a GLMM ...
4
votes
1answer
65 views
Multilevel model with 4 levels?
My dataset is a pretty typical educational dataset: we have data about students, courses, faculty, schools, and I plan to include partially-crossed random effects because students could enroll in ...
0
votes
0answers
39 views
Hierarchical bayesian model: should I account for lack independence?
I am working with vegetation surveys that were conducted in several river networks. See the attached image that shows one of the those river basins/networks. I am interested in analyzing how the ...
0
votes
0answers
7 views
Modelling an response that is an intersection
I am trying to model a variable which is the result of an intersection of words.
For example:
a = ["apple", "orange", "pear"]
b = ["apple", "orange", "carrot"]
The number of intersecting words ...
1
vote
1answer
30 views
Power analysis for multilevel model with two fixed and two random (crossed) effects: how to define sample size with simr package [closed]
I want to define the sample size for a repeated measurement experiment. Every subject will indicate her/his behavior on a 1-7 scale for several stimuli (=behavior). I expect that personality and ...
