Statistical methods appropriate for the analysis of data sets comprising several levels of hierarchy of units of analysis (e.g., students nested in classes nested in schools; observations nested in patients nested in hospitals). If you can refer to more specific models like mixed-model or glmm, ...

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15 views

Multilevel model to analyze limb injury data in Elite Athletes

I have a dataset of muscle activity measurements (variable name = RMS.mean) from a control group and an ACL injured group of elite ski racers. There are 11 ACL subjects and 12 controls. These ...
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1answer
13 views

Sort of repeated measure (that will be constant with one switch)

I cannot be specific about the data because it is proprietary. However, suppose we have data for a large number of customers for about 150 consecutive days. On each day, each customer can decide to ...
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30 views

Sample size for clinical research

I determined the sample size already (25), but I want to know if it has to be increased because of a minor change. Our study consists of two groups - one will be sedated and the other will not. For ...
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0answers
10 views

Predicting from individual and group data

Suppose that I have a classroom of students who each have taken two tests (A and B). I have the scores for test A and only know the average score for test B. Since students tend to perform similarly ...
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11 views

Multilevel between-matrix in R

R has tools for multilevel modelling (e.g., lme4), but I haven't been able to find an R implementation for multilevel correlation matrices on which the multilevel models are based. I'm looking for ...
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1answer
34 views

Whether or not to use a multilevel (hierarchical) model

I have a dataset, and I am not sure whether I have to use a multilevel(hierarchical) model or not. Suppose I have 10 dishes with a cell culture in each dish, and of these 10 cell cultures, 5 are ...
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18 views

Avoiding the ecological fallacy

My question is about how to handle misalignment between the levels of the data and outcome. In this case suppose I have Household income (Level 1) County median housing value (Level 2) County ...
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20 views

Should I include same variable as fixed effect as well as a random effect in random intercept model?

I have a problem in my project work. I have a three level nested model with level-2 cluster and level-3 division. My supervisor suggested me to include division as a explanatory variable as well as a ...
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0answers
14 views

Cause of overdispersion and multilevel model

I am doing some analyses on unethical behaviour scales (e.g. abuse of information) in teams of organisations. I want to analyse whether culture (perceptions of and shared culture) have an impact on ...
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19 views

Multilevel model analysis of dyad data

I'm trying to understand why when conducting a multilevel model analysis the Hessian matrix is not positive definite (using SPSS). The data I'm analyzing are responses from individuals who are grouped ...
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0answers
22 views

Mixed-effect or multi-level model (or other) for multivariate repeated-measures data? [R]

I have a dataset consisting of: 2 groups of plants (Group 1, Group 2) living in 10 different neighboring fields (...
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36 views

Restricted Maximum Likelihood Estimates of Multilevel Regression Model

A two-level regression model : $$Y_{ij} = \gamma_{00} + \gamma_{10}X_{ij} + \gamma_{01}Z_j + \gamma_{11}X_{ij}Z_j + u_{0j} + u_{1j}X_{ij} + e_{ij}$$ where $e_{ij}\sim N(0,\sigma^2_e)$ and , $$ ...
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1answer
46 views

Calculating Overall Relative Bias

I am in some trouble to understand how is to calculate the overall relative bias. In this link, there are results of overall relative bias in "Parameter estimates" sub-section under "Results" ...
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31 views

Multilevel Model in Matrix Form

A two-level model, with one explanatory variable at the individual level $(X)$ and one explanatory variable at the group level $(Z)$ : ...
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1answer
77 views

Multilevel multivariate meta-regression

Background: I'd like to conduct a meta-regression using studies which have (1) several outcomes/constructs (= multivariate) and (2) multiple effect sizes for every of these outcomes because of ...
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0answers
12 views

How to use multilevel analysis (MLM) in SPSS when I have 1 DV (frequency of absenteeism) and multiple IVs (more then ten) over three levels?

My aim is to analyze data in SPSS from an employee survey (approx 2000 subjects) and link this data to absenteeism. I think I should use multilevel analysis, but I am not experienced with MLM. DV = ...
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20 views

OLS regression versus multilevel modelling

I am working with a survey that includes student scores (level 1) and teacher characteristics (level 2). Students are nested within classes/teachers. I am interested in exploring the relationship ...
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0answers
21 views

Notation in two-level regression model

In this pdf, formula of two-level regression model is written as : $$Y_{ij}=\beta_{0j}+\beta_{1j}X_{ij}+e_{ij}$$ and in the pdf $e_{ij}$ is referred as individual level Residual . But I am not ...
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15 views

Hierarchical Linear Regression with One Level

I am using a dataset with information about pedestrian trips. When surveyed, some respondents made more than one pedestrian trip in a day. I am running a linear regression model and need to use ...
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26 views

Alternative to ANOVA (beginner)

I have run 15 experiments to compare the effect of different hormone combinations on the maturation on Xenopus oocytes (immature eggs). I am hoping to find the best performing variable. I have 4 ...
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1answer
28 views

Missing data and covariate analysis

I'm working on a model which has been fitted to longitudinal data (using mixed effects regression). I'm also investigating the effects of about 6 covariates on this model. Covariate A (continuous ...
2
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0answers
37 views

Hierarchical (multilevel, random-effects) Gaussian process regression

If we have a $J$ groups of predictor, outcome (univariate) variable pairs, $$ \{(y_{j1}, x_{j1}) \ldots (y_{jn_j}, x_{jn_j})\}, \quad\text{for $j \in 1\cdots J$}, $$ a hiearchical linear regression ...
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50 views

What is the difference between bi-level linear models and models with interaction terms?

My question is triggered by this question. I can't see that it has been asked here before, even though it looks like a natural enough question. Suppose I have hierarchical data. The Wikipedia article ...
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27 views

How to turn nlme syntax into manuscript appropriate equation?

I ran an linear mixed-effects analysis in R using the nlme package. I would like to write out the algebraic equation of the model's specifications. Unfortunately, I do not know exactly how to ...
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15 views

I have a hierarchical bayesian logit model with large variation in outcome between units. Should I still use a hierarchical model?

So instead of using country and time fixed effects for a time series cross section data on country-years with a binary outcome, I'm using a hierarchical logit model with country and time random ...
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19 views

How to describe this study design + MLM adequate for analysis?

I have recently encountered a rather particular study design and wonder how it could be adequately described and if a multilevel model should be used to analyze it. There are 3 factors in this ...
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1answer
23 views

Error terms and random effects standard deviation in multilevel modeling with R

While interpreting random effects part of the multilevel modeling with R, are standard deviations the same as error terms? For example, when the result is: ...
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12 views

Multilvel Model for Factor with Two Constants

I need to run an analysis in which observations are nested within subsidized and non-subsidized housing. In Stata, I have run random intercept models using xtmixed in which there are multiple ...
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17 views

Specifying 'subjects' and 'repeated' options in Linear Mixed Model (SPSS)

This question is probably quite easy to answer for those who work with Linear Mixed Model analysis. My question is the following: I have a repeated measures design, where each participant completes a ...
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2answers
33 views

Mixed-effects models with customer data: how do choices affect the model?

Suppose I had a large sample of customer data from which I want to predict total amount of sales over a time period with predictor variables indicating: -which sales channel did customers come from ...
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0answers
15 views

Visualize Sensitivity Results Using Combinations of Means and Standard Deviations of Two Normally Distributed Variables

I ran a sensitivity of my model, sampling the response space using two normally distributed variables. I used four nested repetition loops to generate this data, recording the average output of the ...
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0answers
24 views

Multilevel logistic regression model

I have a dataset in which the DV is a binary choice outcome on a task trial. My IV's include binary stimulus property on the same task trial (e.g., stimulus is blue or red) as well as individual ...
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1answer
22 views

How can I extract intercepts and slopes from multilevel(lme4)-model matched to each cluster?

I have a multilevel model based on data from weekly observations nested in persons. The cluster ist id. We measured fatigue several times. I expect that there may be a trend over time, i.e. persons ...
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12 views

Correlated errors within group with nonvarying dependent variable

I am trying to run a model in R to show how well one survey (SurveyA) predicts responses to another survey (SurveyB). SurveyA has 20 questions and we get an estimate of the participant's parameter ...
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15 views

Selection bias in multilevel modeling

I want to fit a multilevel model from a big survey in which the respondent could have no education, medium education or high education. My dependent variable is a continuous variable from the group of ...
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0answers
21 views

Cox survival analysis versus multilevel modeling

I'm debating the wisdom of a couple different approaches. I am constructing a model that measures whether the amount of a treatment received leads to a person coming back for another treatment or ...
4
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1answer
50 views

Managing high autocorrelation in MCMC

I'm building a rather complex hierarchical Bayesian model for a meta-analysis using R and JAGS. Simplifying a bit, the two key levels of the model have $$ y_{ij} = \alpha_j + \epsilon_i$$ $$\alpha_j ...
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1answer
16 views

Interpretation of “Same Slope” in Multilevel Modeling Example

An example of multilevel modeling : Consider an educational study with data from students in many schools,predicting in each school the students’ grades y on a standardized test given their scores on ...
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1answer
83 views

Notation of Variance of Residuals in Multilevel Modeling

I am having some trouble to understand the notation of variance of residuals in multilevel modeling . In this paper "Sufficient Sample Sizes for Multilevel Modeling" , in p.87 below equation (3) , ...
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1answer
23 views

Multilevel analysis or separate analysis for each level - group / individual analysis

I collected muscle activity levels from 4 different leg muscles on each lower limb over a 20 jump test in 2 groups of athletes. One group has ACL injury (n=11) and there is a control group (n=11). ...
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0answers
21 views

Confidence interval for a mean over hierarchical data

What is a good method for producing confidence intervals when computing a mean over hierarchical data? Specifically, I have the text messages sent by group of people and I want to compute the mean ...
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1answer
29 views

Calculating ICC using random intercept and residual variances

I have seen many posts refer to the calculation of the ICC by utilizing the variance of the random intercept and the residual variance from a multilevel model. Does anyone have this formula handy?
1
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1answer
36 views

Challenging Propensity Score/Causal Inference Problem

I am reaching out to the Cross-Validated statistical community seeking suggestions on a challenging problem on which I'm working. I've been asked to look into a problem related to electronic ...
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0answers
15 views

Mean of sample means from samples of different variances

Suppose I have three samples $x_i \sim \mathcal{N}(\mu, \sigma_b^2)$. I cannot measure the $x_i$ directly, so instead I estimate the value of each one by averaging $n_i$ draws from a distribution ...
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9 views

MLM with negative

I am little confused about how to interpret the result of the null model depicted in the image below. I am totally novice in MLM. Does it mean that the average score of students is -0.97 in the null ...
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0answers
7 views

When can hierarchical models be specified as a latent gaussian model?

I'm trying to learn more about integrated nested laplace approximation and latent gaussian models. I came across a blog post by Thiago G. Martins in which he says, "if you can fit your model into this ...
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0answers
46 views

Interpretation of SPSS output mixed model

I have an spss output, whereby I included the variable education in the fixed as well as random part of the SPSS mixed model syntax. A multilevel model is estimated whereby Level 2 represents ...
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0answers
44 views

Model for survival analysis with time varying predictors (panel data) and delayed effects

I collected behavioral data of more than 150 people, monthly, over two years. So for each of them I have 24 repeated measures over time. It occurs that after some months some of them get infected by ...
4
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1answer
46 views

Citation for ML vs. REML

Quick question: can anyone give me a citation that I can use to justify using ML when doing model comparisons? Background: I am fitting some multilevel models in R using lme4, and I do a series of ...
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20 views

Treatment of data that is contingent upon earlier item in multilevel modeling?

How should data be treated in multilevel modeling when they are not available because they are contingent upon how a previous question is answered? For example, if the participant answers "no" on ...