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Statistical analysis of datasets comprising several levels of hierarchy (e.g., students nested in classes nested in schools). For questions about mixed models use [mixed-model] tag. For nested random effects, use [nested-data].

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plm vs lmer - differences in outputs?

I am looking to run a random-effects model to look at attainment of pupils who are nested within schools. The model specification includes pupil-level characteristics, school-level characteristics and ...
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15 views

how can we name node/levels of an hts (hierarchical Time series forecasting package) object other than through leaf level? [closed]

As per hts (hierarchical Time series forecasting package) documentation and also browsing through stackoverflow, rbloggers etc., the only way to specify names to levels of hierarchy other than the ...
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1answer
25 views

Is it neccessary to test for serial correlation in a multi-level model

I am running a multi-level model looking at factors that explain attainment. There are pupil- and school-level predictors, and the school the pupil attends is modelled as a random effect. I have run ...
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1answer
46 views

GLMM optimiser test - optimx.L-BFGS-B doesn't converge, but the rest do

I am running GLMM using lme4 in R for the first time. I have a complex model (with three main effects and four interactions), as well as a random intercept of ...
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10 views

Has anyone used SPSS to do one-with-many analysis with MLM? [closed]

I have collected data from patients and doctors to be analyzed by a reciprocal one-with-many analysis. The outcome is patient-rated and doctor-rated trust in their relationship. And quality of ...
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14 views

Cross-classified longitudinal model in R

I am trying fit an unconditional means model for longitudinal (i.e., repeated measures) cross-classified data in R. I have business segment-year observations for each business segment (SID) within a ...
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12 views

Should I use Generalized Estimating Equations or Linear Mixed Models (i.e. Multi-Level Modelling) analysis for an experimental study analysis?

Apologies for another question in this area. Due to my complicated study design, I have had difficulty trying to apply answers in other posts to my analysis. I completed a repeated measures ...
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How to do classification in mixed effect models in python. My data is nested into groups with binary outcome

Lets say I have 10 sellers (S1-S10). Each seller has 7 buyers which are different for each seller (B1-B7 for S1, B11-B17 for S2 and so on). Each Seller buyer combination has a product category (P1, P2....
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1answer
28 views

Multilevel models - Which level should the random effects enter on?

I am currently studying the effect that a pollutant has on plant growth. The plants come from a few different regions, and it is assumed that plants from the same region share more in common than ...
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1answer
34 views

Repeated measures, multilevel regression or another type of analysis?

I'm doing an experiment for which I've distributed a survey. People were asked in this survey to rate the attractiveness of 5 other people. I provided four groups of pictures and 1 of those groups ...
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1answer
15 views

Confidence intervals for emmeans estimates after multilevel binary logistic regression

I ran a multilevel binary logistic regression / generalized linear mixed-effects model in R, and then ran the following code to get post-hoc tests for a significant A x B interaction where A is a ...
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3 views

Allowing cluster-level residuals to covary in Proc Glimmix

I am modeling the probability of a child being retained in kindergarten based on individual and school-level factors. The model includes random intercepts and slopes, as follows: ...
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14 views

Comparing Demographics Of Observations Within Subgroups

I have a dataset of states with a variety of demographic characteristics of those states, as well as those states assigned to a geographic region (note that the first column is "fips", just that the ...
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14 views

Hierarchical modeling for infering people's beliefs

Usually, when I do hierarchical modeling, the problem is relatively simple. For instance, let us say I want to know the average weight of frogs in an area, and I collect data on frogs from different ...
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15 views

What is the appropriate analysis for this type of repeated measures multi-binary data?

There is a popular theory within psychology that certain emotions will trigger "prototypical" facial expressions defined by the simultaneous contraction of specific facial muscles. For example, if a ...
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20 views

Using lmer to model time series data in R

My data looks as follows: The level structure is as follows: Level 1: Problemtype (A-G) Level 2: Sessions (between 3 and 10) Level 3: Persons (100 overall, but 2 to 8 in each Group) Level 4: ...
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1answer
30 views

output of lmer function

I have a question regarding understanding of the output of lmer function under lme4 package in ...
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0answers
17 views

Determining autocorrelation within occupancy covariates in R

I am doing a study underpinned by an occupancy modelling framework in R using the unmarked package to investigate the influence of different anthropogenic ...
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1answer
84 views

Why is my manual calculation of the log-likelihood for a 3-level model different than what nlme provides?

In short: I want to manually calculate the log-likelihood of a 3-level multilevel/mixed/hierarchical model, but my result is different from what nlme gives. I don't ...
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0answers
10 views

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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27 views

Within-subject or within-group standardization in mixed models

I have read informally suggestions not to standardized within-groups in a mixed model. That is, for example, if my model is ...
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0answers
21 views

Is it okay to include the dependent variable as an input variable to the higher-level regression model, in a hierarchical / multi-level setup

Let's say I have a hierarchical dataset with student scores (for each student) nested within schools. While modelling for a varying intercept, would it be okay to include the average of student scores ...
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14 views

Including predictors with HLM

I have data from healthy controls and patients that I plan to use in a multi-level model. I am comparing how mindfulness improves performance on cognitive tasks in healthy controls and patients. ...
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1answer
50 views

Why is the random intercept variance so much larger in R than in SPSS in my model and how do I interpret the results?

I am new to Cross Validated so please forgive me if this question has been asked before. However, I did not find any post that answered my question, so here it is: I am running a 3 level multilevel ...
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7 views

Multiple Imputation on multi-site data

Suppose I would like to assess the relationship between Y and X (i.e. Y|X) on data collected from several different sites (i.e. 5) with one covariate Z and multiple auxiliary covariates which may ...
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1answer
21 views

Regression: Interaction Effects vs Random Effects

I'm struggling to understand the difference between creating an interaction effect in linear regression vs a random effect. Both allow the algorithm to identify a different slope for a coefficient ...
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1answer
60 views

lm() coefficients don't match lmer() fixed effects

I'm new to hierarchical models and am learning to use the lme4 package. My understanding is that the fixed effects generated from the lmer() function are suppose to match the coefficients from lm(). ...
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1answer
15 views

Running a multilevel model without level-1 predictors

Is it acceptable (publishable) to run a multilevel model with only level-2 and level-3 predictors? Example: Looking only at the effect of school resources, size or location, and at the district level (...
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11 views

Coping with clustered observations in machine learning

One of the assumptions in the generalizability of machine learning algorithms is that observations should be IID. But in many cases, observations come in natural clusters, in which observations are ...
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1answer
58 views

Difference between multilevel logistic regression and a logistic regression with lower levels aggregated

I have a question about the differences between two forms of logistic regression. Let's say that I have data that is collected with some nesting. For concreteness, we'll say that I've got data across ...
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0answers
8 views

Use of cross-sectional survey weights when employing mixed-effect regression models using multiple cross-sectional data

I have conducted an analysis using multiple-cross sectional datasets (i.e. combining different waves of the same survey). The survey provides cross-sectional weights for each wave. Considering that a ...
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10 views

cross-level interaction significant with three levels but insignificant with two levels

Help appreciated! I have run a multilevel model with two levels (students-classes) in which a cross level interaction appears insignificant (an interaction between a student-level predictor and a ...
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0answers
12 views

Determining which variable is more affected

An illustration of my issue: For e.g. X is a hormone that affects both the growth of hair, feet and nails. A case-control study was conducted with cases having a condition causing excessive hormone ...
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10 views

How to formulate a nested model when the higher-level variable is continuous?

I am trying to design a model that will allow me to simultaneously assess the effects of local and landscape-scale variables (both quantitative and continuous) on an ecological response (in this case, ...
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15 views

Model Design for Baseball Regression

I'd like to build a multi-level regression model to predict the difference in scores when two teams play a game. I'm wondering how I should structure the explanatory variables. I would also like to ...
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1answer
17 views

What are the common methodology can be used to find the parameter of the fixed and random effect in a nonlinear mixed effect model?

Recently, I am doing some research about nonlinear mixed effect model. However, most of the time, they will just straight away use the R language nlme package and fit the model into it to get the ...
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32 views

In a three-level - multilevel analysis, what is the formula for the variance of a unit at the third level?

I'm looking for the formula to calculate the variance of a specific unit at the third level of a multilevel analysis. Snijers and Bosker (2012) give the formula for calcualting the variance of a unit ...
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1answer
24 views

How to run a multilevel model with hurdle/zero-inflated and continuous dependent variable

I have a dataset on voting loyalty (measured as percentage dissenting votes on votes cast) of parliamentarians (dependent variable, percentages) and the inclusiveness of their party's selection ...
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2answers
39 views

logistic regression factor/categorical predictor without reference/contrast

I did an experiment and there are 3 treatments. My hypothesis is that treatment A & C will lead to response 1 and treatment B will lead to response 0. I'm not trying to get a comparison result ...
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1answer
26 views

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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20 views

Is a three-level multilevel model appropriate for my research question?

For a study that is currently in the planning stage we are considering what kind of model would be most appropriate. We are interested in the interactive effect of a drug (vs. placebo) and hormone ...
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0answers
21 views

Incorporating knowledge of aggregate outcomes to constrain predictions on finer scales

I've got county-level longitudinal data on the timing of an event between the years 1998 and 2012, and I want to use it to form a predictive model for the time that that event will occur in future ...
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0answers
23 views

multi-level Wilcoxon analysis

The question was originated from the paper [1] Table 3 [2], for every species, there was a data frame with two column: disease categories and the conservation index. Conservation index is numeric. The ...
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30 views

Multinomial (Categorical) Multilevel (Hierarchical) Bayesian Model in R

I have a couple of questions, so I hope it is ok that I ask them here. Before that, here is some background information on my data: Outcome variable (1): categorical, 6 categories, N=168 Predictor ...
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31 views

Compare proportion of patient outcomes of the same group over time- McNemar's or Chi Square?

I want compare proportions for the same practices over two time points, while timepoint 1 is the control and timepoint 2 is an intervention. Let's say I have a design in which doctors are clustered ...
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1answer
107 views

How to account for multiple measurements of same person in either two-group comparision or regression?

I am running analysis on clinical data collected from patients which are correlated either by time (longitudinally) or more commonly different measurements of the same person at same time (eg. ...
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0answers
45 views

Can this be solved using a binary logistic multi-level model?

Is it possible to solve the following task by using a binary logistic multi level regression? If not, how can you solve it? The concept as a diagram: I have the location of individual stores and ...
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17 views

Truncation and a composite distribution

Suppose $X$~$N(a,1)$ $Y|X$~$N(X,\sigma^2)$ Then what is $X|Y<0$ ~ ? and $E[X|Y<0]$ ~ ?
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1answer
57 views

Combining two multilevel models that are a sort of two stage model

I have a study where the same people were exposed to advertisements both with and without an "endorser" or spokesperson. There were also several different kinds of endorsers (male vs. female and so ...