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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20 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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11 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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0answers
16 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
17 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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10 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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11 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
30 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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13 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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21 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
20 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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13 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 ...
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1answer
41 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
15 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
81 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
18 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
20 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
27 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?
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1answer
34 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
13 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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0answers
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
28 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
34 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 ...
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1answer
36 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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0answers
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 ...
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47 views

Interpreting lme4 fixed effects using pamer.fnc from LMERConvenienceFunctions package in R

I'm fitting multi-level models in R using both lme from nlme package and lmer from ...
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0answers
18 views

Repeated measures regression with categorical and continous predictors

(This is a follow-up of a previous question of mine, and similar to this unanswered question) Scenario Say I have 30 subjects. On each subject, I have a number of categorical and continuous ...
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1answer
62 views

Parametric vs non-parametric time series modeling

Hi I have a large data set of objects, each containing a set of the same attributes. The attributes are measured quantities like height, width, etc. The data is arranged in a time series so that the ...
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2answers
42 views

specification of mixed effects model with two levels of repeated measures (in R)

My colleagues and I conducted a study of the effects of an experimental translocation on the movement and activity patterns of common brushtail possums in New Zealand. This involved first capturing 12 ...
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0answers
48 views

Multivariate Mixed Model With Continuous Independent Variable - SPSS or R?

I've been trying to find an appropriate statistical technique to analyze multiple IVs and DVs with no luck. The IVs include 1 trichotomous within-subjects factor, 1 dichotomous between-subjects ...
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0answers
10 views

Missing block (Multilevel Modelling, repeated measures)

Experiment: participants respond to a moving object. Explanatory variables: velocity of object (fast, slow), Type of object (A,B). There are four different types of blocks, each with 16 trials: ...
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1answer
65 views

How to analyze data once broken down into gender, race, etc

I have two conditions, Treatment A, and Treatment B. Participants are randomly assigned to a treatment at the outset. Then I run unpaired t-tests on the data to find any differences. BUT I am also ...
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0answers
31 views

Post-hoc multi-level design analysis

I am developing a model to predict a dichotomous satisfaction measure on festival event participants. Events can last 1 to n days; and participants are grouped in parties of 1 to k party members who ...
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1answer
57 views

Metafor rma.mv function: missing estimates for two levels of a categorical moderator

I am conducting a meta-analysis with several categorical moderators and one continuous moderator; I am also interested in an interaction between two of the moderators (outcome and scale). I have ...
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3answers
45 views

Multilevel modeling for limited dependent variable

I am doing the research, using Multilevel modeling, with limited dependent variable number of days- it is limited downward (0) and upward (30). Is it necesarry to use Multilevel logit model? Or is it ...
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0answers
43 views

Testing for effect of covariate in nonlinear mixed model, T-test or F-test?

I am using package nlme for nonlinear mixed model. I use SSlogis self-starting model( Bates Pinheiro, 2000) for my model. ...
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1answer
46 views

Is it correct to use multilevel models when observations are nested by individual?

I know only the basics of multilevel modeling. I'm trying to measure the relationship between one paired set of questions to another set. A simple example, one set of questions might be, "How funny ...
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0answers
25 views

In Stata, how do I test for interaction of categorical variables in multilevel models?

I'm trying to figure out a way to test for interaction between variables in three level model. Using example Stat dataset we can have a dummy model with states nested into regions: ...
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0answers
4 views

Parafac for crossover design studies

.Hi, everybody I have data that has 28 subjects involved in a crossover design study including 4 different treatments. The amount of variables is over 10000 (measured almost on the same scale) In ...
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0answers
10 views

how to specify the order of repeated measure of same subject in multilevel modelling

I am trying to do multilevel modelling for finding the management of diabetes in 100s of patients using R (lmer). Each patient has multiple measurements of blood glucose which is taken in unequal ...
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0answers
100 views

When and why do I have to use “trait” for multinomial multilevel models with MCMCglmm in R?

I want to estimate a multilevel multinomial logit model but I am struggling with the terminology and notation used by the R-package MCMCglmm. There is documentation ...
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3answers
53 views

Whether to use a hierarchical linear model

I've been reading through Gelmans book: Data Analysis Using Regression and Multilevel/Hierarchical Models trying to learn more about how to implement hierarchal models. I have a dataset that I think ...
6
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1answer
241 views

Estimating Multilevel Logistic Regression Models

The following multilevel logistic model with one explanatory variable at level 1 (individual level) and one explanatory variable at level 2 (group level) : ...
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0answers
18 views

What is the “variance component parameter” in mixed effect model?

On page 12 of Bates' book on mixed effect model, he describes the model as follows: Near the end of the screenshot, he mentions the relative covariance factor $\Lambda_{\theta}$, depending on ...
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0answers
16 views

Mixed models with repeated measures

I am using mixed model for analysing a two level model where level 1 are the occasions (years) and level 2 is team (NBA teams). My IV is at team level and I have no reason for expecting different ...
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1answer
33 views

Interactions between levels in lme4

We are implementing multilevel models in lme4 and have a question about how to handle cross-level predictors. This is a psychology experiment where individual participants come into the lab and ...
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0answers
7 views

Analyzing specific factor combinations

Is there any way to isolate specific treatments and test those for differences within an overall multi-factor model? I'm running a multi-way ANOVA. For my particular model, I have factors with ...
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0answers
26 views

Multiple dummy variables and hierarchical models: interpretation of intercept

I have two variables, race and marriage, that I have created dummy coding for. I know that typically the intercept ($\beta_0$) is interpreted as the default level (level 1) for one variable. How do ...