Refers to a class of models developed to account for correlation that may occur within nested data.

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3answers
29 views

Test for effect of groups in a mixed effects model

This model is a simple linear regression: mtcars_lm <- lm(mpg ~ wt, mtcars) And this model adds cyl as a random effect: ...
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0answers
18 views

Mixed models (lme4) + lsmeans to estimate trend in population means

I aim to estimate one populations mean blood pressure during different years. Here is the setting: (1) 7400 onservations; repeated measurements. Unbalanced. (2) measurements are undertaken anually ...
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1answer
15 views

Complex level 1 variance mixed effects models in R

Take this mixed effects model in R: $y_i = \beta_0 + \beta_1X_{ij} + u_{j} + e_{ij}$ where $u$ is a random effect (level 2 residual) with groups $j$. It is possible to allow the variance of $e_{ij}$ ...
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0answers
17 views

Degrees of freedom for a 3x2 mixed ANOVA

I want to report the results of a 3x2 (system x task) mixed ANOVA. System is a between-subject factor with 3 levels, while task is a within-subject factor with 2 levels. For one of the independent ...
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0answers
15 views

Understand mixed models SPSS

On a mixed model on SPSS I got the following results: in the table called "Type III Tests of Fixed Effectsa" ...
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0answers
13 views

Meta analysis on multiple endpoints and unknown covariance

I am doing meta-analysis on intervention studies on human subjects where a number of measures were obtained before and after the intervention in a treatment and a control group. We categorize the ...
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0answers
17 views

Linear mixed models

I have some spatial measurement for two quantities, x and y. y is my dependent variable that I am looking to build a linear mixed effects model.Each point in space (lat,long) has one value of x, for ...
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0answers
18 views

Is this interpretation of mixed ordinal logistic regression correct?

I am doing mixed ordinal logistic regression using clmm function in ordinal package. Before running the clmm model I have changed my DV into ordinal variable using: ...
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0answers
19 views

Auto-correlation vs. number of observation periods

I've just read an excellent post mix model I've a question connected to that. Roland, can you recommend any reference to a comment that if one have not enough observation periods then it is ...
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0answers
12 views

Is there any possible method to calculate effect size in SPSS mixed model?

I run MIXED command for mixed model analysis of repeated measured data. However, there is no option or menu for estimate power(like partial eta in GLM) in mixed analysis. Is there any method to ...
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1answer
28 views

Modeling error structure in lmer in R?

Is it possible to add a parameter to lmer model which will be modeling the error structure? Sth similar to TOEP(X) and SP(POW) from SAS???
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0answers
12 views

Confidence intervals for multinomial mixed models

I am using the ordinal package in R to create a multinomial mixed model using the clmm2 function. However, I cannot find a way to get confidence intervals for the coefficients; confint() does not work ...
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2answers
127 views

Do the residual plot and QQ plot look normal?

I am doing linear mixed model and would like to check the assumptions using residual plot and QQ plot. Here is my code: ...
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0answers
14 views

Nonlinear mixed effects model proportion data

I'm working on proportion data (clutch success: number of hatch eggs over total clutch size) which is non normally distributed. I would like to fit a nonlinear mixed effects model with 6 fixed effects ...
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0answers
155 views

Linear mixed models or not?

We did a study with a course participants where we have one outcome variable and several metrics calculated for each message they posted on a discussion forum. Basically, the data are structure in the ...
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1answer
30 views

Linear Mixed model, number of observations per group

I am trying to fit a mixed model with about 45 groups, about 10 of the groups have just one observation and about 10 groups have more than 5 observations. The total number of observations is around ...
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0answers
19 views

Mixed logistic model with complete separation

I want am trying to produce a mixed logistic model but certain explanatory variables suffer from complete separation. I am aware that I need to either use exact logistic regression or a firth ...
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0answers
14 views

MIDAS Forecasting in R, using midasr package

I am attempting to provide a forecast on yearly data using monthly data as a regressor variable via the MIDAS regression from the midasr R package. Here is my data: y is yearly data ...
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1answer
42 views

Random-effects probit model

I am currently using a mixed binomial model with the following specification in a paper I recently submitted (using lme4): ...
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0answers
11 views

Use of Proc Mixed to find if product version has effect of its sales

I would like to confirm what I am doing is correct or not. I have the following data: Day Units sold (Var = Units) Number of stores in which the product was sold (var = stores) Version of the ...
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0answers
44 views

In R package lme4, how do you force the random slopes and intercepts to be uncorrelated for an interaction term?

I have a mixed model, fit using lmer in R, that has three interaction terms (X1:X1, X1:X3, ...
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1answer
33 views

Linear mixed effect model with repeated measures using lmer

Background I think I am close to the error structure I want for random effects but not sure about some parts of it. I am carrying an experiment on wheat plots in a field to measure the increase in ...
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1answer
39 views

Specification of Mixed Model

I have very big experiment with 70 places around country. In each place there are several experimental plots where measures have been done. There were several measurement occasions during last 50 ...
4
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1answer
43 views

How many levels in multilevel modeling is too many?

This is pretty general, but what are the pros and cons of including additional levels in multilevel model (linear mixed model)? I have a data containing information on multilevel administrative ...
2
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1answer
74 views

Obtaining conditional distribution from mixed model

Suppose you have the following mixed model: $$y_{it} =X_{it} \beta + Z_{it}b_{i} + u_{it} \tag{1}$$ where $y_{it}$ is the response for a subject $i$ and time $t$, $X_{it}$ is a vector of features, ...
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1answer
23 views

How to deal with a response variable calculated from added percentages

I am analyzing a data set where the response variable is the total non-native plant cover within a plot. There are non-native grasses and non-native herbaceous plants with overlapping canopies, so the ...
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1answer
35 views

Are level 1 and level 2 residuals in a mixed effects model always normally distributed?

Take this mixed effects model: $y_{ij} = \beta_0 + \beta_1X_{ij} + \mu_{j} + \epsilon_{ij}$ The level 2 residuals are $\mu_{j}$ and the level 1 residuals are $\epsilon_{ij}$. As I understand the ...
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0answers
24 views

$R^2$ for mixed models = ICC?

I will be referring here to Nakagawa and Schielzeth (2013). As those authors state, $R^2$ for OLS regression could be defined as follows: $$R^2 = \frac{\sum^n_{i=1}(\bar{y} - ...
2
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1answer
46 views

Non-linear model in lme4

I'm about to attempt to fit a non-linear mixed effects model $(A + B*e^t)$ in lme4. I've already tried fitting this model in nlme with some difficulty due to noise within the data. However, I ...
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1answer
29 views

Acceptable values for variance, aic and bic in multilevel models

I'm building a multilevel model from a sample of 820 observations at level 1 and 11 groups (level 2). I'm using stata xtmixed. Running the empty model (including ...
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0answers
22 views

R lmer Model Diagnosis qqnorm

I fitted this lmer model: m1 <- lmer(logR ~ N_g.m.2 * Year + (1|Wh/N_g.m.2), data = CO2_Ratio) Rendering the attached qqplot. ...
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2answers
38 views

different definition of compound symmetry in SAS

I have two questions about the covariance structure in SAS (proc mixed). I realize the compound symmetry structure in SAS allows the covariance term to be negative. This is different from the ...
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0answers
30 views

nlme estimates near zero variance for the random effects

I am doing various analysis on a small sample. Basically, we have an experiment where 14 subjects (UID 1 ~ 14) used one of the 6 instruments (MID 1 ~ 6) on 3 occasions (Sequence 1 ~ 3). Each time an ...
7
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2answers
95 views

How should I model interactions between explanatory variables when one of them may have quadratic and cubic terms?

I'm sincerely hoping that I have phrased this question in such a way that it can be definitively answered--if not, please let me know and I will try again! I should also I guess note that I will be ...
2
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0answers
16 views

Linear mixed model construction validation

I have 6 groups of fish made up of 8 individuals. Each group is tested three times under different treatments. These group level treatments are hungry , ...
3
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0answers
46 views

Recommendation for books/notes for linear mixed effect models for longitudinal data?

I'm a beginner in data analysis who needs to learn (say in a period of 2 to 3 weeks or so) the key ideas and techniques in the linear mixed effect models for longitudinal data. I'll apply them in ...
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1answer
24 views

Mixed effects model for power function data

I have data which I suspect follows a power function over time. It is collected from several units which have different intercepts. Therefore I'd like to do a mixed model with the parameters of the ...
1
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0answers
48 views

GEE as alternative for Linear Mixed Models

A linear mixed model requires the residuals to be normal. In the case of a simple linear mixed model with a random intercept only, a colleague of mine was arguiing that I could just use a GEE with an ...
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0answers
13 views

Adjusting for Baseline values

In a RCT setting where we have 1 treatment group vs 1 placebo, we want to investigate the effects of the active treatment to a particular lab result. If we have the results for the baseline lab exam ...
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0answers
39 views

Identifiability issues for linear mixed models with cross-classified data

I have a dataset that could be easily simulated like this: ...
4
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1answer
137 views

How to formulate linear mixed model to find out effects of continuous variables?

I have a dataset with growth rate as a response variable (resp in the example) and temperature, food availability, and salinity as predictor variables (...
1
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1answer
24 views

HMMFit underlying algorithms

After reading article "Hidden Markov Models for Controlling False Discovery Rate in Genome-Wide Association Analysis" by Zhi Wei I am trying to use it in my project. I am using R and I have found out ...
2
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1answer
56 views

Difference in 2 groups when group assignment is not certain

Suppose you have two groups and you want to see whether these two groups differ in regards to some variable. This sounds like a basic t-test or perhaps non-parametric Wilcoxon rank sum test. Suppose ...
0
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0answers
77 views

Residual Diagnostics and Homogeneity of variances in linear mixed model

Before asking this question, I did search our site and found a lot of similar questions, (like here, here, and here). But I feel those related questions were not well responded or discussed, thus ...
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0answers
12 views

Repeated measures in GLMM

I have a dataset in which individuals in some plant populations were measured over 3 consecutive years. My response variable is the reproduction of each individual. My fixed effects involve: one ...
0
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0answers
15 views

Confidence interval for the response in glm with mixed effects?

I am fitting a mixed effect glm with binomial distribution. My model has 2 predictive variables, one grouping (with tree categories) and one continous. So my model is like this: $y_{ij} \sim ...
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0answers
31 views

Estimating regression parameters separately for each subject

It seems to be a relatively common approach in some fields to, for a linear relationship which is subject to individual differences, estimate regression parameters separately for each subject in an ...
1
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1answer
24 views

mix model for averages or for raw data

I have classic block design of the experiment. There are blocks and treatments, and several observation within. The experiment is unbalanced thus I want to use mix models to analyze if the treatment ...
3
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1answer
61 views

Should the within-subject variability decrease?

I have a crossover experiment design, detailed as follows. there are 7 sites conducting the same experiment; In the experiment of each sites, 5 different treatments are administered to $n_i, \, (i = ...
1
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1answer
11 views

Problem fitting a geeglm regression

I am fitting a model using geeglm in geepack and ran into a problem. I have a dataset pertaining to oil consumption and fit the below model. ...