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

learn more… | top users | synonyms

5
votes
0answers
45 views

How scared should we be about convergence warnings in lme4

If we a re fitting a glmer we may get a warning that tells us the model is finding a hard time to converge...e.g. ...
1
vote
0answers
33 views

including interactions in a mixed linear model in R (lme)

I'm trying to test for the effect of soil moisture on transpiration rates. I have plot-level data for 18 plots in 6 different stands of trees (3 plots x 6 stands). I want to treat "stand" as a random ...
0
votes
0answers
17 views

Assessing the effect of related variables using lmer in R

I am trying to run a model to describe the rate of water table drawdown in the soil. The predicted variable is rate, and I am interested in the effect of two categorical variables: (1) if the water ...
1
vote
0answers
32 views

How to fit a longitudinal model with binary outcomes

I'd like to fit a longitudinal model for where multiple subjects experience binary outcomes over time. To accomplish that, I'd like to use an additive random effect for each subject and an ...
2
votes
0answers
20 views

Correlation fitted-residuals in mixed models

IN OLS linear models, fitted (predicted) and residuals scores are uncorrelated. I was under the impression that the same held true in mixed models. However, I have here an example model where fitted ...
2
votes
1answer
28 views

conducting multi-level regression on ordinal DVs with imputed data in R

Do you know of an approach/package that facilitates mixed model regression of ordinal dependent variables on multiply imputed datasets in R? Ideally, the function takes: a list of multiply imputed ...
0
votes
0answers
15 views

Compare LMM GLMM (generalised linear mixed model, negative binomial) by numerical measure (AIC BIC, cross validation, R² squared) for model validation

How to compare results of generalized linear mixed model (GLMM, negative binomial) with a log transformed linear mixed model (multilevel, hierarchical) . I have a data set (counts), which is nested. ...
0
votes
0answers
27 views

R² (squared) from a generalized linear mixed-effects models (GLMM) using a negative binomial distribution

I try to compute the marginal and conditional R² for a GLMM using a negative binomial distribution by following the procedure recommended by Nakagawa & Schielzeth (2013) . Unfortunately, the ...
1
vote
1answer
16 views

Calculated breeding values using markers using animal model in R

Animal model (frequently used in animal science and sometime in human or plants) is mixed model with: $y$ = $X$$b$ + $Z$$u$ + $e$ y is observed values for any quantitative variable, $Xb$ is fixed ...
0
votes
0answers
20 views

center variable separately for each factor in linear mixed model?

I am working on a relatively simple mixed model where I have two continuous predictors with an interaction term and three sites. I am treating the two predictors as fixed effects and the site as ...
0
votes
1answer
28 views

Experimental design and mixed models

I want to test effect of 3 PH on larval development. I would like to know what is the best experimental design and statistical analysis. We can only use 3 compartments of sea water, each one with a ...
1
vote
1answer
45 views

Multivariate model in lme() with independent random effect, similar to MCMCglmm

I would like to specify a multivariate model with lme with a random effect for group which is independent across variables. I found this post, which explains that ...
3
votes
0answers
44 views

Mixed effects modelling; what to do when model is over-specified?

I'm trying to use mixed-effects modelling to analyse some data. There are a number of variables that I need to specify within the model, two of which are between-participants (...
0
votes
0answers
13 views

Fitting a Mixed Model with Random and Repeated effects in SAS

I have want to fit a linear regression with repeated measures and random effects. The data come from clinical observations. In CT images The dependent variable is the diameter of a lymph node lesion ...
2
votes
2answers
62 views

What is the right way to analyze a nested design in R?

I know that there are already a host of questions about nested designs but many of them haven't been answered or come from biological domains which I sometimes find hard to transfer to my domain. I ...
0
votes
0answers
26 views

Demand Forecasting : Montecarlo Simulation

I am trying to build a demand forecasting model for human resource team. I have thought of using monte carlo simulation method to do it. Is it the right technique for it? Has anyone used it to ...
1
vote
0answers
22 views

How to do a power analysis for an unbalanced mixed effects ANOVA?

I need suggestions for how to calculate the $n$ required for 80% and 90% power for >30% change from baseline ($T_0$) at $T_1$ or $T_2$, drug vs. placebo, 2:1 ratio; 20% CV in test; factors: subject, ...
0
votes
1answer
50 views

How to compare models from different but related datasets?

I'm building regression models on four the different but related data set and at the end, I want to test the significance of models. Since my models are built in a different data set, it's not ...
0
votes
0answers
29 views

How to model non-linear time courses with nlme

I have some time course data which plotted looks like this: I am trying to fir a model to it using nlme.lme(). I am interfacing with R via RPy, and using the ...
1
vote
0answers
22 views

How to apply the random statement in my model?

i am trying to model the following data in SAS using proc glimmix and i would like feedback if i have modelled my data correctly. My data consist of individual chickens (ID) who are grouped by ...
0
votes
1answer
39 views

Repeated-measures, crossover analysis using linear mixed model in R

I have a data set that I am attempting to analyse in R and I am relatively new to the environment. My full data set contains 7 subjects (represented by Subject), that all receive 3 treatments ...
1
vote
1answer
42 views

The 'best' model selected with AICc have lower $R^2$ -square than the full/global model

I have used the R lme function (nlme package) to construct linear mixed models, with a single random effect (as a random intercept) and a varIdent variance structure on a fixed effect (that is a ...
6
votes
1answer
96 views

Relationship between paired t test and simple mixed model

The bounty I placed on this question expires in the next 24 hours. I have a psychological data set which, traditionally, would be analysed using a paired samples t test. The design of the ...
0
votes
0answers
25 views

Proc Mixed statement

Suppose I have a data set: ...
0
votes
0answers
47 views

Help with lmer in the lme4 package

I am new to using linear mixed models and would greatly appreciate any help I can get. I have an equation of the form $ y = X\beta + Zu + \epsilon$ where $u$ is a random effect whose covariance ...
1
vote
0answers
26 views

Understanding repeated covariance types in SPSS?

I am working in SPSS on a repeated measures linear mixed model and I am having a really hard time wrapping my head around how to select a "repeated covariance type". The options are: ...
0
votes
0answers
11 views

How to get/calculate confidence intervals for slopes of the continuous*categorical interactions?

Not sure if this should be in Stack Exchange or here, but here goes. I have a linear mixed model in SPSS, and I want the confidence intervals for slopes of the continuous*categorical interactions. ...
1
vote
1answer
39 views

How to perform a meta regression with a random effect model?Which model should I use?How to start? (beginner)

I have to perform a meta-regression, using mixed or random effects model, but I don't have any software (except Matlab) and I'm new on this topic (having a relativelly poor statistics background). ...
0
votes
0answers
34 views

Within-subject and between-subject fixed effects in mixed model

I've been trying to analyze some data using mixed models but I have some troubles to understand how should I include both within-subject and between-subject fixed effects in such models. Let's ...
0
votes
0answers
8 views

Negative Binomial Mixture in PyMC [migrated]

I am trying to fit a Negative binomial mixture with PyMC. It seems I do something wrong, because the predictive doesn't look at all similar to the input data. And the predictions for the parameters ...
0
votes
0answers
26 views

MANOVA for mixed model with multiple repeated measurements

I struggle performing a MANOVA for a mixed model. I have the following columns: S - subject (1,...,N) B - in between group (B1, B2) W - repeated measurement - within (W1, W2) M - measured dependent ...
1
vote
0answers
19 views

How to model a multiplicative effect of a parameter

I am having difficulty in fitting a model on data. Basically, I have data about the evaluation of phenotypic property (i.e. hard) of 65 palm trees by 5 judges. As an evaluation scheme, each judge ...
4
votes
1answer
78 views

Longitudinal item response theory models in R

I'm trying to fit longitudinal item response theory (IRT) models in R. I have a test that was administered at multiple measurement occasions. I'd like to examine individuals' growth curves of factor ...
0
votes
0answers
12 views

Modeling paired data: Philosophical difference between using mixed effects model and using grouping-variable-level outcome

I am facing a problem of detecting change in infection rate after surgery in about 400 eye surgery patients. Crucial medical background includes the following-- About 30% patients have both eyes ...
1
vote
1answer
38 views

Interpreting the mathematical formula of a mixed effect model

I am a bit confused about the function of a parameter in setting up a linear mixed effect model (hierarchical/multilevel model). This is how I understand a (random intercept and slope) multilevel ...
0
votes
0answers
6 views

MLR equivalent for repeated measures, multiple correlated responses

I'd like to determine the best approach to determining effect sizes for a set of experimental data with multiple correlated responses. Due to repeated measurements and high correlation between ...
2
votes
2answers
76 views

mixed model: is it primarily used for prediction or explanation or both?

Inspired by this post on the difference between explaining and predicting. I want to ask is mixed model primarily used to get better explanation (such as, but not limited to, getting better ...
1
vote
0answers
41 views

Comparing slopes in mixed-effect model

My data looks like the attached picture. The dependent variable indirectly measured physical activity. I tried to use mixed-effect model rather than RM Anova, because my actual data is imbalanced. ...
0
votes
0answers
14 views

Site effect in GAM model

I am trying to build GAM model to see the effect of several environmental variables on the total abundance of one species. I have collected samples from three sites with three replicates from each ...
0
votes
0answers
26 views

repeated measures ANOVA - non-experimental data

For every year, for eight years, I have a set of projects (n=332). The number of projects that exist in each year varies (for example, some years there are 10 projects others there are 60). In each ...
0
votes
1answer
38 views

fitting LMEMs for repeated measures with no correlation between intercept and slope

For a simulation study, I contrast the power of different LMEMs for repeated measures. To get p-values, I use likelihood ratio tests where I compare a model including a fixed treatment effect with one ...
1
vote
0answers
21 views

Testing the random slope with correlated random effects

I have a mixed/random effects model $$\mathbf{y}_i=\mathbf{X}_i\boldsymbol\beta+\mathbf{Z}_i\mathbf b_i+\boldsymbol\epsilon_i,$$ where random effects $\mathbf b_i$ has variance-covariance matrix ...
0
votes
0answers
13 views

Choosing levels of random factor in a mixed model

My apologies in advance if this question is as much about experimental design as it is about statistics. I'd like to know if there is a "best" way to choose levels of a random factor in a mixed model. ...
0
votes
0answers
17 views

Split plot ANOVA or t-test

I did a study in which I wanted to see if a teaching intervention would have an effect on student learning. I nonrandomly divided students into two groups, a control and experimental group, and gave ...
1
vote
1answer
36 views

Hausman's test for all $\beta$s – comparing FE vs RE models

I fit several two level models in SAS using PROC MIXED: an empty model with multilevel structure (null), a model with a level 2 covariate (partial model), and a ...
1
vote
1answer
75 views

Random factor nested in two fixed factors

I have read Random effect nested under fixed effect model in R, but I have a doubt: My data is on germling survivorship, I have Temperature as a fixed factor (2 ...
0
votes
1answer
29 views

Fitted values of 'lme' function result

I fitted a linear mixed model with R as follows. ...
1
vote
1answer
44 views

SAS Proc Mixed model interpretation

I'm fitting a linear mixed model by SAS. There are 596 sectors and 8489 subjects. (each sector contains 10~15 subjects). Each subject is measured at most 6 times, so the total number of observation is ...
0
votes
0answers
24 views

MIXED modeling of 2 within-subject factors with 2 repeated factors and df

This is a novice question regarding MIXED models, denominator freedom degree, and long format (e.g., in SPSS). Most Mixed Model tutorials that I find address between factors and repeated measurments. ...
2
votes
1answer
61 views

Multilevel modeling: longitudinal data with within-subjects factors

I have a data set with experimental data that I am analysing with multilevel modeling. Data are structured as follows: 24 Sessions 6 Subjects per Session 10 Rounds per Subject There was one ...