Tagged Questions

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

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0answers
17 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
54 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 ...
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0answers
5 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 , ...
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0answers
28 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
16 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
28 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
9 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
22 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
114 views
+50

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 (...
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1answer
13 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
50 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
43 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
6 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
9 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
28 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
20 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
votes
1answer
58 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
10 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. ...
4
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1answer
181 views

R: equivalence between an aov between-within repeated measures model and an lmer mixed model

I have some trouble obtaining equivalent results between an aov between-within repeated measures model and an lmer mixed model. ...
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0answers
22 views

How do we calculate the $R^2$ statistic for a mixed model with one random intercept only?

I have read in previous posts that for mixed models with random intercepts only, the statistic for $R^2$ is $$R^2 = \frac{\text{V of intercept only model} − \text{V of full model}}{\text{V of ...
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0answers
24 views

How to analyse binary outcome data with between- and within subjects factors?

I am looking for the right statistical procedure to analyse my data (mixed design) with binary outcomes. Between-subjects variable: treatment (yes or no); experimentally manipulated Within-subjects ...
0
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0answers
6 views

Mixed models and Levels Impacting the Intercept

Can only a level 2 variable influence the intercept in a mixed model (with two levels)? Following the Singer 1998 article, say school is level 2, and student is level 1. So can only the school level ...
0
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1answer
15 views

Pretest-Posttest comparison

I am having a hard time doing this on Stata. I have a group of 32 students. All perform a pretest and are scored. Next, half of them are randomized to receiving an intervention and the other half ...
2
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1answer
81 views

Add a quadratic random effect to a nonlinear mixed model?

How can one add a quadratic random effect to a nonlinear mixed effect model? I've been trying to do this with nlmer without luck. Any tips would be greatly appreciated! Edit: as diagnosed by Ben, the ...
0
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1answer
39 views

Repeated measures ANOVA and uneven number of trials

Suppose I have multiple responses from each subject in three different conditions (A, B, C). If I would decide to run a repeated measures ANOVA, I would first average over the repetitions from each ...
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4answers
382 views

Unified view on shrinkage: what is the relation (if any) between Stein's paradox, ridge regression, and random effects in mixed models?

Consider the following three phenomena. Stein's paradox: given some data from multivariate normal distribution in $\mathbb R^n, \: n\ge 3$, sample mean is not a very good estimator of the true mean. ...
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1answer
42 views

Extracting slopes for cases from a mixed effects model (lme4)

I would like to extract the slopes for each individual in a mixed effect model, as outlined in the following paragraph Mixed effects models were used to characterize individual paths of change in ...
4
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1answer
133 views

Can anyone provide a peer reviewed reference for the calculation of least squares means as implemented in the R package lsmeans?

I am using the lsmeans package from the R programming language for follow up analyses of a linear mixed model. However, my target journal does not generally use these methods and I would like to have ...
0
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1answer
44 views

estimating LMM with r

Suppose I have a model $$\begin{bmatrix}y(1)\\y(2)\end{bmatrix} = \begin{bmatrix}\mu \\ \mu \end{bmatrix} + \begin{bmatrix}\Lambda \\ \Lambda\end{bmatrix} + \begin{bmatrix}\varepsilon(1)/\rho_1\\ ...
0
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0answers
10 views

Proc Mixed for a random slopes model - contrast the slopes?

I have a need to make predictions about a set of students $^1$ who are nested under teachers, under schools, under districts. I have produced the below model, and I now wish to do some forecasting at ...
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1answer
46 views

Using the same variable as a fixed and random effect in Mixed Effect Models

The experiment this data comes from an experiment where two people collaborate to put objects in a specific order. The Direction has the target array on their screen, and the Matcher has a scrambled ...
1
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0answers
24 views

Assumptions for nlme

I want to analyze a repeated measure design with two independent variables (var1, var2) where the subjects had to solve three ...
2
votes
1answer
43 views

lme4: profile takes lot of time for a complicated model

I have a pretty complicated mixed model (cross classified data) and a pretty large dataset (>700000 obs.). The lmer function took few hours to compute, but profile takes over two days and is still ...
0
votes
0answers
13 views

Standard errors of estimates in multi factorial LMEM

This question may already be well-answered as it seems relatively straight forward, but my search of existing posts has failed... apologies if it is redundant. I am building a linear mixed effects ...
0
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0answers
12 views

G and R matrices in mixed model and model selection

I have data in which the plants were subjected to four conditions and measured weekly for a month. I would like to incorporate "plot" as a random factor into my linear mixed model using SPSS. I am ...
2
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0answers
21 views

Data analysis : replication, pseudoreplication and mixed models

I have several questions concerning analysis of data, especially when there are replications and/or pseudoreplications. First, I read an example in « pseudoreplication is a pseudoproblem » where we ...
0
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0answers
25 views

mixed effect regression model

I would like to expand over a previous question of mine (What is the correct model for this experiment design?), with slight modifications... To set up the scene : We have a completely randomized ...
0
votes
0answers
37 views

Determine the causes of change in time with mixed models

I have a database with several continuous variables measured in two times. I searched for a change in time in my dependent variables in this way: ...
1
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0answers
27 views

Assumptions of Linear Mixed Model

I had data with repeated measurement and nested design. Conventional ANOVA requires strict control on homogeneity of variance and repeated measurement ANOVA requires assumption of sphericity. ...
0
votes
1answer
53 views

ANOVA - when homogeneity of variance is violated

My data was a repeated measurement (3-4 measuring times) with one fixed factor (4 doses) and nested (Please find an example below). I would like to ran ANOVA but the assumption of homogeneity of ...
0
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0answers
13 views

Error using “cengaussian” family with MCMCglmm

I'm trying to run a model using a cengaussian family distribution with the function MCMCglmm. The model is: ...
1
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0answers
32 views

How can I model this problem?

Genetic algorithms are a kind of evolutive approach to problem solving where solutions are randomly generated and crossed with each other as to produce other solutions. With each generation or ...
5
votes
1answer
136 views

What is the meaning of $\oplus$ and $\otimes$?

I am struggling to fully understand some notation in a book where they use a "crosshair" symbol - first like $\bigoplus\limits_{i=1}^n{} Z_j $ where the $Z_j$ are matrices and second like $I_n \otimes ...
0
votes
0answers
11 views

How to take care of the percentage/rate of an absolute number as independent variable?

I am working on a mixed model, where suppose I have several stores of different sizes. The number of products manufactured in each store is different, say one store can manufacture 100 and other can ...
2
votes
1answer
90 views

Mixed effects model with repeated measures

I was trying to work out this on my own but I find myself overwhelmed. I am looking at the amount of moisture present in forest fuels (FMC) following forest thinning. Forest fuels are classified by ...
0
votes
0answers
31 views

Correlations of fixed effects in logit mixed model with a nested fixed effect

I am using lme4 in R to fit a logistic mixed effects model of psycholinguistic data with three categorial (binary) fixed effects and two crossed random factors (subjects; items). The critical ...
1
vote
0answers
9 views

Testing hypothesis about the location of the maximum point on a curve

I have data from an experiment on the relationship between PPI (the dependent variable, a measure of startle reflex attentuation by weak stimuli) and SOA (the main independent variable; it's the time ...
1
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2answers
120 views

Getting P value with mixed effect with lme4 package

I have problem with getting p value from my mixed model, library(lme4) ...
0
votes
1answer
46 views

Linear regression or mixed effects models for data with two time points?

I have a dataset in which individuals were assessed at two time points during the study on a cognitive test, as such I was wondering which statistical model would be more appropriate for my data, ...
0
votes
1answer
44 views

Does it make sense to add random coefficients to a fixed effects (fixed-intercepts) model?

If you have panel data, and you fit a model like $$ y_{it} = \alpha_i + X_{it}'\beta + \epsilon_{it} $$ then you have $E[\hat\beta] = \beta$ if you can make an argument that $E[\epsilon]=0$. This is ...