1
vote
0answers
5 views

How to model non-linear, linear and crossed random effects in one model

I have a model with fixed and crossed random effects like this: glmer(response~1+var1+var2+var3+var3^2+(1|var4)+(1|var5)+(1|var6), family="poisson") Now, I decided that variable3 is best modelled ...
11
votes
1answer
135 views
+150

Invalid inference when observations are not independent

I learned in elementary statistics that, with a general linear model, for inferences to be valid, observations must be independent. When clustering occurs, independence may no longer hold leading to ...
2
votes
2answers
50 views

comparing non nested models with AIC

say we have to glmms mod1 <- glmer (y ~ x + A + (1|g) data= dat) mod2 <- glmer (y ~ x + B + (1|g) data= dat) These models are not nested in the usual sense ...
0
votes
1answer
22 views

R- predict payment day (1-31)

I need to predict payment day of the month (1-31) for each client (I have at most 9 month of payments and on average is 5). I have both categorical variables and numerical. I tried to use rpart to do ...
0
votes
0answers
16 views

Two-way Repeated Measures ANOVA with replicated measures

My experiment involves 16 participants with a dependent variable (PP) tested under 2 conditions, across 3 different time-points. At every time-point, each participant is tested twice. My data is ...
0
votes
0answers
40 views

repeated measures ANOVA, crossover trial, R

I am sorry for stating such a question. Unfortunatelly, it's very-very hard to go through all statistics. I have a crossover study design with 3 treatments, 3 periods, and a baseline (covariate). The ...
2
votes
1answer
82 views

Mixed, repeated measure model specification and results interpretation using LMER in R

I am working with data from a computer task which has 288 total trials, each of which can be categorically classified according to Trial Type, Number of Stimuli, and Probe Location. Because I want to ...
2
votes
0answers
51 views

Multiple correlated random non-nested intercepts in R

I am trying to estimate a longitudinal model in R in which there are several random intercepts that are correlated with each other, and the data are non-nested. For example, consider a simple ...
3
votes
1answer
48 views

What is the null model for a likelihood ratio test of a within-subjects factor?

Tissue samples were taken from 4 differention locations and repeatedly measured. This was done identically for 3 animals. The research question was: Are there differences in measurement between the ...
1
vote
1answer
31 views

AICc and K for categorical factors and interactions

I am new to multimodel inference. I am trying to create a model that has multiple categorical factors and possible interactions. For example say that my model is... Y ~ X1 + factor(X2) + ...
0
votes
0answers
18 views

Identifying the number of conditions by which variance components will be divided in Generalizability Theory using QME R package

I'm using QME R Package (can be downloaded from here) to calculate Generalizability ...
0
votes
0answers
28 views

To get the overall significant p value, am I on the right track for LMM?

According to this document: http://www.bodowinter.com/tutorial/bw_LME_tutorial2.pdf I can get the overall p-value of fix effects by comparing models that I would like to know to null model. In my ...
1
vote
0answers
22 views

Mixed effect models: Why are variance components incongruent with predictive power in presence of hidden interactions?

I have noticed that if there are interactions between hidden variables not in the model, then the variance estimates are inflated greatly compared to the predictive power of the model itself, and I'm ...
2
votes
0answers
40 views

One inflated beta regression with random effects using GAMLSS

I am new to modelling percentage data, and I would be greatfull for some advice. I have proportion data (0,1] on a percentage of money sent by Player B to Player A. Participants received an amount of ...
0
votes
1answer
55 views

Random effect significance in linear mixed model

I have performed LRT: ...
3
votes
1answer
64 views

Design of matrix of contrasts in R

I am doing some post-hoc comparisons (in lme4, but here I'll just present a simple linear model), and I am having a hard time making sure that I am building the right matrix of contrasts to test ...
1
vote
0answers
23 views

Specific contrasts in mixed model with interaction

I have a dataset consisting of two groups tested across three days. Therefore I run a linear mixed model as follows: ...
1
vote
1answer
67 views

Mixed models with R - convert from SAS code

I have this SAS code running a mixed model: ...
2
votes
0answers
49 views

R model.matrix and makeContrast. Understanding model and possible contrast

I have measurements from 12 mice, grouped in two conditions. I each mouse I have measurements from 4 tissues. The design is not balanced, 5 mice in condition1 and 7 in condition2. After reading the ...
1
vote
0answers
21 views

expected values determined with model parameters estimated from a nlme analysis

I'm kind new into nonlinear mixed model theory and I've seen that you cannot determine expected values of your response variable by simply inserting the estimated parameters into your model equation, ...
1
vote
1answer
62 views

Mixed model interaction (covariate+factor): How to interpret posthoc table output in R package phia?

In R, using package lme4, I have used the following 2 mixed models to determine I have a signifacnt interaction between a covariate (continous, normally distributed) and a factor (three levels: ...
0
votes
1answer
52 views

After trying various optimzers, model simplification running more iterations, when fitting GLMMs, R still produces warning messages

I am trying to fit GLMM's to my data using the glmer function available in R's lme4 package. The data is available at: https://onedrive.live.com/redir?resid=1B727FC7180E87DF%21118 I keep getting ...
0
votes
0answers
46 views

Mixed linear models in R, help with nested terms and procedure

This is my first post, so sorry if it not optimally written. I have a paired samples at two time points in two groups, undergoing the same intervention. I want to test the effect of my intervention on ...
1
vote
1answer
66 views

Specifying a linear mixed model in lmer with replications nested within a fully crossed design

I’m trying to specify a linear mixed model for a somewhat complicated, nested & crossed method comparison study with replicated measurements. The goal is to partition and compare variances. It’s ...
0
votes
1answer
78 views

Number of observations in groups - linear mixed effects model

I would like to fit linear mixed effects model to my dataset, but I was wondering if quantity of observations in groups matter? I have some groups with about 60 observations in each, but there are ...
2
votes
0answers
30 views

Calculating means and confidence intervals for groups with multiple observations in each subject using the NLME package in R

I need your help to identify group means and calculate the corresponding 95% confidence intervals for a set of independent samples with 2 dependent observations within each of those samples. I'm using ...
0
votes
0answers
66 views

How to test signicance of differences between factor levels in mixed model using lme4 in R

My basic knowledge on model simplification comes from Crawley (2007) and I have also looked in Zuur et al Mixed Effects Models and Extensions in Ecology with R to try to answer my question. In ...
0
votes
1answer
84 views

Calculating $R^2$ in mixed models using Nakagawa & Schielzeth's (2013) R2glmm method

I have been reading about calculating $R^2$ values in mixed models and after reading the R-sig FAQ, other posts on this forum (I would link a few but I don't have enough reputation) and several other ...
1
vote
0answers
41 views

Multiple covariates for each fixed effect

I'm analyzing data from a classical intervention design. Subjects were divided into groups, undertaking different interventions. Each subject was measured using the same tests before and after the ...
0
votes
2answers
42 views

Convergence errors in parametric bootstraps (PBmodcomp) of lmer models

I am using PBmodcomp from the pbkrtest to perform a parametric bootstrap model comparison. However, for some of the comparisons a warning message stating that the models failed to converge appear. A ...
0
votes
0answers
10 views

analysing multiple individuals in specific time points for similarities

I am looking for a suitable analysis to examine my data for the presence of foraging individuals at different time periods, and whether the individual are in the same place over time. My dataset is ...
1
vote
1answer
97 views

mixed effects model output

Let's say we have this: ...
22
votes
2answers
427 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
67 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
22 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 ...
2
votes
1answer
49 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
75 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
38 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
34 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 ...
1
vote
1answer
90 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 ...
4
votes
1answer
132 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 (...
2
votes
2answers
86 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
35 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 ...
0
votes
1answer
76 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 ...
6
votes
1answer
121 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
54 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
68 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 ...
4
votes
1answer
123 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
17 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
1answer
40 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 ...