Hello! I have a rather simplistic model which I have been using in SPSS that entails a general mixed effect model explaining a binary outcome. The professor offhandedly mentioned that if I should get this research published, I would want to use R instead of SPSS but she does not know how to work...
I am analyzing data from a randomized clinical trial, with 2 intervention groups (placebo and intervention) and repeated measurements over time. I am planning to use linear mixed effects modeling to analyze this longitudinal data and determine whether the intervention causes a change in response...
Hi to everybody,
I've just created four cross sectional models based on panel data with MIXED MODEL procedure.
Now I'd like to made a simultaneous equation models analysis.
Do you know how I can do it?
Do I need AMOS?
And if yes, does anyone know whether there is a specific tutorial...
Hi All,
I'm trying to run an nlme on some data looking at the nonlinear response (in this case 'distance', but will also use for 'weight') of individuals ('possum') over time (repeated measures, recorded weekly for 12 weeks = 'week'). There were 3 different 'treatment' groups. Other factors...
:wave: Help!
I have some data I am trying to analyze but was hoping to get some stats help with it. I'm not sure what the best way to analyze it is.
I'm interested in seeing if there is any effect of different dietary treatments on bacterial colonization and shedding in experimentally...
Hello, I am attempting to model Michaelis-Menten uptake kinetics to predict denitrification rates (response) across a gradient of nitrate loading (predictor) in four seasons (June, August, October, and December) using a mixed effects model. The basic models run well in the nls program in R and...
Mixed-effects models are wonderful for analyzing data, but it is always a hassle to find the best model, i.e. the model with the lowest AIC, especially when the number of predictor variables is large.
Presently when trying to find the right model, I perform the following steps:
1) Start...
I have a complex design and haven't found similar examples online. I'd really appreciate any views on the way I modelled it.
At a first stage, 19 editors improved the wording of 41 sentences - all editors saw all 41 sentences. At a subsequent stage, 3 judges assessed the quality of the edited...
A two-level model, with one explanatory variable at the individual level (X) and one explanatory variable at the group level (Z):
Y_{ij}=\gamma_{00}+\gamma_{10}X_{ij}+\gamma_{01}Z_{j}+\gamma_{11}X_{ij}Z_{j}+u_{0j}+u_{1j}X_{ij}+e_{ij}\ldots (1)
correlation between u_{0j} and u_{1j} is 0 .
The...
Is "getVarCov" of lme output gives variance-covariance of estimated "Standard Deviation" of random effects or variance-covariance of estimated "variance" of random effects .
library(nlme)
fm1 <- lme(distance ~ age, data = Orthodont)
VarCorr(fm1)
getVarCov(fm1)
That is ,
VarCorr(fm1)...
The following model assumes that the covariance between the random intercepts and random slopes across Subjects is Zero .
lmer(Reaction ~ Days + (Days||Subject), sleepstudy)
How can I write the same model by "lme" function under nlme pacakge assuming zero covariance between the random...
I am trying to fit a random slope model by "varComp" in R . For the following example , that is in "lmer" syntax , how can I write it in "varComp" syntax :
library(lme4)
library(varComp)
fm1 <- lmer(Reaction ~ Days + (Days||Subject), sleepstudy)
I am not understanding...
Hello,
I need some help with how to run a mixed regression with a random factor please!
I have a data set with 10 participants, who I conducted observations on multiple times (around 26 observations per participant), so in total I have around 262 observations. For each observation I have 2...
library(lme4)
fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
The notation `(Days | Subject)` says to allow the intercept and `Days` to vary randomly for each level of `Subject` .
Can you please explain me the result of the following commands ...
Hi , I have a two-level model with one explanatory variable (X) on the respondent level, and one group-level explanatory variable (Z) . I am following this paper http://joophox.net/publist/methodology05.pdf
I am simulating data from the model . Three conditions are varied in the simulation...
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) , they mentioned
" the variance of residual errors u_{0j} and u_{1j} is specified as...
How is the following code working ?
(fm1 <- lmer(angle ~ recipe * temperature + (1|recipe:replicate), cake, REML= FALSE))
In the formula of lmer :
What does 1 before vartical bar , (1|recipe:replicate) , indicate ?
How does "recipe:replicate" after vartical bar work ?
I...
I am trying to analyze a dataset where each subject has 12 repeated measures (quarterly, over 3 years). I want to extract subject specific estimates of the time slope to evaluate if the subjects are changing significantly over time.
The code I currently have consistently suggests that each...
Hi!
I am running a mixed effects models in spss and have found a significant interaction between session and sex. I now wants to examine the simple effects for sex and I've been trying the below syntax but keeping getting the following warning message:
"The symbol sex was found following...
I have a question regarding crating a graph displaying the fixed effects of a mixed effects model that I cannot seem to find an answer to. I am not sure what the correct approach is. For example, when graphing a standard non-mixed effects model (i.e. binomial glm;logistic regression), I used to...