random-effects

I'm trying to understand the function lmer. I've found plenty of information about how to use the command, but not much about what it's actually doing (save for some cryptic comments here: http://www.bioconductor.org/help/course-materials/2008/PHSIntro/lme4Intro-handout-6.pdf ). I'm playing with the following simple example: library(data.table) library(lme4) options(digits=15) n<-1000 m<-100 data<-data.table(id=sample(1:m,n,replace=T),key="id") b<-rnorm(m) data$y<-rand[data$id]+rnorm(n)*0.1 fitted<-lmer(b~(1|id),data=data,verbose=T) fitted I understand that lmer is fitting a model of the form

I am a bit confused about the output of Statsmodels Mixedlm and am hoping someone could explain. I have a large dataset of single family homes, including the previous two sale prices/sale dates for each property. I have geocoded this entire dataset and fetched the elevation for each property. I am trying to understand the way in which the relationship between elevation and property price appreciation varies between different cities. I have used statsmodels mixed linear model to regress price appreciation on elevation, holding a number of other factors constant, with cities as my groups

The qqmath function makes great caterpillar plots of random effects using the output from the lmer package. That is, qqmath is great at plotting the intercepts from a hierarchical model with their errors around the point estimate. An example of the lmer and qqmath functions are below using the built-in data in the lme4 package called Dyestuff. The code will produce the hierarchical model and a nice plot using the ggmath function. library("lme4") data(package = "lme4") # Dyestuff # a balanced one-way classiï¬cation of Yield # from samples produced from six Batches summary(Dyestuff) # Batch is

In lm and glm models, I use functions coef and confint to achieve the goal: m = lm(resp ~ 0 + var1 + var1:var2) # var1 categorical, var2 continuous coef(m) confint(m) Now I added random effect to the model - used mixed effects models using lmer function from lme4 package. But then, functions coef and confint do not work any more for me! > mix1 = lmer(resp ~ 0 + var1 + var1:var2 + (1|var3)) # var1, var3 categorical, var2 continuous > coef(mix1) Error in coef(mix1) : unable to align random and fixed effects > confint(mix1) Error: $ operator not defined for this S4 class I tried to google and use