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# est.mer.R
# generate estimable output for mer objects using mcmcsamp()
# Randall Johnson
# Laboratory of Genomic Diversity at NCI Frederick
# SAIC Frederick, Inc
# Created April 25, 2006
# Updated 2012-04-19 for S4 version of lmer object
## est.mer <- function(obj, cm, beta0, conf.int, show.beta0, n.sim)
## {
## samp <- lme4:::mcmcsamp(obj, n.sim)
## ## samp.summ <- summary(samp)
## samp.cm <- t(cm %*% samp@fixef)
## # calculate requested statistics
## est <- apply(samp.cm, 2, mean)
## stderr <- apply(samp.cm, 2, sd)
## pval <- sapply(1:length(beta0),
## function(i){percentile(beta0[i], samp.cm[,i])})
## pval <- ifelse(pval <= .5, 2*pval, 2*(1-pval))
## if(is.null(conf.int))
## {
## lower.ci <- NULL
## upper.ci <- NULL
## }
## else
## {
## alpha <- 1-conf.int
## samp.ci <- sapply(1:length(beta0),
## function(i)
## {
## quantile(samp.cm[,i], probs=c(alpha/2, 1-alpha/2))
## }
## )
## lower.ci <- samp.ci[1,]
## upper.ci <- samp.ci[2,]
## }
## # return results
## if(!show.beta0)
## beta0 <- NULL
## samp.stats <- cbind('beta0' = beta0,
## 'Estimate' = est,
## 'Std. Error' = stderr,
## 'p value' = pval,
## 'Lower.CI' = lower.ci,
## 'Upper.CI' = upper.ci)
## row.names(samp.stats) <- paste('(', apply(cm, 1, paste, collapse=" "),
## ')', sep='')
## return(samp.stats)
## }
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