sdaza

######################################################
# SIMULATION FUNCTION TERM PAPER SOC 952, SPRING 2014
######################################################

# RETURN STANDARDIZED BIAS AND COVERAGE RATES

# These libraries have to be installed

library(data.table)
library(lavvan)

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# SAMPLING ERROR
 
serr <- function(n, deff=1, rr=1, N=NULL, cl=.95, p=0.5, relative=FALSE)  {

# validation

if (sum(n==0)>=1) { 
  stop("n vector contains 0 values")
}

sdaza

mycoefplot <- function(coef) {

# reverse coefficients
coef <- apply(coef, 2, rev)
nvar <- length(rownames(coef))

# dotplot
dotplot(1:nvar~coef[,1], 
	xlim=c(min(coef[,1]-2*coef[,2])-.02, max(coef[,1]+2*coef[,2])+.02), 
	xlab='Average predictive comparison', ylab=" ",

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# AVERAGE PREDICTVE COMPARISON

# loading libraries
library(arm)

# data
dat <- read.csv("http://dl.getdropbox.com/u/18116710/example.csv")

# id: individual identifier
# wave: 1 to 7

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# dat has to be a data.frame or data.table
# varnames should bea vector with the variable names you are looking for, e.g., c("hc", "hv"), or regular expressions
# the result would be a vector with variables names

lookvar  <- function(dat, varnames) {
  n  <- names(dat)
  
  nn  <- list()
    for (i in 1:length(varnames)) {
      nn[[i]]  <- grep(varnames[i],n)