exercise_3b.R

# -----------------------------------------------------------------------------
# DESCRIPTION:  THIS PROGRAM ILLUSTRATES HOW TO POOL MEPS LONGITUDINAL DATA
#  FILES FROM DIFFERENT PANELS
#
# THE EXAMPLE USED IS PANELS 17-19 POPULATION AGE 26-30 WHO ARE UNINSURED BUT
#  HAVE HIGH INCOME IN THE FIRST YEAR
#
# DATA FROM PANELS 17, 18, AND 19 ARE POOLED.
#
# INPUT FILES:  (1) C:/MEPS/H183.ssp (PANEL 19 LONGITUDINAL FILE)
# 	            (2) C:/MEPS/H172.ssp (PANEL 18 LONGITUDINAL FILE)
# 	            (3) C:/MEPS/H164.ssp (PANEL 17 LONGITUDINAL FILE)
# -----------------------------------------------------------------------------

# Install and load libraries

  # Can skip this part if already installed
  install.packages("survey")
  install.packages("foreign")
  install.packages("dplyr")

  # Run this part each time you re-start R
  library(survey)
  library(foreign)
  library(dplyr)

# Set options to deal with lonely psu
options(survey.lonely.psu='adjust');


# Read in data

varlist = c("DUPERSID", "INSCOVY1", "INSCOVY2",
            "LONGWT",   "VARSTR",   "VARPSU",
            "POVCATY1", "AGEY1X",   "PANEL")

h183 = read.xport("C:/MEPS/h183.ssp") %>% select(varlist) # Panel 19
h172 = read.xport("C:/MEPS/h172.ssp") %>% select(varlist) # Panel 18
h164 = read.xport("C:/MEPS/h164.ssp") %>% select(varlist) # Panel 17

# Stack longitudinal files and define pooled weight variable and subpop of interest
#  subpop = age 26-30, uninsured, high income

pool = bind_rows(h183, h172, h164) %>%
  mutate(poolwt = LONGWT / 3,
         subpop = (26 <= AGEY1X & AGEY1X <= 30 & POVCATY1 == 5 & INSCOVY1 == 3))

pool %>%
  filter(subpop) %>%
  summary

head(pool)



# Define the survey design

mepsdsgn = svydesign(
  id = ~VARPSU,
  strata = ~VARSTR,
  weights = ~poolwt,
  data = pool,
  nest = TRUE)


# INSURANCE STATUS IN THE SECOND YEAR FOR THOSE W/ AGE=26-30, UNINSURED WHOLE YEAR, AND HIGH INCOME IN THE FIRST YEAR'

svymean(~as.factor(INSCOVY2), design = subset(mepsdsgn, subpop))