# -----------------------------------------------------------------------------
# R programming statements for h36brr22 data
#
# This file contains programming statements needed to import the ASCII data
# file (.dat) into R. The R programming language has the capability to produce
# appropriate standard errors for estimates from a survey with a complex sample
# design such as the Medical Expenditure Panel Survey (MEPS).
#
# The input file is the ASCII data file (h36brr22.dat) supplied in this PUF
# release, which can be extracted from the .zip file supplied at the MEPS
# website: https://meps.ahrq.gov/mepsweb/data_stats/download_data_files.jsp
#
# This code imports the MEPS data into R as a data frame called 'h36brr22'.
#
# Note that additional packages are needed to successfully run this code. To
# install these packages, run the 'install.packages' function (shown below).
# Once installed, the packages can be called using the 'library' function.
# Packages only need to be installed once, but they must be called using the
# 'library' function every time a new R session is started.
#
# Two options are available to run this code:
#
# 1. Copy and paste the code into an interactive R session.
#
# The user must first download the ASCII (.dat) file from the MEPS website
# and save it to a local directory, which must be defined in the
# 'meps_path' variable below. In this example, the local directory is
# called "C:/MEPS". Note that the path structure will differ on Mac and PC.
#
#
# 2. Call this code directly from an interactive R session.
#
# (a) If the ASCII (.dat) file has already been downloaded from the MEPS
# website and saved to a local directory, the following code can be run
# (after re-defining the 'meps_path' variable to point to the location
# of the h36brr22.dat file.)
#
# meps_path <- "C:/MEPS/h36brr22.dat"
# source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h36brr22/h36brr22ru.txt")
# head(h36brr22) # view data
#
#
# (b) Alternatively, the ASCII (.dat) file can be downloaded directly from
# the MEPS website. The following code can be used to download and
# import the h36brr22 data into R without having to manually download,
# unzip, and store the file on your local computer.
#
# url <- "https://meps.ahrq.gov/mepsweb/data_files/pufs/h36brr22dat.zip"
# download.file(url, temp <- tempfile())
#
# meps_path <- unzip(temp, exdir = tempdir())
# source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h36brr22/h36brr22ru.txt")
#
# unlink(temp) # Unlink to delete temporary file
#
# head(h36brr22) # view data
#
# -----------------------------------------------------------------------------
# DEFINE 'meps_path' -----------------------------------------------------------
# 'meps_path' should point to the file path of the ASCII file (h36brr22.dat)
# Here, the 'exists' function checks whether meps_path is already defined. This
# feature is useful if calling this file from an external source.
if(!exists("meps_path"))
meps_path = "C:/MEPS/h36brr22.dat"
# INSTALL PACKAGES ------------------------------------------------------------
# Uncomment and run this portion if packages are not yet installed
#
# install.packages("readr")
# LOAD PACKAGES ---------------------------------------------------------------
# Run this for every new R session
library(readr)
# DATA FILE INFO --------------------------------------------------------------
# Define start and end positions to read fixed-width file
pos_start <-
c(1, 8, 11, 21, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,
34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,
49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78,
79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93,
94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106,
107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118,
119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130,
131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142,
143, 144, 145, 146, 147, 148, 149, 150)
pos_end <-
c(7, 10, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,
34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,
49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78,
79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93,
94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106,
107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118,
119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130,
131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142,
143, 144, 145, 146, 147, 148, 149, 150)
# Define variable names and types ('c' = character, 'n' = 'numeric')
var_names <-
c("DUID", "PID", "DUPERSID", "PANEL", "BRR1", "BRR2", "BRR3",
"BRR4", "BRR5", "BRR6", "BRR7", "BRR8", "BRR9", "BRR10",
"BRR11", "BRR12", "BRR13", "BRR14", "BRR15", "BRR16",
"BRR17", "BRR18", "BRR19", "BRR20", "BRR21", "BRR22",
"BRR23", "BRR24", "BRR25", "BRR26", "BRR27", "BRR28",
"BRR29", "BRR30", "BRR31", "BRR32", "BRR33", "BRR34",
"BRR35", "BRR36", "BRR37", "BRR38", "BRR39", "BRR40",
"BRR41", "BRR42", "BRR43", "BRR44", "BRR45", "BRR46",
"BRR47", "BRR48", "BRR49", "BRR50", "BRR51", "BRR52",
"BRR53", "BRR54", "BRR55", "BRR56", "BRR57", "BRR58",
"BRR59", "BRR60", "BRR61", "BRR62", "BRR63", "BRR64",
"BRR65", "BRR66", "BRR67", "BRR68", "BRR69", "BRR70",
"BRR71", "BRR72", "BRR73", "BRR74", "BRR75", "BRR76",
"BRR77", "BRR78", "BRR79", "BRR80", "BRR81", "BRR82",
"BRR83", "BRR84", "BRR85", "BRR86", "BRR87", "BRR88",
"BRR89", "BRR90", "BRR91", "BRR92", "BRR93", "BRR94",
"BRR95", "BRR96", "BRR97", "BRR98", "BRR99", "BRR100",
"BRR101", "BRR102", "BRR103", "BRR104", "BRR105", "BRR106",
"BRR107", "BRR108", "BRR109", "BRR110", "BRR111", "BRR112",
"BRR113", "BRR114", "BRR115", "BRR116", "BRR117", "BRR118",
"BRR119", "BRR120", "BRR121", "BRR122", "BRR123", "BRR124",
"BRR125", "BRR126", "BRR127", "BRR128")
var_types <-
c("n", "n", "c", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n",
"n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n")
var_types <- setNames(var_types, var_names)
# IMPORT ASCII (.dat) file ----------------------------------------------------
h36brr22 <- read_fwf(
meps_path,
col_positions =
fwf_positions(
start = pos_start,
end = pos_end,
col_names = var_names),
col_types = var_types)
# OPTIONAL: save as .Rdata file for easier loading ----------------------------
# Run this to save a permanent .Rdata file in the local working directory
#
# save(h36brr22, file = "h36brr22.Rdata")
# -----------------------------------------------------------------------------
# NOTES:
#
# 1. This program has been tested on R version 3.6.0
#
# 2. This program will create a temporary data frame in R called 'h36brr22'.
# You must run the 'save' command to permanently save the data to a local
# folder
# -----------------------------------------------------------------------------