# ----------------------------------------------------------------------------- # R programming statements for h214 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 (h214.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 'h214'. # # 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 h214.dat file.) # # meps_path <- "C:/MEPS/h214.dat" # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h214/h214ru.txt") # head(h214) # 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 h214 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/h214dat.zip" # download.file(url, temp <- tempfile()) # # meps_path <- unzip(temp, exdir = tempdir()) # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h214/h214ru.txt") # # unlink(temp) # Unlink to delete temporary file # # head(h214) # view data # # ----------------------------------------------------------------------------- # DEFINE 'meps_path' ----------------------------------------------------------- # 'meps_path' should point to the file path of the ASCII file (h214.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/h214.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, 36, 38, 39, 42, 44, 46, 47, 49, 51, 52, 55, 58, 64, 70, 76, 78, 79, 82, 85, 87, 89, 101, 105) pos_end <- c( 7, 10, 20, 22, 35, 37, 38, 41, 43, 45, 46, 48, 50, 51, 54, 57, 63, 69, 75, 77, 78, 81, 84, 86, 88, 100, 104, 105) var_names <- c( "DUID", "PID", "DUPERSID", "CONDN", "CONDIDX", "PANEL", "CONDRN", "AGEDIAG", "CRND1", "CRND2", "CRND3", "CRND4", "CRND5", "INJURY", "ACCDNWRK", "ICD10CDX", "CCSR1X", "CCSR2X", "CCSR3X", "HHNUM", "IPNUM", "OPNUM", "OBNUM", "ERNUM", "RXNUM", "PERWT19F", "VARSTR", "VARPSU") var_types <- c( "c", "n", "c", "n", "c", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "c", "c", "c", "c", "n", "n", "n", "n", "n", "n", "n", "n", "n") var_types <- setNames(var_types, var_names) # IMPORT ASCII file ----------------------- h214 <- 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(h214, file ="h214.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 'h214'. # You must run the 'save' command to permanently save the data to a local # folder # -----------------------------------------------------------------------------