# ----------------------------------------------------------------------------- # R programming statements for h223 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 (h223.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 'h223'. # # 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 h223.dat file.) # # meps_path <- "C:/MEPS/h223.dat" # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h223/h223ru.txt") # head(h223) # 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 h223 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/h223dat.zip" # download.file(url, temp <- tempfile()) # # meps_path <- unzip(temp, exdir = tempdir()) # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h223/h223ru.txt") # # unlink(temp) # Unlink to delete temporary file # # head(h223) # view data # # ----------------------------------------------------------------------------- # DEFINE 'meps_path' ----------------------------------------------------------- # 'meps_path' should point to the file path of the ASCII file (h223.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/h223.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, 36, 46, 56, 67, 92, 106, 108, 109, 123, 125, 128, 129, 132, 135, 136, 137, 139, 141, 143, 145, 147, 149, 151, 153, 155, 157, 159, 161, 163, 165, 167, 168, 169, 170, 172, 175, 177, 179, 181, 183, 185, 187, 189, 192, 194, 195, 196, 203, 210, 218, 220, 223, 225, 227, 229, 232) pos_end <- c( 35, 45, 55, 66, 91, 105, 107, 108, 122, 124, 127, 128, 131, 134, 135, 136, 138, 140, 142, 144, 146, 148, 150, 152, 154, 156, 158, 160, 162, 164, 166, 167, 168, 169, 171, 174, 176, 178, 180, 182, 184, 186, 188, 191, 193, 194, 195, 202, 209, 217, 219, 222, 224, 226, 228, 231, 233) var_names <- c( "EPCPIDX", "DUPERSID", "PHLDRIDX", "ESTBIDX", "EPRSIDX", "InsurPrivIDEX", "PANEL", "RN", "JOBSIDX", "JOBSINFR", "JOBSFILE", "FYFLG", "CMJINS", "EMPLSTAT", "PHOLDER", "DEPNDNT", "PHLDRCHNG", "EVALCOVR", "EVALCOV5", "STAT1", "STAT2", "STAT3", "STAT4", "STAT5", "STAT6", "STAT7", "STAT8", "STAT9", "STAT10", "STAT11", "STAT12", "DECPHLDR", "OUTPHLDR", "NOPUFLG", "COVROUT_M18", "TYPEFLAG", "STEXCH", "PrivateCat", "HOSPINSX", "MSUPINSX", "DENTLINS", "VISIONIN", "PMEDINS", "COBRA", "PLANMETL", "COVTYPIN", "OOPELIG", "OOPPREM", "OOPPREMX", "OOPX12X", "OOPFLAG", "PREMLEVX", "PREMSUBZ", "ANNDEDCT", "HSAACCT", "UPRHMO", "NAMECHNG") var_types <- c( "c", "c", "c", "c", "c", "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") var_types <- setNames(var_types, var_names) # IMPORT ASCII file ----------------------- h223 <- 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(h223, file ="h223.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 'h223'. # You must run the 'save' command to permanently save the data to a local # folder # -----------------------------------------------------------------------------