# ----------------------------------------------------------------------------- # R programming statements for h208 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 (h208.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 'h208'. # # 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 h208.dat file.) # # meps_path <- "C:/MEPS/h208.dat" # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h208/h208ru.txt") # head(h208) # 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 h208 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/h208dat.zip" # download.file(url, temp <- tempfile()) # # meps_path <- unzip(temp, exdir = tempdir()) # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h208/h208ru.txt") # # unlink(temp) # Unlink to delete temporary file # # head(h208) # view data # # ----------------------------------------------------------------------------- # DEFINE 'meps_path' ----------------------------------------------------------- # 'meps_path' should point to the file path of the ASCII file (h208.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/h208.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, 134, 142, 150, 161, 181, 192, 194, 195, 209, 211, 214, 215, 216, 218, 221, 222, 223, 225, 227, 229, 231, 233, 235, 237, 239, 241, 243, 245, 247, 249, 251, 253, 255, 257, 259, 261, 263, 265, 267, 269, 271, 273, 275, 276, 277, 278, 280, 282, 284, 286, 288, 290, 292, 294, 296, 298, 300, 303, 305, 306, 307, 315, 322, 330, 332, 335, 337, 340, 342, 345) pos_end <- c(35, 45, 55, 66, 91, 105, 133, 141, 149, 160, 180, 191, 193, 194, 208, 210, 213, 214, 215, 217, 220, 221, 222, 224, 226, 228, 230, 232, 234, 236, 238, 240, 242, 244, 246, 248, 250, 252, 254, 256, 258, 260, 262, 264, 266, 268, 270, 272, 274, 275, 276, 277, 279, 281, 283, 285, 287, 289, 291, 293, 295, 297, 299, 302, 304, 305, 306, 314, 321, 329, 331, 334, 336, 339, 341, 344, 346) # Define variable names and types ('c' = character, 'n' = 'numeric') var_names <- c("EPCPIDX", "DUPERSID", "PHLDRIDX", "ESTBIDX", "EPRSIDX", "InsurPrivIDEX", "EPCPIDX_17", "DUPERSID_17", "PHLDRIDX_17", "ESTBIDX_17", "EPRSIDX_17", "JOBSIDX_17", "PANEL", "RN", "JOBSIDX", "JOBSINFR", "JOBSFILE", "PITFLG", "FYFLG", "CMJINS", "EMPLSTAT", "PHOLDER", "DEPNDNT", "PHLDRCHNG", "EVALCOVR", "STATUS1", "STATUS2", "STATUS3", "STATUS4", "STATUS5", "STATUS6", "STATUS7", "STATUS8", "STATUS9", "STATUS10", "STATUS11", "STATUS12", "STATUS13", "STATUS14", "STATUS15", "STATUS16", "STATUS17", "STATUS18", "STATUS19", "STATUS20", "STATUS21", "STATUS22", "STATUS23", "STATUS24", "DECPHLDR", "OUTPHLDR", "NOPUFLG", "COVROUT_M18", "TYPEFLAG", "STEXCH", "STSHOP", "PrivateCat", "PRIVCAT", "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", "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", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "c", "n", "n", "n") var_types <- setNames(var_types, var_names) # IMPORT ASCII (.dat) file ---------------------------------------------------- h208 <- 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(h208, file = "h208.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 'h208'. # You must run the 'save' command to permanently save the data to a local # folder # -----------------------------------------------------------------------------