# ----------------------------------------------------------------------------- # R programming statements for h220A 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 (h220A.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 'h220A'. # # 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 h220A.dat file.) # # meps_path <- "C:/MEPS/h220A.dat" # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h220A/h220Aru.txt") # head(h220A) # 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 h220A 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/h220Adat.zip" # download.file(url, temp <- tempfile()) # # meps_path <- unzip(temp, exdir = tempdir()) # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h220A/h220Aru.txt") # # unlink(temp) # Unlink to delete temporary file # # head(h220A) # view data # # ----------------------------------------------------------------------------- # DEFINE 'meps_path' ----------------------------------------------------------- # 'meps_path' should point to the file path of the ASCII file (h220A.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/h220A.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, 34, 53, 69, 71, 72, 75, 79, 129, 189, 200, 208, 258, 308, 358, 408, 411, 413, 415, 417, 419, 421, 423, 425, 427, 429, 430, 431, 432, 433, 434, 437, 440, 443, 446, 449, 452, 455, 457, 459, 462, 465, 468, 471, 474, 477, 480, 483, 491, 500, 508, 516, 524, 532, 540, 547, 554, 561, 570, 583, 587) pos_end <- c( 7, 10, 20, 33, 52, 68, 70, 71, 74, 78, 128, 188, 199, 207, 257, 307, 357, 407, 410, 412, 414, 416, 418, 420, 422, 424, 426, 428, 429, 430, 431, 432, 433, 436, 439, 442, 445, 448, 451, 454, 456, 458, 461, 464, 467, 470, 473, 476, 479, 482, 490, 499, 507, 515, 523, 531, 539, 546, 553, 560, 569, 582, 586, 587) var_names <- c( "DUID", "PID", "DUPERSID", "DRUGIDX", "RXRECIDX", "LINKIDX", "PANEL", "PURCHRD", "RXBEGMM", "RXBEGYRX", "RXNAME", "RXDRGNAM", "RXNDC", "RXQUANTY", "RXFORM", "RXFRMUNT", "RXSTRENG", "RXSTRUNT", "RXDAYSUP", "PHARTP1", "PHARTP2", "PHARTP3", "PHARTP4", "PHARTP5", "PHARTP6", "PHARTP7", "PHARTP8", "PHARTP9", "RXFLG", "IMPFLAG", "PCIMPFLG", "DIABEQUIP", "INPCFLG", "PREGCAT", "TC1", "TC1S1", "TC1S1_1", "TC1S1_2", "TC1S2", "TC1S2_1", "TC1S3", "TC1S3_1", "TC2", "TC2S1", "TC2S1_1", "TC2S1_2", "TC2S2", "TC3", "TC3S1", "TC3S1_1", "RXSF20X", "RXMR20X", "RXMD20X", "RXPV20X", "RXVA20X", "RXTR20X", "RXOF20X", "RXSL20X", "RXWC20X", "RXOT20X", "RXXP20X", "PERWT20F", "VARSTR", "VARPSU") var_types <- c( "n", "n", "c", "c", "c", "c", "n", "n", "n", "n", "c", "c", "c", "n", "c", "c", "c", "c", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "n", "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") var_types <- setNames(var_types, var_names) # IMPORT ASCII file ----------------------- h220A <- 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(h220A, file ="h220A.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 'h220A'. # You must run the 'save' command to permanently save the data to a local # folder # -----------------------------------------------------------------------------