# ----------------------------------------------------------------------------- # R programming statements for h36brr20 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 (h36brr20.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 'h36brr20'. # # 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 h36brr20.dat file.) # # meps_path <- "C:/MEPS/h36brr20.dat" # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h36brr20/h36brr20ru.txt") # head(h36brr20) # 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 h36brr20 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/h36brr20dat.zip" # download.file(url, temp <- tempfile()) # # meps_path <- unzip(temp, exdir = tempdir()) # source("https://meps.ahrq.gov/mepsweb/data_stats/download_data/pufs/h36brr20/h36brr20ru.txt") # # unlink(temp) # Unlink to delete temporary file # # head(h36brr20) # view data # # ----------------------------------------------------------------------------- # DEFINE 'meps_path' ----------------------------------------------------------- # 'meps_path' should point to the file path of the ASCII file (h36brr20.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/h36brr20.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 ---------------------------------------------------- h36brr20 <- 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(h36brr20, file = "h36brr20.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 'h36brr20'. # You must run the 'save' command to permanently save the data to a local # folder # -----------------------------------------------------------------------------