############################################################################################################# ################################ MAIN SCRIPT - FORMING NHANES MERGED DATASET ############################## ############################################################################################################# working_directory <- "/Users/vynguyen/Dropbox/Mac/Documents/GitHub/publish_nhanes_data_1988_2018" setwd(working_directory) #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Assign Directories of NHANES Datasets ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# mortality_directory <- paste(working_directory , "Mortality Datasets" , sep = "/") #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Compile the NHANES Datasets ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# # Extract the individual mortality datasets and compile them into the unclean mortality dataset mortality_unclean <- compile_mortality_dataset(dataset_directory = mortality_directory , current_directory = working_directory) setwd(working_directory) response_unclean <- compile_datasets(cleaning_documentation = list_master_files$Response , current_directory = working_directory , name_dataset = "Response") dietary_unclean <- NHANES_dietary_final demographics_unclean <- compile_datasets(cleaning_documentation = list_master_files$Demographics , current_directory = working_directory , name_dataset = "Demographics") # Fix this due to change from df to list for the cleaning documentation medications_unclean <- compile_datasets(cleaning_documentation = list_master_files$Questionnaire %>% filter(grepl("\\bPrescription Medications\\b" , .$file_summary) == TRUE & is.na(.$SDDSRVYR) == FALSE) , current_directory = working_directory , name_dataset = "Medications") chemicals_unclean <- compile_datasets(cleaning_documentation = list_master_files$Chemicals , current_directory = working_directory , name_dataset = "Chemicals") weights_unclean <- compile_datasets(cleaning_documentation = list_master_files$Weights , current_directory = working_directory , name_dataset = "Weights") occupations_unclean <- compile_datasets(cleaning_documentation = list_master_files$Occupation , current_directory = working_directory , name_dataset = "Occupation") setwd(working_directory) questionnaire_unclean <- compile_datasets(cleaning_documentation = list_master_files$Questionnaire %>% filter(grepl("\\bPrescription Medications\\b" , .$file_summary) == FALSE & is.na(.$SDDSRVYR) == FALSE) , current_directory = working_directory , name_dataset = "Questionnaire") extract_series_of_8(dataset_unclean = questionnaire_unclean , name_dataset = "questionnaire") #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Clean the NHANES Datasets ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# # Clean the mortality dataset mortality_clean <- clean_mortality_dataset(mortality_unclean , list_master_files , "Mortality") dietary_clean <- clean_dietary_dataset(dietary_unclean , list_master_files , "Dietary") demographics_clean <- clean_demographics_dataset(demographics_unclean , list_master_files , "Demographics") setwd(working_directory) response_clean <- clean_response_dataset(response_unclean , list_master_files , "Response" , demographics_clean) medications_clean <- clean_medications_dataset(medications_unclean , list_master_files , "Questionnaire") list_chemicals_clean <- clean_chemicals_dataset(chemicals_unclean , list_master_files , "Chemicals") chemicals_clean <- list_chemicals_clean$only_harmonized_variable comments_unclean <- list_chemicals_clean$harmonized_and_unharmonized_variables rm(list_chemicals_clean) comments_clean <- form_comments_dataset(comments_unclean , list_master_files , "Chemicals") weights_clean <- form_survey_weights_dataset(weights_unclean , list_master_files , "Weights") occupation_clean <- clean_occupation_dataset(occupations_unclean , list_master_files) # Upload the cleaning documentation for all datasets list_master_files <- upload_nhanes_master_files("NHANES - Master List of Files 1i.xlsx") questionnaire_clean <- clean_questionnaire_dataset(questionnaire_unclean , list_master_files , "Questionnaire") #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Create dictionary ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# df_medications_drug_info <- create_dictionary_drugs("RXQ_DRUG") df_dictionary <- create_dictionary(list_dataset = list("mortality" = mortality_clean , "dietary" = dietary_clean , "demographics" = demographics_clean , "response" = response_clean , "medications" = medications_clean , "questionnaire" = questionnaire_clean , "chemicals" = chemicals_clean , "occupation" = occupation_clean , "weights" = weights_clean , "comments" = comments_clean) , list_documentations = list_master_files) df_levels_categorical_variables <- create_dictionary_harmonized_categories(list_documentations = list_master_files) #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Calculate statistics on the dataset ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# list_num_files <- calculate_num_files(list_master_files) list_num_variables <- calculate_num_variables(list_master_files , df_dictionary)