In ready4-dev/TTU: Implement Transfer to Utility Mapping Algorithms
\blandscape
library(magrittr)
Specify parameters
Specify data
As this is an illustrative example, we first must create a fake dataset (if using real data, skip this step).
ds_tb <- readRDS(url("https://dataverse.harvard.edu/api/access/datafile/4750597"))
ds_tb %>%
head() %>%
ready4show::print_table(output_type_1L_chr = "HTML",
caption_1L_chr = "Input dataset",
mkdn_tbl_ref_1L_chr = "tab:inputds")
We note our use of synthetic data by creating an object use_fake_data_1L_lgl and setting it to TRUE. For real world application - set this variable to FALSE.
use_fake_data_1L_lgl <- TRUE
Reporting details
We specify details about the authorship team of the study for which we are generating reports.
authors_tb <- ready4show::authors_tb
institutes_tb <- ready4show::institutes_tb
And add details about the main project report we are authoring.
header_yaml_args_ls = list(authors_tb = authors_tb,
institutes_tb = institutes_tb,
fl_nm_1L_chr = "header_common.yaml",
title_1L_chr = "A hypothetical study using fake data for instructional purposes only",
keywords_chr = c("this","is","a","replication","using","fake","data","do", "not","cite"))
nbr_of_digits_1L_int = 2L
output_types_ls = list(manuscript_1L_chr = "Word",
supplementary_1L_chr = "PDF")
Path parameters
path_params_ls <- list(path_from_top_level_1L_chr = normalizePath("../") %>% strsplit("\\\\") %>% purrr::pluck(1) %>% tail(1),
path_to_data_from_top_level_chr = "fake_data.rds",
path_to_current_1L_chr = normalizePath(".") %>% strsplit("\\\\") %>% purrr::pluck(1) %>% tail(1))
Input dataset metadata
ds_descvs_ls <- list(candidate_predrs_chr = c("k10_int","psych_well_int"),
cohort_descv_var_nms_chr = c("d_age", "Gender", "d_relation_s","d_sexual_ori_s", "Region", "CALD", "d_studying_working"),
dictionary_tb = TTU::make_eq5d_ds_dict(ds_tb),
id_var_nm_1L_chr = "uid",
msrmnt_date_var_nm_1L_chr = "data_collection_dtm",
round_var_nm_1L_chr = "Timepoint",
round_vals_chr = c("BL", "FUP"),
maui_item_pfx_1L_chr = "eq5dq_",
utl_wtd_var_nm_1L_chr = "EQ5D_total_dbl",
utl_unwtd_var_nm_1L_chr = "EQ5d_cumulative_dbl")
Analysis parameters
predictors_lup <- TTU::TTU_predictors_lup(TTU::make_pt_TTU_predictors_lup(short_name_chr = ds_descvs_ls$candidate_predrs_chr,
long_name_chr = c("Kessler Psychological Distress - 10 Item Total Score",
"Overall Wellbeing Measure (Winefield et al. 2012)"),
min_val_dbl = c(10,18),
max_val_dbl = c(50,90),
class_chr = "integer",
increment_dbl = 1,
class_fn_chr = "as.integer",
mdl_scaling_dbl = 0.01,
covariate_lgl = F))
analysis_params_ls <- list(ds_descvs_ls = ds_descvs_ls,
iters_1L_int = 4000L,
mdl_smry_ls = list(mdl_types_lup = TTU::mdl_types_lup,
mdl_types_chr = TTU::mdl_types_lup$short_name_chr,
choose_from_pfx_chr = c("GLM","OLS","BET"),
folds_1L_int = 10L,
max_nbr_of_boruta_mdl_runs_int = 300L),
nbr_of_digits_1L_int = nbr_of_digits_1L_int,
output_type_1L_chr = output_types_ls$supplementary_1L_chr,
predictors_lup = predictors_lup,
seed_1L_int = 12345,
use_fake_data_1L_lgl = use_fake_data_1L_lgl,
prior_ls = NULL,
control_ls = list(adapt_delta = 0.99))
Reporting details
rprt_lup <- TTU::rprt_lup
file.create("aaaaaaaaaa.txt")
paths_ls <- ready4show::write_main_outp_dir(path_params_ls,
use_fake_data_1L_lgl = use_fake_data_1L_lgl)
paths_ls$path_to_current_1L_chr <- path_params_ls$path_to_current_1L_chr
Output repositories
Provide details of dataverse dataset(s) to which results will be posted. If you do not permissions for any dataverse datasets, set dv_ls <- NULL.
dv_ls <- list(primary_dv_chr = c("fakes","https://doi.org/10.7910/DVN/612HDC"))
Primary Analysis
Run analysis
params_ls <- list(candidate_covar_nms_chr = c("d_sex_birth_s", "d_age", "d_sexual_ori_s", "d_relation_s", "d_studying_working"),
ds_tb = ds_tb,
maui_domains_pfxs_1L_chr = NULL,
maui_itm_short_nms_chr = c("Mobility", "Self-care", "Activities","Pain","Anxiety"),
maui_scoring_fn = function(data_tb,# Function must have these arguments in this order.
maui_item_pfx_1L_chr,
id_var_nm_1L_chr,
utl_wtd_var_nm_1L_chr,
utl_unwtd_var_nm_1L_chr){
require(eq5d)
data_tb %>%
dplyr::rename_with(~stringr::str_replace(.x,maui_item_pfx_1L_chr,""),dplyr::starts_with(maui_item_pfx_1L_chr)) %>%
dplyr::mutate(`:=`(!!rlang::sym(utl_wtd_var_nm_1L_chr),
eq5d::eq5d(., country="UK", version = "5L", type = "CW"))) %>%
dplyr::rename_with(~paste0(maui_item_pfx_1L_chr,.x),c("MO","SC","UA","PD","AD")) %>%
dplyr::mutate(`:=`(!!rlang::sym(utl_unwtd_var_nm_1L_chr),
rowSums(dplyr::across(dplyr::starts_with(maui_item_pfx_1L_chr))))) %>% dplyr::filter(!is.na(!!rlang::sym(utl_unwtd_var_nm_1L_chr)))
},
prefd_covars_chr = NA_character_,
prefd_mdl_types_chr = c("GLM_GSN_LOG","OLS_CLL"),
raw_ds_tfmn_fn = NULL,
subtitle_1L_chr = "Methods Report 1: Analysis Program (Primary Analysis)",
utl_class_fn_1L_chr = "as.numeric") %>%
append(analysis_params_ls) %>%
append(path_params_ls[1:2])
ready4show::write_report(params_ls = params_ls,
paths_ls = paths_ls,
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
rprt_nm_1L_chr = "AAA_PMRY_ANLYS_MTH",
abstract_args_ls = NULL,
header_yaml_args_ls = header_yaml_args_ls,
rprt_lup = rprt_lup)
Report results
ready4show::write_rprt_with_rcrd(path_to_outp_fl_1L_chr = paste0(paths_ls$output_data_dir_1L_chr,"/I_ALL_OUTPUT_.RDS"),
paths_ls = paths_ls,
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
header_yaml_args_ls = header_yaml_args_ls,
rprt_lup = rprt_lup,
use_fake_data_1L_lgl = use_fake_data_1L_lgl,
subtitle_1L_chr = "Results Report 1: TTU Models (Primary Analysis)",
rprt_subtitle_1L_chr = "Methods Report 2: Reporting Program (Primary Analysis).",
rprt_nm_1L_chr = "AAA_TTU_MDL_CTG",
rcrd_nm_1L_chr = "AAA_RPRT_WRTNG_MTH",
output_type_1L_chr = output_types_ls$supplementary_1L_chr,
rprt_output_type_1L_chr = output_types_ls$supplementary_1L_chr,
nbr_of_digits_1L_int = nbr_of_digits_1L_int,
abstract_args_ls = NULL,
rcrd_rprt_append_ls = path_params_ls[1:2])
Share (de-confidentialised) results
if(!is.null(dv_ls)){
params_ls <- list(dv_ds_nm_and_url_chr = dv_ls$primary_dv_chr,
dv_mdl_desc_1L_chr = "This is a longitudinal transfer to utility model designed for use with the youthu R package.",
inc_fl_types_chr = ".pdf",
nbr_of_digits_1L_int = nbr_of_digits_1L_int,
output_type_1L_chr = output_types_ls$supplementary_1L_chr,
purge_data_1L_lgl = FALSE,
rprt_lup = rprt_lup,
subtitle_1L_chr = "Methods Report 3: Sharing Program (Primary Analysis)",
use_fake_data_1L_lgl = use_fake_data_1L_lgl) %>%
append(path_params_ls[1:2])
params_ls %>%
ready4show::write_report(paths_ls = paths_ls,
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
rprt_nm_1L_chr = "AAA_SHARING_MTH",
abstract_args_ls = NULL,
header_yaml_args_ls = header_yaml_args_ls,
rprt_lup = TTU::transform_rprt_lup(rprt_lup,
add_suplry_rprt_1L_lgl = F,
add_sharing_rprt_1L_lgl = T))
ready4::write_to_dv_with_wait(dss_tb = tibble::tibble(ds_obj_nm_chr = "AAA_SHARING_MTH",
title_chr = params_ls$subtitle_1L_chr),
dv_nm_1L_chr = dv_ls$primary_dv_chr[1],
ds_url_1L_chr = dv_ls$primary_dv_chr[2],
parent_dv_dir_1L_chr = paths_ls$dv_dir_1L_chr,
paths_to_dirs_chr = paths_ls$reports_dir_1L_chr,
inc_fl_types_chr = params_ls$inc_fl_types_chr,
paths_are_rltv_1L_lgl = F)
}
Secondary Analysis A (Anxiety + Depression)
reference_1L_int <- 1
scndry_paths_ls <- TTU::write_scndry_analysis_dir(paths_ls,
reference_1L_int = reference_1L_int)
Run analysis
TTU::write_scndry_analysis(analysis_params_ls = analysis_params_ls %>%
append(path_params_ls[1:2]),
candidate_covar_nms_chr = c("BADS", "SOFAS", "c_p_diag_s", "c_clinical_staging_s",
"d_age", "d_sex_birth_s", "d_sexual_ori_s", "d_country_bir_s", "d_relation_s",
"d_studying_working"),
candidate_predrs_chr = c("SCARED","OASIS","GAD7"),
prefd_covars_chr = "BADS",
reference_1L_int = reference_1L_int,
subtitle_1L_chr = "Methods Report 4: Analysis Program (Secondary Analysis (A))",
header_yaml_args_ls = header_yaml_args_ls,
paths_ls = paths_ls,
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
rprt_lup = rprt_lup)
Report results
ready4show::write_rprt_with_rcrd(path_to_outp_fl_1L_chr = here::here(paths_ls$path_from_top_level_1L_chr,
paths_ls$write_to_dir_nm_1L_chr,
paste0("secondary_",reference_1L_int),
"Output","I_ALL_OUTPUT_.RDS"),
paths_ls = scndry_paths_ls,
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
header_yaml_args_ls = header_yaml_args_ls,
rprt_lup = rprt_lup,
use_fake_data_1L_lgl = use_fake_data_1L_lgl,
subtitle_1L_chr = "Results Report 2: TTU Models (Secondary Analysis A)",
rprt_subtitle_1L_chr = "Methods Report 5: Reporting Program (Secondary Analysis A).",
rprt_nm_1L_chr = "AAA_TTU_MDL_CTG",
rcrd_nm_1L_chr = "AAA_RPRT_WRTNG_MTH",
output_type_1L_chr = output_types_ls$supplementary_1L_chr,
rprt_output_type_1L_chr = output_types_ls$supplementary_1L_chr,
nbr_of_digits_1L_int = nbr_of_digits_1L_int,
abstract_args_ls = NULL,
rcrd_rprt_append_ls = path_params_ls[1:2],
main_rprt_append_ls = list(existing_predrs_ls = readRDS(paste0(paths_ls$output_data_dir_1L_chr,
"/I_ALL_OUTPUT_.RDS")) %>%
purrr::pluck("predr_vars_nms_ls")))
Share (de-confidentialised) results
if(!is.null(dv_ls$secondary_1_dv_chr)){
params_ls <- list(dv_ds_nm_and_url_chr = dv_ls$secondary_1_dv_chr,
dv_mdl_desc_1L_chr = "This is a longitudinal transfer to utility model designed for use with the youthu R package.",
inc_fl_types_chr = ".pdf",
nbr_of_digits_1L_int = nbr_of_digits_1L_int,
output_type_1L_chr = output_types_ls$supplementary_1L_chr,
purge_data_1L_lgl = FALSE,
rprt_lup = rprt_lup,
subtitle_1L_chr = "Methods Report 6: Sharing Program (Secondary Analysis A)",
transform_paths_ls = list(fn = transform_paths_ls_for_scndry, #TTU::
args_ls = list(reference_1L_int = reference_1L_int,
remove_prmry_1L_lgl = T)),
use_fake_data_1L_lgl = use_fake_data_1L_lgl) %>%
append(path_params_ls[1:2])
ready4show::write_report(params_ls = params_ls,
paths_ls = scndry_paths_ls[names(scndry_paths_ls) != "prmry_analysis_dir_nm_1L_chr"],
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
rprt_nm_1L_chr = "AAA_SHARING_MTH",
abstract_args_ls = NULL,
header_yaml_args_ls = header_yaml_args_ls,
rprt_lup = TTU::transform_rprt_lup(rprt_lup,
add_suplry_rprt_1L_lgl = F,
add_sharing_rprt_1L_lgl = T))
ready4::write_to_dv_with_wait(dss_tb = tibble::tibble(ds_obj_nm_chr = "AAA_SHARING_MTH",
title_chr = params_ls$subtitle_1L_chr),
dv_nm_1L_chr = dv_ls$primary_dv_chr[1],
ds_url_1L_chr = dv_ls$primary_dv_chr[2],
parent_dv_dir_1L_chr = paths_ls$dv_dir_1L_chr,
paths_to_dirs_chr = paths_ls$reports_dir_1L_chr,
inc_fl_types_chr = params_ls$inc_fl_types_chr,
paths_are_rltv_1L_lgl = F)
}
Secondary Analysis B (SOFAS)
Run analysis
reference_1L_int <- 2
scndry_paths_ls <- TTU::write_scndry_analysis_dir(paths_ls,
reference_1L_int = reference_1L_int)
TTU::write_scndry_analysis(analysis_params_ls = analysis_params_ls %>%
append(path_params_ls[1:2]),
candidate_covar_nms_chr = c("d_sex_birth_s", "c_p_diag_s", "c_clinical_staging_s", "d_age",
"d_sexual_ori_s", "d_country_bir_s", "d_relation_s", "d_studying_working"),
candidate_predrs_chr = "SOFAS",
prefd_covars_chr = NULL,
reference_1L_int = 2,
subtitle_1L_chr = "Methods Report 7: Analysis Program (Secondary Analysis (B))",
header_yaml_args_ls = header_yaml_args_ls,
paths_ls = paths_ls,
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
rprt_lup = rprt_lup)
Report results
ready4show::write_rprt_with_rcrd(path_to_outp_fl_1L_chr = here::here(paths_ls$path_from_top_level_1L_chr,
paths_ls$write_to_dir_nm_1L_chr,
paste0("secondary_",reference_1L_int),
"Output","I_ALL_OUTPUT_.RDS"),
paths_ls = scndry_paths_ls,
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
header_yaml_args_ls = header_yaml_args_ls,
rprt_lup = rprt_lup,
use_fake_data_1L_lgl = use_fake_data_1L_lgl,
subtitle_1L_chr = "Results Report 3: TTU Models (Secondary Analysis B)",
rprt_subtitle_1L_chr = "Methods Report 8: Reporting Program (Secondary Analysis B).",
rprt_nm_1L_chr = "AAA_TTU_MDL_CTG",
rcrd_nm_1L_chr = "AAA_RPRT_WRTNG_MTH",
output_type_1L_chr = output_types_ls$supplementary_1L_chr,
rprt_output_type_1L_chr = output_types_ls$supplementary_1L_chr,
nbr_of_digits_1L_int = nbr_of_digits_1L_int,
abstract_args_ls = NULL,
rcrd_rprt_append_ls = path_params_ls[1:2],
main_rprt_append_ls = list(existing_predrs_ls = readRDS(paste0(paths_ls$output_data_dir_1L_chr,
"/I_ALL_OUTPUT_.RDS")) %>%
purrr::pluck("predr_vars_nms_ls")))
Share (de-confidentialised) results
if(!is.null(dv_ls$secondary_2_dv_chr)){
params_ls <- list(dv_ds_nm_and_url_chr = dv_ls$secondary_2_dv_chr,
dv_mdl_desc_1L_chr = "This is a longitudinal transfer to utility model designed for use with the youthu R package.",
inc_fl_types_chr = ".pdf",
nbr_of_digits_1L_int = nbr_of_digits_1L_int,
output_type_1L_chr = output_types_ls$supplementary_1L_chr,
purge_data_1L_lgl = FALSE,
rprt_lup = rprt_lup,
subtitle_1L_chr = "Methods Report 9: Sharing Program (Secondary Analysis B)",
transform_paths_ls = list(fn = TTU::transform_paths_ls_for_scndry,
args_ls = list(reference_1L_int = reference_1L_int,
remove_prmry_1L_lgl = T)),
use_fake_data_1L_lgl = use_fake_data_1L_lgl) %>%
append(path_params_ls[1:2])
ready4show::write_report(params_ls = params_ls,
paths_ls = scndry_paths_ls[names(scndry_paths_ls) != "prmry_analysis_dir_nm_1L_chr"],
R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr,
rprt_nm_1L_chr = "AAA_SHARING_MTH",
abstract_args_ls = NULL,
header_yaml_args_ls = header_yaml_args_ls,
rprt_lup = TTU::transform_rprt_lup(rprt_lup,
add_suplry_rprt_1L_lgl = F,
add_sharing_rprt_1L_lgl = T))
ready4::write_to_dv_with_wait(dss_tb = tibble::tibble(ds_obj_nm_chr = "AAA_SHARING_MTH",
title_chr = params_ls$subtitle_1L_chr),
dv_nm_1L_chr = dv_ls$primary_dv_chr[1],
ds_url_1L_chr = dv_ls$primary_dv_chr[2],
parent_dv_dir_1L_chr = paths_ls$dv_dir_1L_chr,
paths_to_dirs_chr = paths_ls$reports_dir_1L_chr,
inc_fl_types_chr = params_ls$inc_fl_types_chr,
paths_are_rltv_1L_lgl = F)
}
Render Manuscript
if(!use_fake_data_1L_lgl){
var_nm_change_lup <- tibble::tibble(old_nms_chr = c("PHQ9","GAD7"),
new_nms_chr = c("PHQ-9", "GAD-7"))
study_descs_ls <- TTU::make_study_descs_ls(health_utl_nm_1L_chr = "AQol-6D",
time_btwn_bl_and_fup_1L_chr = "three months",
predr_ctgs_ls = list(`psychological distress` = c("K6"),
depression = c("BADS","PHQ9"),
anxiety = c("GAD7","OASIS","SCARED")))
spine_of_results_ls <- TTU::make_results_ls_spine(output_data_dir_1L_chr = paths_ls$output_data_dir_1L_chr,
var_nm_change_lup = var_nm_change_lup,
study_descs_ls = study_descs_ls,
nbr_of_digits_1L_int = 2L)
cs_ts_ratios_tb = tibble::tibble(predr_nm_chr = c("K6","depression measurements", "anxiety measurements"),
ratios_chr = c(paste0("about ",round(spine_of_results_ls$mdl_coef_ratios_ls$`psychological distress`,2)),
paste0(round(mean(spine_of_results_ls$mdl_coef_ratios_ls$depression),2)),
paste0(round(min(spine_of_results_ls$mdl_coef_ratios_ls$anxiety),2)," or over")
))
ctgl_vars_regrouping_ls = list('Primary Diagnosis' = list(anxdpr = list(name_1L_chr = "anxiety/depression",
ctgs_chr = c("Anxiety", "Depression", "Depression and Anxiety"))),
'Clinical Stage' = list(early = list(name_1L_chr = "early (prior to first episode of a serious mental disorder) clinical stages",
ctgs_chr = c("0-1a","1b"))))
sig_covars_some_predrs_mdls_tb = tibble::tibble(covars_ls = list(c("No other confounding factor"),
c("sex at birth"),
c("primary diagnosis", "clinical staging","age")),
predrs_mdls_ls = list(c("PHQ-9"), c("K6"),c("anxiety and depression measurements other than PHQ-9")),
sig_thresh_dbl = c(NA_real_,0.01,NA_real_),
assn_strgth_chr = c(NA_character_,NA_character_,"weakly"))
results_ls <- TTU::make_results_ls(spine_of_results_ls,
cs_ts_ratios_tb = cs_ts_ratios_tb,
ctgl_vars_regrouping_ls = ctgl_vars_regrouping_ls,
sig_covars_some_predrs_mdls_tb = sig_covars_some_predrs_mdls_tb,
sig_thresh_covars_1L_chr = "0.005")
saveRDS(results_ls,paste0(paths_ls$output_data_dir_1L_chr,"/results_ls.RDS"))
rmarkdown::render("AQoL_VIH/AQoL_VIH.Rmd",
output_format = NULL,
params = list(figures_in_body_lgl = F,
output_type_1L_chr = "Word",
results_ls = results_ls,
tables_in_body_lgl = F),
output_file = paste0("AQoL_VIH", ".docx"),
output_dir = paths_ls$reports_dir_1L_chr)
}
Purge dataset copies
TTU::write_to_delete_ds_copies(paths_ls)
\elandscape
ready4-dev/TTU documentation built on July 2, 2024, 8:12 a.m.
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\blandscape
library(magrittr)
Specify parameters
Specify data
As this is an illustrative example, we first must create a fake dataset (if using real data, skip this step).
ds_tb <- readRDS(url("https://dataverse.harvard.edu/api/access/datafile/4750597"))
ds_tb %>% head() %>% ready4show::print_table(output_type_1L_chr = "HTML", caption_1L_chr = "Input dataset", mkdn_tbl_ref_1L_chr = "tab:inputds")
We note our use of synthetic data by creating an object use_fake_data_1L_lgl and setting it to TRUE. For real world application - set this variable to FALSE.
use_fake_data_1L_lgl <- TRUE
Reporting details
We specify details about the authorship team of the study for which we are generating reports.
authors_tb <- ready4show::authors_tb institutes_tb <- ready4show::institutes_tb
And add details about the main project report we are authoring.
header_yaml_args_ls = list(authors_tb = authors_tb, institutes_tb = institutes_tb, fl_nm_1L_chr = "header_common.yaml", title_1L_chr = "A hypothetical study using fake data for instructional purposes only", keywords_chr = c("this","is","a","replication","using","fake","data","do", "not","cite")) nbr_of_digits_1L_int = 2L output_types_ls = list(manuscript_1L_chr = "Word", supplementary_1L_chr = "PDF")
Path parameters
path_params_ls <- list(path_from_top_level_1L_chr = normalizePath("../") %>% strsplit("\\\\") %>% purrr::pluck(1) %>% tail(1), path_to_data_from_top_level_chr = "fake_data.rds", path_to_current_1L_chr = normalizePath(".") %>% strsplit("\\\\") %>% purrr::pluck(1) %>% tail(1))
Input dataset metadata
ds_descvs_ls <- list(candidate_predrs_chr = c("k10_int","psych_well_int"), cohort_descv_var_nms_chr = c("d_age", "Gender", "d_relation_s","d_sexual_ori_s", "Region", "CALD", "d_studying_working"), dictionary_tb = TTU::make_eq5d_ds_dict(ds_tb), id_var_nm_1L_chr = "uid", msrmnt_date_var_nm_1L_chr = "data_collection_dtm", round_var_nm_1L_chr = "Timepoint", round_vals_chr = c("BL", "FUP"), maui_item_pfx_1L_chr = "eq5dq_", utl_wtd_var_nm_1L_chr = "EQ5D_total_dbl", utl_unwtd_var_nm_1L_chr = "EQ5d_cumulative_dbl")
Analysis parameters
predictors_lup <- TTU::TTU_predictors_lup(TTU::make_pt_TTU_predictors_lup(short_name_chr = ds_descvs_ls$candidate_predrs_chr, long_name_chr = c("Kessler Psychological Distress - 10 Item Total Score", "Overall Wellbeing Measure (Winefield et al. 2012)"), min_val_dbl = c(10,18), max_val_dbl = c(50,90), class_chr = "integer", increment_dbl = 1, class_fn_chr = "as.integer", mdl_scaling_dbl = 0.01, covariate_lgl = F))
analysis_params_ls <- list(ds_descvs_ls = ds_descvs_ls, iters_1L_int = 4000L, mdl_smry_ls = list(mdl_types_lup = TTU::mdl_types_lup, mdl_types_chr = TTU::mdl_types_lup$short_name_chr, choose_from_pfx_chr = c("GLM","OLS","BET"), folds_1L_int = 10L, max_nbr_of_boruta_mdl_runs_int = 300L), nbr_of_digits_1L_int = nbr_of_digits_1L_int, output_type_1L_chr = output_types_ls$supplementary_1L_chr, predictors_lup = predictors_lup, seed_1L_int = 12345, use_fake_data_1L_lgl = use_fake_data_1L_lgl, prior_ls = NULL, control_ls = list(adapt_delta = 0.99))
Reporting details
rprt_lup <- TTU::rprt_lup file.create("aaaaaaaaaa.txt") paths_ls <- ready4show::write_main_outp_dir(path_params_ls, use_fake_data_1L_lgl = use_fake_data_1L_lgl) paths_ls$path_to_current_1L_chr <- path_params_ls$path_to_current_1L_chr
Output repositories
Provide details of dataverse dataset(s) to which results will be posted. If you do not permissions for any dataverse datasets, set dv_ls <- NULL.
dv_ls <- list(primary_dv_chr = c("fakes","https://doi.org/10.7910/DVN/612HDC"))
Primary Analysis
Run analysis
params_ls <- list(candidate_covar_nms_chr = c("d_sex_birth_s", "d_age", "d_sexual_ori_s", "d_relation_s", "d_studying_working"), ds_tb = ds_tb, maui_domains_pfxs_1L_chr = NULL, maui_itm_short_nms_chr = c("Mobility", "Self-care", "Activities","Pain","Anxiety"), maui_scoring_fn = function(data_tb,# Function must have these arguments in this order. maui_item_pfx_1L_chr, id_var_nm_1L_chr, utl_wtd_var_nm_1L_chr, utl_unwtd_var_nm_1L_chr){ require(eq5d) data_tb %>% dplyr::rename_with(~stringr::str_replace(.x,maui_item_pfx_1L_chr,""),dplyr::starts_with(maui_item_pfx_1L_chr)) %>% dplyr::mutate(`:=`(!!rlang::sym(utl_wtd_var_nm_1L_chr), eq5d::eq5d(., country="UK", version = "5L", type = "CW"))) %>% dplyr::rename_with(~paste0(maui_item_pfx_1L_chr,.x),c("MO","SC","UA","PD","AD")) %>% dplyr::mutate(`:=`(!!rlang::sym(utl_unwtd_var_nm_1L_chr), rowSums(dplyr::across(dplyr::starts_with(maui_item_pfx_1L_chr))))) %>% dplyr::filter(!is.na(!!rlang::sym(utl_unwtd_var_nm_1L_chr))) }, prefd_covars_chr = NA_character_, prefd_mdl_types_chr = c("GLM_GSN_LOG","OLS_CLL"), raw_ds_tfmn_fn = NULL, subtitle_1L_chr = "Methods Report 1: Analysis Program (Primary Analysis)", utl_class_fn_1L_chr = "as.numeric") %>% append(analysis_params_ls) %>% append(path_params_ls[1:2]) ready4show::write_report(params_ls = params_ls, paths_ls = paths_ls, R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, rprt_nm_1L_chr = "AAA_PMRY_ANLYS_MTH", abstract_args_ls = NULL, header_yaml_args_ls = header_yaml_args_ls, rprt_lup = rprt_lup)
Report results
ready4show::write_rprt_with_rcrd(path_to_outp_fl_1L_chr = paste0(paths_ls$output_data_dir_1L_chr,"/I_ALL_OUTPUT_.RDS"), paths_ls = paths_ls, R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, header_yaml_args_ls = header_yaml_args_ls, rprt_lup = rprt_lup, use_fake_data_1L_lgl = use_fake_data_1L_lgl, subtitle_1L_chr = "Results Report 1: TTU Models (Primary Analysis)", rprt_subtitle_1L_chr = "Methods Report 2: Reporting Program (Primary Analysis).", rprt_nm_1L_chr = "AAA_TTU_MDL_CTG", rcrd_nm_1L_chr = "AAA_RPRT_WRTNG_MTH", output_type_1L_chr = output_types_ls$supplementary_1L_chr, rprt_output_type_1L_chr = output_types_ls$supplementary_1L_chr, nbr_of_digits_1L_int = nbr_of_digits_1L_int, abstract_args_ls = NULL, rcrd_rprt_append_ls = path_params_ls[1:2])
Share (de-confidentialised) results
if(!is.null(dv_ls)){ params_ls <- list(dv_ds_nm_and_url_chr = dv_ls$primary_dv_chr, dv_mdl_desc_1L_chr = "This is a longitudinal transfer to utility model designed for use with the youthu R package.", inc_fl_types_chr = ".pdf", nbr_of_digits_1L_int = nbr_of_digits_1L_int, output_type_1L_chr = output_types_ls$supplementary_1L_chr, purge_data_1L_lgl = FALSE, rprt_lup = rprt_lup, subtitle_1L_chr = "Methods Report 3: Sharing Program (Primary Analysis)", use_fake_data_1L_lgl = use_fake_data_1L_lgl) %>% append(path_params_ls[1:2]) params_ls %>% ready4show::write_report(paths_ls = paths_ls, R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, rprt_nm_1L_chr = "AAA_SHARING_MTH", abstract_args_ls = NULL, header_yaml_args_ls = header_yaml_args_ls, rprt_lup = TTU::transform_rprt_lup(rprt_lup, add_suplry_rprt_1L_lgl = F, add_sharing_rprt_1L_lgl = T)) ready4::write_to_dv_with_wait(dss_tb = tibble::tibble(ds_obj_nm_chr = "AAA_SHARING_MTH", title_chr = params_ls$subtitle_1L_chr), dv_nm_1L_chr = dv_ls$primary_dv_chr[1], ds_url_1L_chr = dv_ls$primary_dv_chr[2], parent_dv_dir_1L_chr = paths_ls$dv_dir_1L_chr, paths_to_dirs_chr = paths_ls$reports_dir_1L_chr, inc_fl_types_chr = params_ls$inc_fl_types_chr, paths_are_rltv_1L_lgl = F) }
Secondary Analysis A (Anxiety + Depression)
reference_1L_int <- 1 scndry_paths_ls <- TTU::write_scndry_analysis_dir(paths_ls, reference_1L_int = reference_1L_int)
Run analysis
TTU::write_scndry_analysis(analysis_params_ls = analysis_params_ls %>% append(path_params_ls[1:2]), candidate_covar_nms_chr = c("BADS", "SOFAS", "c_p_diag_s", "c_clinical_staging_s", "d_age", "d_sex_birth_s", "d_sexual_ori_s", "d_country_bir_s", "d_relation_s", "d_studying_working"), candidate_predrs_chr = c("SCARED","OASIS","GAD7"), prefd_covars_chr = "BADS", reference_1L_int = reference_1L_int, subtitle_1L_chr = "Methods Report 4: Analysis Program (Secondary Analysis (A))", header_yaml_args_ls = header_yaml_args_ls, paths_ls = paths_ls, R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, rprt_lup = rprt_lup)
Report results
ready4show::write_rprt_with_rcrd(path_to_outp_fl_1L_chr = here::here(paths_ls$path_from_top_level_1L_chr, paths_ls$write_to_dir_nm_1L_chr, paste0("secondary_",reference_1L_int), "Output","I_ALL_OUTPUT_.RDS"), paths_ls = scndry_paths_ls, R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, header_yaml_args_ls = header_yaml_args_ls, rprt_lup = rprt_lup, use_fake_data_1L_lgl = use_fake_data_1L_lgl, subtitle_1L_chr = "Results Report 2: TTU Models (Secondary Analysis A)", rprt_subtitle_1L_chr = "Methods Report 5: Reporting Program (Secondary Analysis A).", rprt_nm_1L_chr = "AAA_TTU_MDL_CTG", rcrd_nm_1L_chr = "AAA_RPRT_WRTNG_MTH", output_type_1L_chr = output_types_ls$supplementary_1L_chr, rprt_output_type_1L_chr = output_types_ls$supplementary_1L_chr, nbr_of_digits_1L_int = nbr_of_digits_1L_int, abstract_args_ls = NULL, rcrd_rprt_append_ls = path_params_ls[1:2], main_rprt_append_ls = list(existing_predrs_ls = readRDS(paste0(paths_ls$output_data_dir_1L_chr, "/I_ALL_OUTPUT_.RDS")) %>% purrr::pluck("predr_vars_nms_ls")))
Share (de-confidentialised) results
if(!is.null(dv_ls$secondary_1_dv_chr)){ params_ls <- list(dv_ds_nm_and_url_chr = dv_ls$secondary_1_dv_chr, dv_mdl_desc_1L_chr = "This is a longitudinal transfer to utility model designed for use with the youthu R package.", inc_fl_types_chr = ".pdf", nbr_of_digits_1L_int = nbr_of_digits_1L_int, output_type_1L_chr = output_types_ls$supplementary_1L_chr, purge_data_1L_lgl = FALSE, rprt_lup = rprt_lup, subtitle_1L_chr = "Methods Report 6: Sharing Program (Secondary Analysis A)", transform_paths_ls = list(fn = transform_paths_ls_for_scndry, #TTU:: args_ls = list(reference_1L_int = reference_1L_int, remove_prmry_1L_lgl = T)), use_fake_data_1L_lgl = use_fake_data_1L_lgl) %>% append(path_params_ls[1:2]) ready4show::write_report(params_ls = params_ls, paths_ls = scndry_paths_ls[names(scndry_paths_ls) != "prmry_analysis_dir_nm_1L_chr"], R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, rprt_nm_1L_chr = "AAA_SHARING_MTH", abstract_args_ls = NULL, header_yaml_args_ls = header_yaml_args_ls, rprt_lup = TTU::transform_rprt_lup(rprt_lup, add_suplry_rprt_1L_lgl = F, add_sharing_rprt_1L_lgl = T)) ready4::write_to_dv_with_wait(dss_tb = tibble::tibble(ds_obj_nm_chr = "AAA_SHARING_MTH", title_chr = params_ls$subtitle_1L_chr), dv_nm_1L_chr = dv_ls$primary_dv_chr[1], ds_url_1L_chr = dv_ls$primary_dv_chr[2], parent_dv_dir_1L_chr = paths_ls$dv_dir_1L_chr, paths_to_dirs_chr = paths_ls$reports_dir_1L_chr, inc_fl_types_chr = params_ls$inc_fl_types_chr, paths_are_rltv_1L_lgl = F) }
Secondary Analysis B (SOFAS)
Run analysis
reference_1L_int <- 2 scndry_paths_ls <- TTU::write_scndry_analysis_dir(paths_ls, reference_1L_int = reference_1L_int) TTU::write_scndry_analysis(analysis_params_ls = analysis_params_ls %>% append(path_params_ls[1:2]), candidate_covar_nms_chr = c("d_sex_birth_s", "c_p_diag_s", "c_clinical_staging_s", "d_age", "d_sexual_ori_s", "d_country_bir_s", "d_relation_s", "d_studying_working"), candidate_predrs_chr = "SOFAS", prefd_covars_chr = NULL, reference_1L_int = 2, subtitle_1L_chr = "Methods Report 7: Analysis Program (Secondary Analysis (B))", header_yaml_args_ls = header_yaml_args_ls, paths_ls = paths_ls, R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, rprt_lup = rprt_lup)
Report results
ready4show::write_rprt_with_rcrd(path_to_outp_fl_1L_chr = here::here(paths_ls$path_from_top_level_1L_chr, paths_ls$write_to_dir_nm_1L_chr, paste0("secondary_",reference_1L_int), "Output","I_ALL_OUTPUT_.RDS"), paths_ls = scndry_paths_ls, R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, header_yaml_args_ls = header_yaml_args_ls, rprt_lup = rprt_lup, use_fake_data_1L_lgl = use_fake_data_1L_lgl, subtitle_1L_chr = "Results Report 3: TTU Models (Secondary Analysis B)", rprt_subtitle_1L_chr = "Methods Report 8: Reporting Program (Secondary Analysis B).", rprt_nm_1L_chr = "AAA_TTU_MDL_CTG", rcrd_nm_1L_chr = "AAA_RPRT_WRTNG_MTH", output_type_1L_chr = output_types_ls$supplementary_1L_chr, rprt_output_type_1L_chr = output_types_ls$supplementary_1L_chr, nbr_of_digits_1L_int = nbr_of_digits_1L_int, abstract_args_ls = NULL, rcrd_rprt_append_ls = path_params_ls[1:2], main_rprt_append_ls = list(existing_predrs_ls = readRDS(paste0(paths_ls$output_data_dir_1L_chr, "/I_ALL_OUTPUT_.RDS")) %>% purrr::pluck("predr_vars_nms_ls")))
Share (de-confidentialised) results
if(!is.null(dv_ls$secondary_2_dv_chr)){ params_ls <- list(dv_ds_nm_and_url_chr = dv_ls$secondary_2_dv_chr, dv_mdl_desc_1L_chr = "This is a longitudinal transfer to utility model designed for use with the youthu R package.", inc_fl_types_chr = ".pdf", nbr_of_digits_1L_int = nbr_of_digits_1L_int, output_type_1L_chr = output_types_ls$supplementary_1L_chr, purge_data_1L_lgl = FALSE, rprt_lup = rprt_lup, subtitle_1L_chr = "Methods Report 9: Sharing Program (Secondary Analysis B)", transform_paths_ls = list(fn = TTU::transform_paths_ls_for_scndry, args_ls = list(reference_1L_int = reference_1L_int, remove_prmry_1L_lgl = T)), use_fake_data_1L_lgl = use_fake_data_1L_lgl) %>% append(path_params_ls[1:2]) ready4show::write_report(params_ls = params_ls, paths_ls = scndry_paths_ls[names(scndry_paths_ls) != "prmry_analysis_dir_nm_1L_chr"], R_fl_nm_1L_chr = paths_ls$R_fl_nm_1L_chr, rprt_nm_1L_chr = "AAA_SHARING_MTH", abstract_args_ls = NULL, header_yaml_args_ls = header_yaml_args_ls, rprt_lup = TTU::transform_rprt_lup(rprt_lup, add_suplry_rprt_1L_lgl = F, add_sharing_rprt_1L_lgl = T)) ready4::write_to_dv_with_wait(dss_tb = tibble::tibble(ds_obj_nm_chr = "AAA_SHARING_MTH", title_chr = params_ls$subtitle_1L_chr), dv_nm_1L_chr = dv_ls$primary_dv_chr[1], ds_url_1L_chr = dv_ls$primary_dv_chr[2], parent_dv_dir_1L_chr = paths_ls$dv_dir_1L_chr, paths_to_dirs_chr = paths_ls$reports_dir_1L_chr, inc_fl_types_chr = params_ls$inc_fl_types_chr, paths_are_rltv_1L_lgl = F) }
Render Manuscript
if(!use_fake_data_1L_lgl){ var_nm_change_lup <- tibble::tibble(old_nms_chr = c("PHQ9","GAD7"), new_nms_chr = c("PHQ-9", "GAD-7")) study_descs_ls <- TTU::make_study_descs_ls(health_utl_nm_1L_chr = "AQol-6D", time_btwn_bl_and_fup_1L_chr = "three months", predr_ctgs_ls = list(`psychological distress` = c("K6"), depression = c("BADS","PHQ9"), anxiety = c("GAD7","OASIS","SCARED"))) spine_of_results_ls <- TTU::make_results_ls_spine(output_data_dir_1L_chr = paths_ls$output_data_dir_1L_chr, var_nm_change_lup = var_nm_change_lup, study_descs_ls = study_descs_ls, nbr_of_digits_1L_int = 2L) cs_ts_ratios_tb = tibble::tibble(predr_nm_chr = c("K6","depression measurements", "anxiety measurements"), ratios_chr = c(paste0("about ",round(spine_of_results_ls$mdl_coef_ratios_ls$`psychological distress`,2)), paste0(round(mean(spine_of_results_ls$mdl_coef_ratios_ls$depression),2)), paste0(round(min(spine_of_results_ls$mdl_coef_ratios_ls$anxiety),2)," or over") )) ctgl_vars_regrouping_ls = list('Primary Diagnosis' = list(anxdpr = list(name_1L_chr = "anxiety/depression", ctgs_chr = c("Anxiety", "Depression", "Depression and Anxiety"))), 'Clinical Stage' = list(early = list(name_1L_chr = "early (prior to first episode of a serious mental disorder) clinical stages", ctgs_chr = c("0-1a","1b")))) sig_covars_some_predrs_mdls_tb = tibble::tibble(covars_ls = list(c("No other confounding factor"), c("sex at birth"), c("primary diagnosis", "clinical staging","age")), predrs_mdls_ls = list(c("PHQ-9"), c("K6"),c("anxiety and depression measurements other than PHQ-9")), sig_thresh_dbl = c(NA_real_,0.01,NA_real_), assn_strgth_chr = c(NA_character_,NA_character_,"weakly")) results_ls <- TTU::make_results_ls(spine_of_results_ls, cs_ts_ratios_tb = cs_ts_ratios_tb, ctgl_vars_regrouping_ls = ctgl_vars_regrouping_ls, sig_covars_some_predrs_mdls_tb = sig_covars_some_predrs_mdls_tb, sig_thresh_covars_1L_chr = "0.005") saveRDS(results_ls,paste0(paths_ls$output_data_dir_1L_chr,"/results_ls.RDS")) rmarkdown::render("AQoL_VIH/AQoL_VIH.Rmd", output_format = NULL, params = list(figures_in_body_lgl = F, output_type_1L_chr = "Word", results_ls = results_ls, tables_in_body_lgl = F), output_file = paste0("AQoL_VIH", ".docx"), output_dir = paths_ls$reports_dir_1L_chr) }
Purge dataset copies
TTU::write_to_delete_ds_copies(paths_ls)
\elandscape
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