data-raw/Clippings.R

In ready4-dev/youthvars: Describe and Validate Youth Mental Health Economic Datasets

#   tibble::tribble(
#   ~var_name_chr, ~coef_dbl,
#   "vD1", 0.0719264,
#   "vD2", 0.1027818,
#   "vD3", 0.2519563,
#   "vD4", 0.3201172,
#   "vD5", 0.1288289,
#   "vD6", 0.2052164,
#   "Constant", - 0.0444493
# ) %>% ready4fun::make_pkg_ds_ls(db_1L_chr = "aqol6d_from_8d_coefs_lup_tb",
#                                 title_1L_chr = "Model 2A Coefficients To Weight AQoL6D",
#                                 desc_1L_chr = "Coefficients for model to predict AQoL-6D utility score from AQoL-8D. The optimal model is Model 2A (see Richardson et al (2011, 18-19)*/",
#                                 url_1L_chr = "https://www.aqol.com.au/index.php/scoring-algorithms"),
# tibble::tribble(
#   ~Question_chr, ~Answer_1_dbl, ~Answer_2_dbl, ~Answer_3_dbl, ~Answer_4_dbl, ~Answer_5_dbl, ~Answer_6_dbl,
#   "Q1", 0, 0.073, 0.435, 0.820, 1, NA_real_,
#   "Q2", 0, 0.033, 0.240, 0.471, 0.840,1,
#   "Q3", 0, 0.041, 0.251, 0.570, 0.830, 1,
#   "Q4", 0, 0.040, 0.297, 0.797, 1, NA_real_,
#   "Q5", 0, 0.074, 0.461, 0.841, 1, NA_real_,
#   "Q6", 0, 0.193, 0.759, 1, NA_real_,NA_real_,
#   "Q7", 0, 0.197, 0.648, 1, NA_real_, NA_real_,
#   "Q8", 0, 0.133, 0.392, 0.838, 1, NA_real_,
#   "Q9", 0, 0.142, 0.392, 0.824, 1, NA_real_,
#   "Q10", 0, 0.097, 0.330, 0.784, 1, NA_real_,
#   "Q11", 0, 0.064, 0.368, 0.837, 1, NA_real_,
#   "Q12", 0, 0.056, 0.338, 0.722, 1, NA_real_,
#   "Q13", 0, 0.055, 0.382, 0.774, 1, NA_real_,
#   "Q14", 0, 0.057, 0.423, 0.826, 1, NA_real_,
#   "Q15", 0, 0.133, 0.642, 1, NA_real_,NA_real_,
#   "Q16", 0, 0.200, 0.758, 1, NA_real_, NA_real_,
#   "Q17", 0, 0.072, 0.338, 0.752, 1, NA_real_,
#   "Q18", 0, 0.033, 0.223, 0.621, 0.843, 1,
#   "Q19", 0, 0.024, 0.205, 0.586, 0.826, 1,
#   "Q20", 0, 0.187, 0.695, 1, NA_real_,NA_real_
# ) %>% ready4fun::make_pkg_ds_ls(db_1L_chr = "aqol6d_adult_disv_lup_tb",
#                                 title_1L_chr = "AQoL6D (adult version) item disvalues lookup table",
#                                 desc_1L_chr = "Disutility weights for individual AQoL6D (adult version) items.",
#                                 url_1L_chr = "https://www.aqol.com.au/index.php/scoring-algorithms"),
# tibble::tibble(Question_dbl = 1:20,
#                Domain_chr = c(rep("IL",4),
#                               rep("REL",3),
#                               rep("MH",4),
#                               rep("COP",3),
#                               rep("P",3),
#                               rep("SEN",3))) %>%
#   ready4fun::make_pkg_ds_ls(db_1L_chr = "aqol6d_domain_qs_lup_tb",
#                             title_1L_chr = "AQoL6D dimension questions lookup table",
#                             desc_1L_chr = "Breakdown of which questions relate to which dimension of the AQoL6D.",
#                             url_1L_chr = "https://www.aqol.com.au/index.php/scoring-algorithms"),
# tibble::tribble(
#   ~Dimension_chr, ~Constant_dbl,
#   "IL",-0.978,
#   "RL", -0.923,
#   "MH", -0.983,
#   "COP", -0.930,
#   "P", -0.96,
#   "SEN", -0.851) %>%
#   ready4fun::make_pkg_ds_ls(db_1L_chr = "aqol6d_dim_sclg_con_lup_tb",
#                             title_1L_chr = "AQoL6D dimension scaling constants lookup table",
#                             desc_1L_chr = "Scaling constants for each dimension of AQoL6D.",
#                             url_1L_chr = "https://www.aqol.com.au/index.php/scoring-algorithms"),
# tibble::tribble(
#   ~Question_chr, ~Worst_Weight_dbl,
#   "Q1", 0.385412,
#   "Q2", 0.593819,
#   "Q3", 0.630323,
#   "Q4", 0.794888,
#   "Q5", 0.64303,
#   "Q6", 0.697742,
#   "Q7", 0.508658,
#   "Q8", 0.640377,
#   "Q9", 0.588422,
#   "Q10", 0.648748,
#   "Q11", 0.71122,
#   "Q12", 0.415694,
#   "Q13", 0.636994,
#   "Q14", 0.773296,
#   "Q15", 0.631833,
#   "Q16", 0.767573,
#   "Q17", 0.652241,
#   "Q18", 0.580696,
#   "Q19", 0.463022,
#   "Q20", 0.604613
# ) %>% ready4fun::make_pkg_ds_ls(db_1L_chr = "aqol6d_adult_itm_wrst_wts_lup_tb",
#                                 title_1L_chr = "AQoL6D (adult) item worst weightings lookup table",
#                                 desc_1L_chr = "Worst weightings for individual items in AQoL6D (adult version).",
#                                 url_1L_chr = "https://www.aqol.com.au/index.php/scoring-algorithms"),
#
# read.csv("data-raw/csvs/AQoL_6D_Dim_Scaling.csv", stringsAsFactors = F, fileEncoding="UTF-8-BOM") %>%
#   ready4fun::make_pkg_ds_ls(db_1L_chr = "adol_dim_sclg_eqs_lup",
#                             title_1L_chr = "AQoL6D (adolescent) item worst weightings equations lookup table",
#                             desc_1L_chr = "Dimension scaling equations for adolescent version of AQoL6D scoring algorithm.",
#                             url_1L_chr = "https://www.aqol.com.au/index.php/scoring-algorithms"),
# read.csv("data-raw/csvs/aqol_valid_stata.csv") %>%
#   ready4fun::make_pkg_ds_ls(db_1L_chr = "aqol6d_adult_vldn_pop_with_STATA_scores_tb",
#                             title_1L_chr = "STATA comparison validation synthetic population",
#                             desc_1L_chr = "Synthetic population following application of STATA adult scoring algorithm.",
#                             url_1L_chr = "https://www.aqol.com.au/index.php/scoring-algorithms"),