# construct data ---------------------------------------------------------------
# idx: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
# ---------------------------------------------------------------------------------------------
id <- c(1, 1, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6)
cyc <- c(1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 3, 3, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2)
preg <- c(0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1)
sex <- c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)
age <- c(2, 2, 2, 2, 2, 0, 0, 0, 7, 7, 7, 7, 7, 7, 7, 2, 2, 9, 9, 9, 9, 5, 5, 5, 5, 5, 5, 5, 5)
bmi <- c(1, 1, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2)
edu <- c(2, 2, 2, 2, 2, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 2, 2, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0)
opk <- c(0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0)
drnk <- c(0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0)
# all vars are factors except for `age`
bmi <- as.factor(bmi)
edu <- as.factor(edu)
opk <- as.factor(opk)
drnk <- as.factor(drnk)
# all vars have missing except for `edu`
base_blocks <- list(1:5, 6:8, 9:15, 16:17, 18:21, 22:29)
cyc_blocks <- list(1:2, 3:5, 6:8, 9:10, 11:13, 14:15, 16:17, 18:19, 20:21, 22:27, 28:29)
sex[c(7, 13, 14, 17, 20, 21, 25)] <- NA_real_
age[base_blocks[1:3] %>% unlist] <- NA_real_
bmi[base_blocks[5:6] %>% unlist] <- NA_integer_
opk[cyc_blocks[c(1, 2, 3, 6, 9)] %>% unlist] <- NA_integer_
drnk[c(9, 12, 14, 18, 20, 26, 27, 29)] <- NA_integer_
comb_dat <- data.frame(id = id,
cyc = cyc,
preg = preg,
sex = sex,
age = age,
bmi = bmi,
edu = edu,
opk = opk,
drnk = drnk)
model_with_intercept <- formula(~ age + bmi + edu + opk + drnk)
model_no_intercept <- formula(~ 0 + age + bmi + edu + opk + drnk)
expan_with_intercept <- expand_model_rhs(comb_dat, model_with_intercept)
expan_no_intercept <- expand_model_rhs(comb_dat, model_no_intercept)
cov_with_intercept_info <- get_cov_col_miss_info(expan_with_intercept, model_with_intercept, "all")
cov_no_intercept_info <- get_cov_col_miss_info(expan_no_intercept, model_no_intercept, "all")
var_nm <- list(id = "id",
cyc = "cyc",
preg = "preg",
sex = "sex",
all_base = c("id", "age", "bmi"),
all_cyc = c("id", "cyc", "preg", "opk"))
# TODO: remove data duplication above
# target output ----------------------------------------------------------------
u_with_intercept <- expan_with_intercept
u_with_intercept[is.na(u_with_intercept[, "age"]), "age"] <- mean(u_with_intercept[, "age"], na.rm = TRUE)
u_with_intercept[is.na(u_with_intercept[, "bmi1"]), "bmi1"] <- 1
u_with_intercept[is.na(u_with_intercept[, "bmi2"]), "bmi2"] <- 0
u_with_intercept[is.na(u_with_intercept[, "bmi3"]), "bmi3"] <- 0
u_with_intercept[is.na(u_with_intercept[, "opk1"]), "opk1"] <- 1
u_with_intercept[is.na(u_with_intercept[, "drnk1"]), "drnk1"] <- 1
u_no_intercept <- expan_no_intercept
u_no_intercept[is.na(u_no_intercept[, "age"]), "age"] <- mean(u_no_intercept[, "age"], na.rm = TRUE)
u_no_intercept[is.na(u_no_intercept[, "bmi0"]), "bmi0"] <- 1
u_no_intercept[is.na(u_no_intercept[, "bmi1"]), "bmi1"] <- 0
u_no_intercept[is.na(u_no_intercept[, "bmi2"]), "bmi2"] <- 0
u_no_intercept[is.na(u_no_intercept[, "bmi3"]), "bmi3"] <- 0
u_no_intercept[is.na(u_no_intercept[, "opk1"]), "opk1"] <- 1
u_no_intercept[is.na(u_no_intercept[, "drnk1"]), "drnk1"] <- 1
# begin testing ----------------------------------------------------------------
test_get_u_miss_filled_in <- function() {
out_with_intercept <- get_u_miss_filled_in(expan_with_intercept, cov_with_intercept_info)
identical(u_with_intercept, out_with_intercept)
out_no_intercept <- get_u_miss_filled_in(expan_no_intercept, cov_no_intercept_info)
identical(u_no_intercept, out_no_intercept)
}
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