# Add PPVT scores to the database
library("L2TDatabase")
library("dplyr")
# Load external dependencies
source("inst/paths.R")
source(paths$GetSiteInfo, chdir = TRUE)
# Download/backup db beforehand
cnf_file <- file.path(getwd(), "inst/l2t_db.cnf")
l2t <- l2t_connect(cnf_file, "backend")
l2t_dl <- l2t_backup(l2t, "inst/backup")
# Get info for both sites. Function sourced via paths$GetSiteInfo
t1 <- get_study_info("TimePoint1")
t2 <- get_study_info("TimePoint2")
t3 <- get_study_info("TimePoint3")
ci1 <- get_study_info("CochlearV1")
ci2 <- get_study_info("CochlearV2")
cim <- get_study_info("CochlearMatching")
lt <- get_study_info("LateTalker")
medu <- get_study_info("MaternalEd")
dialect <- get_study_info("DialectSwitch")
process_scores <- . %>%
select(Study,
ShortResearchID = Participant_ID,
PPVT_Form,
PPVT_Completion = maybe_starts_with("PPVT_COMPLETION"),
PPVT_Raw = maybe_starts_with("PPVT_raw"),
PPVT_Standard = maybe_starts_with("PPVT_standard"),
PPVT_GSV) %>%
mutate(PPVT_Completion = format(PPVT_Completion))
df_scores <- c(t1, t2, t3, ci1, ci2, cim, lt, medu, dialect) %>%
lapply(process_scores) %>%
bind_rows()
# Combine child-study-childstudy tbls
df_cds <- tbl(l2t, "ChildStudy") %>%
left_join(tbl(l2t, "Study")) %>%
left_join(tbl(l2t, "Child")) %>%
select(ShortResearchID, Study, ChildStudyID, Birthdate) %>%
collect()
# Attach the database identifiers to the PPVT scores
df_with_ppvt <- left_join(df_scores, df_cds)
# Kids in spreadsheets not in database. Should be empty rows (attrition)
df_scores %>% anti_join(df_cds) %>% as.data.frame
df_can_be_added <- df_with_ppvt %>%
filter(!is.na(PPVT_Completion)) %>%
mutate(PPVT_Age = chrono_age(PPVT_Completion, Birthdate)) %>%
select(-Study, -ShortResearchID, -Birthdate)
# Find completely new records that need to be added
df_to_add <- find_new_rows_in_table(
data = df_can_be_added,
ref_data = l2t_dl$PPVT,
required_cols = "ChildStudyID")
df_to_add %>%
print(n = Inf)
df_with_ppvt %>%
inner_join(df_to_add) %>%
select(Study:PPVT_Completion) %>%
print(n = Inf)
# Update the remote table. An error here is a good thing if there are no new
# rows to add
append_rows_to_table(l2t, "PPVT", df_to_add)
## Find records that need to be updated
# Redownload the table
df_remote <- collect("PPVT" %from% l2t)
# Attach the database keys to latest data
df_remote_indices <- df_remote %>%
select(ChildStudyID, PPVTID)
df_local <- df_can_be_added %>%
inner_join(df_remote_indices) %>%
arrange(ChildStudyID)
# Keep just the columns in the latest data
df_remote <- match_columns(df_remote, df_local) %>%
filter(ChildStudyID %in% df_local$ChildStudyID) %>%
arrange(PPVTID)
# Preview changes with daff
library("daff")
daff <- diff_data(df_remote, df_local, context = 0)
stamp <- format(Sys.time(), "%Y-%m-%d_%H-%M")
render_diff(daff)
# save them
# render_diff(daff, file = sprintf("inst/diffs/%s_ppvt_diffs.html", stamp))
# daff::write_diff(daff, file = sprintf("inst/diffs/%s_ppvt_.csv", stamp))
# Or see them itemized in a long data-frame
create_diff_table(df_local, df_remote, "PPVTID")
overwrite_rows_in_table(l2t, "PPVT", rows = df_local, preview = TRUE)
overwrite_rows_in_table(l2t, "PPVT", rows = df_local, preview = FALSE)
# Check one last time
df_remote <- collect("PPVT" %from% l2t)
anti_join(df_remote, df_local, by = "PPVTID")
anti_join(df_local, df_remote)
anti_join(df_can_be_added, df_remote)
anti_join(df_remote, df_can_be_added)
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