# Interpret a `REDcap`-style rule and create an expression, that represents this rule ```r util_parse_redcap_rule( rule, debug = 0, entry_pred = "REDcapPred", must_eof = FALSE ) ``` ## Arguments - `rule`: character `REDcap` style rule - `debug`: integer debug level (0 = off, 1 = log, 2 = breakpoints) - `entry_pred`: character for debugging reasons: The production rule used entry point for the parser - `must_eof`: logical if `TRUE`, expect the input to be `eof`, when the parser succeeded, fail, if not. ## Returns expression the interpreted rule c("[list(\"REDcap\")](https://help.redcap.ualberta.ca/help-and-faq/project-best-practices/data-quality/example-data-quality-rules)", "[ rules 1](https://help.redcap.ualberta.ca/help-and-faq/project-best-practices/data-quality/example-data-quality-rules)") c("[list(\"REDcap\")](https://www.ctsi.ufl.edu/files/2017/06/Calculated-Fields-%E2%80%93-REDCap-How.pdf)", "[ rules 2](https://www.ctsi.ufl.edu/files/2017/06/Calculated-Fields-%E2%80%93-REDCap-How.pdf)") c("[list(\"REDcap\")](https://www.iths.org/wp-content/uploads/REDCap-Branching-Logic-2017-202.pdf)", "[ rules 3](https://www.iths.org/wp-content/uploads/REDCap-Branching-Logic-2017-202.pdf)") For resolving left-recursive rules, [StackOverflow](https://stackoverflow.com/a/9934631) helps understanding the grammar below, just in case, theoretical computer science is not right in your mind currently. ## Examples ```r ## Not run: # rules: # pregnancies <- 9999 ~ SEX == 'm' | is.na(SEX) # pregnancies <- 9998 ~ AGE < 12 | is.na(AGE) # pregnancies = 9999 ~ dist > 2 | speed == 0 data.frame(target = "SEX_0", rule = '[speed] > 5 and [dist] > 42 or 1 = "2"', CODE = 99999, LABEL = "PREGNANCIES_NOT_ASSESSED FOR MALES", class = "JUMP") ModifyiedStudyData <- replace in SEX_0 where SEX_0 is empty, if rule fits ModifyedMetaData <- add missing codes with labels and class here subset(study_data, eval(pregnancies[[3]])) rule <- paste0('[con_consentdt] <> "" and [sda_osd1dt] <> "" and', ' datediff([con_consentdt],[sda_osd1dt],"d",true) < 0') x <- data.frame(con_consentdt = c(as.POSIXct("2020-01-01"), as.POSIXct("2020-10-20")), sda_osd1dt = c(as.POSIXct("2020-01-20"), as.POSIXct("2020-10-01"))) eval(util_parse_redcap_rule(paste0( '[con_consentdt] <> "" and [sda_osd1dt] <> "" and ', 'datediff([con_consentdt],[sda_osd1dt],"d", "Y-M-D",true) < 10')), x, util_get_redcap_rule_env()) util_parse_redcap_rule("[a] = 12 or [b] = 13") cars[eval(util_parse_redcap_rule( rule = '[speed] > 5 and [dist] > 42 or 1 = "2"'), cars, util_get_redcap_rule_env()), ] cars[eval(util_parse_redcap_rule( rule = '[speed] > 5 and [dist] > 42 or 2 = "2"'), cars, util_get_redcap_rule_env()), ] cars[eval(util_parse_redcap_rule( rule = '[speed] > 5 or [dist] > 42 and 1 = "2"'), cars, util_get_redcap_rule_env()), ] cars[eval(util_parse_redcap_rule( rule = '[speed] > 5 or [dist] > 42 and 2 = "2"'), cars, util_get_redcap_rule_env()), ] util_parse_redcap_rule(rule = '(1 = "2" or true) and (false)') eval(util_parse_redcap_rule(rule = '[dist] > sum(1, +(2, [dist] + 5), [speed]) + 3 + [dist]'), cars, util_get_redcap_rule_env()) ## End(Not run) ``` ## See Also Other parser_functions: `util_interpret_limits()`, `util_parse_assignments()`, `util_parse_interval()`

util_parse_redcap_rule function