Introduction

This table links study specific missing codes with a standard definition in dataquieR to derive response rates. As missing codes may vary across data elements, multiple missing lists may be needed and linked via a key at the item level list.


Missing tables for data quality reporting


CODE_VALUE

Defines the different levels associated with missing data or jumps as defined in the study, i.e., the missing categories. Any code will be used to identify the missing or jump values in the data.

CAVEAT: currently, within a variable, missing and jump codes must match the data type of the variable. For dates, for example, the missing table can only contain missing codes in date time format, such as 1800.01.01 00:00:00 AM; and not numeric codes such as 99981. This must be kept in mind also for the item level metadata columns MISSING_LIST and JUMP_LIST.


CODE_LABEL

Sets the interpretation of the codes, usually they correspond to the labels assigned in the study. For example, the code labels may be as follows.

CODE_VALUE CODE_LABEL
2 99981 Missing - exclusion criteria
9 99988 Missing - optional value
11 99990 Deleted - contradiction
17 88880 JUMP 88880


CODE_CLASS

Assigns the meaning of CODE_VALUE according to whether the code represents a missing or a jump value. For the missing codes defined above, the code labels could be as follows.

CODE_VALUE CODE_LABEL CODE_CLASS
2 99981 Missing - exclusion criteria MISSING
9 99988 Missing - optional value MISSING
11 99990 Deleted - contradiction MISSING
17 88880 JUMP 88880 JUMP


CODE_INTERPRET

Defines the interpretation of the missing and jump values using the AAPOR concept. The acronym from AAPOR suffices as an entry. For more details see the explanation on qualified missingness labels from AAPOR.

For the codes presented earlier, the AAPOR lables may be the following.

CODE_VALUE CODE_LABEL CODE_INTERPRET
2 99981 Missing - exclusion criteria NE
9 99988 Missing - optional value NE
11 99990 Deleted - contradiction O
17 88880 JUMP 88880 NE