QMB exam 2
Missing Data - Answer-Data from a participant that are not available for one or more variables of
interest. In surveys, missing data typically occur when participants intentionally or accidentally skip,
refuse to answer, or do not know the answer to measurement question and are reluctant to guess.
Missing data also occur due to researcher error, malfunctioning software or equipment, corrupted data
files, and changes in the research or instrument design after data were collected from some participants,
such as when variables are dropped or added. In longitudinal studies, missing data may result from
participants dropping out of the study or being absent for one or more data collection periods.
Data missing completely at random (MCAR) - Answer-High probability that missing data for a particular
variable ARE NOT dependent on the variable itself and ARE NOT dependent on another variable in the
data record (e.g., a participant inadvertently skips a question).
Data missing at random (MAR) - Answer-High probability that missing data for a particular variable are
NOT dependent on the variable itself but ARE dependent on another variable in the data record (e.g.,
the answer to the first question of a branched-question set might cause missing data to the second
question within the branched-question set).
Data missing but not missing at random (NMAR) - Answer-High probability that missing data for a
particular variable ARE dependent on the variable itself and ARE NOT dependent on other variables in
the data record (e.g., participant finds the question unanswerable or too sensitive and skips the
question).
Content analysis - Answer-A systematic and objective approach used to code message characteristics so
researchers can treat diverse textual or verbal content quantitatively as they look for patterns and draw
inferences.
Missing Data - Answer-Data from a participant that are not available for one or more variables of
interest. In surveys, missing data typically occur when participants intentionally or accidentally skip,
refuse to answer, or do not know the answer to measurement question and are reluctant to guess.
Missing data also occur due to researcher error, malfunctioning software or equipment, corrupted data
files, and changes in the research or instrument design after data were collected from some participants,
such as when variables are dropped or added. In longitudinal studies, missing data may result from
participants dropping out of the study or being absent for one or more data collection periods.
Data missing completely at random (MCAR) - Answer-High probability that missing data for a particular
variable ARE NOT dependent on the variable itself and ARE NOT dependent on another variable in the
data record (e.g., a participant inadvertently skips a question).
Data missing at random (MAR) - Answer-High probability that missing data for a particular variable are
NOT dependent on the variable itself but ARE dependent on another variable in the data record (e.g.,
the answer to the first question of a branched-question set might cause missing data to the second
question within the branched-question set).
Data missing but not missing at random (NMAR) - Answer-High probability that missing data for a
particular variable ARE dependent on the variable itself and ARE NOT dependent on other variables in
the data record (e.g., participant finds the question unanswerable or too sensitive and skips the
question).
Content analysis - Answer-A systematic and objective approach used to code message characteristics so
researchers can treat diverse textual or verbal content quantitatively as they look for patterns and draw
inferences.
