Types of Missing Data
Missing data can occur because of nonresponse: no information is provided for several items or no information is provided for a whole unit. Some items are more sensitive for nonresponse than others, for example items about private subjects such as income.
Dropout is a type of missingness that occurs mostly when studying development over time. In this type of study the measurement is repeated after a certain period of time. Missingness occurs when participants drop out before the test ends and one or more measurements are missing.
Sometimes missing values are caused by the researchers themselves. If data collection was not done properly or if mistakes were made with the data entry (Ader, H.J., Mellenbergh, G.J. 2008).
And a great deal of missing data arise in cross-national research in economics, sociology, and political science because governments choose not to, or fail to, report critical statistics for one or more years (Messner 1992).
It is important to question why the data is missing, this can help with finding a solution to the problem. If the values are missing at random there is still information about each variable in each unit but if the values are missing systematically the problem is more severe because the sample cannot be representative of the population. For example: a research is done about the relation between IQ and income. If participants with an over average IQ do not answer the question ‘What is your salary?’ the results of the research may show that there is no association between IQ and salary, while in fact there is a relationship. Because of these problems, methodologists routinely advise researchers to design research so as to minimize the incidence of missing values (Ader, H.J., Mellenbergh, G.J. 2008).
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