Problem of Missing Data

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Latest revision as of 20:53, 7 September 2009

Why is missing data a problem? Missing values means reduced sample size and loss of data. Fe40.png - You conduct research to measure empirical reality so missing values thwart the very purpose of research. The less data collected, the less data that can be analyzed, and reducing the data that can be analyzed reduces statistical power, which is the ability to detect real relationships in the data.

Missing values may also indicate bias in the data. Fe40.png - If the missing values are non-random, then the study is not accurately measuring the intended constructs. The results of your study may have been different if the missing data was not missing. See Why do missing values occur? for the difference between random and non-random missing data.

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