Researchers have to consider a host of factors when planning their research and analyzing their data. This chapter discusses a number of important research considerations. For instance, when planning research it is important to have a large enough sample to prevent conducting an underpowered study that would be unable to detect true differences when they existed. When selecting measures, researchers should understand exactly what they are assessing and determine if the scales used have a history of producing valid and reliable scores with similar samples. When developing measures, researchers should avoid the jingle jangle fallacy and avoid creating scales that are redundant with already developed scales or use names that obfuscate the reader. When analyzing their data scientists should avoid dichotomizing continuous constructs and should shun stepwise regression techniques. When compiling findings, researchers need to consider if their results are meaningful, so effect sizes should be reported and interpreted in light of absolute standards and relative to prior research.
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