Essay on Overview of Internal and External Validity

1836 Words 8 Pages
Validity
Generally speaking statistics, research, and reports are everywhere. Statistical data is reported regarding professional and amateur athletic sports, the weather, social activities such as how many people did or did not enjoy a particular movie, and which product one should purchase. Additionally, there are reports which impact how people make serious choices about healthcare, career paths, education, and purchasing a home. Finally, professionals and consumers make decisions about physical and mental treatment approaches. With so many different people relying on data for a variety of reasons, questions of credibility and application come to mind. How trustworthy is the data? Experts are educated to digest, metabolize, and
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There are many threats to validity and some are difficult to control. For example, according to Campbell and Stanley (1997) a longitudinal study can last for many years during which time individuals change because of the experiences they encounter. Additionally, Campbell and Stanley described the influence of fatigue or boredom can have on results, when testing becomes lengthy (Smith & Davis, 2007). Morgan and Gilner (1997) explain that when gauging validity one has to consider if the variables were measured correctly. These authors also state that accurate measurement is directly related to the instrument used in determining the outcome. Another component, according to Morgan and Gilner (1997) is the power of the research project. Power is linked to sample size. In simple terms, how many participants actually contributed to the study? Although Campbell and Stanley (1997) explain that the random assignment of participants is advantageous, it does not eliminate the threat to validity. They go on to say that participants who realize or learn that they are in the control group may not expend as much effort, or overcompensate (Morgan & Gliner, 1997). A simple method for monitoring and managing control groups is to isolate them from one another (Morgan & Gliner, 1997). For example, if the study is

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