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# Levels of Measurement and Concepts of Validity

Selecting a method to accurately measure variables can be a complex task. Some data can be transformed from one level of measurement to another, and other data cannot. Measurement instruments must also be validated to prove they accurately measure the variables in question. Consider the measurement of data and compare measurement validity to the concept of design validity.

To prepare for this Discussion:
- What is an example of data that can be transformed from one level of measurement to another and another example of data that cannot be transformed?
- Why is validity for measurement so difficult to establish?
- How are the concepts of validity for design and for measurement similar and different?
- What is the relationship between reliability and validity?

Post a response:

1. One paragraph in which you differentiate between the levels of measurement by providing an example of data that can be transformed from one level of measurement to another.
2. Another example of data that cannot be transformed.
3. Include an explanation for why some data can be transformed and some cannot.
4. Two paragraphs comparing the concept of validity for design to the concept of validity for measurement.

#### Solution Preview

1. One paragraph in which you differentiate between the levels of measurement by providing an example of data that can be transformed from one level of measurement to another.

An example of data that can be transferred from one level to another is lower level data such as ordinal and nominal data. Nominal data is considered the lowest level of data. It allows the research only to be able to place a person, object or thing into a category, or not into a category. Both the ordinal and nominal scales have the capability of capturing continuous (quantitative) data measured on a linear scale. An Ordinal scale captures all the data of a nominal level, but allows the researcher to rank the data (e.g., highest to lowest). For example, a study was conducted to show that the danger of cigarette smoking may be viewed in which certain behaviors are lacking; and focused on reinforcing behavior [e.g., self-control] (Debell & Harliss, 1992). Self-control was needed to overcome the lapses that occur between the smoking of a cigarette; and the immediate gratification of smoking another cigarette (Yang & Oliver, 2010). The amount of cigarettes smoked (the data) could be displayed in nominal categories. (e.g. , 2 per day, 3, or 4 per day)

2. Another example of data that cannot be transformed.

Considering the same example (Yang & Oliver, 2010), the ordinal scale may be used to rank the subjects from lowest to ...

#### Solution Summary

This solution discusses the relationship between reliability and validity in assessments in almost 900 words.

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