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Levels of Measurement

How things are measured is of great importance, because the method used for measuring the qualities of a variable gives researchers information about how one should be interpreting those measurements. Similarly, the precision or accuracy of the measurement used can lead to differing outcomes of research findings, and it could potentially limit the statistical analyses that could be performed on the data collected.

Measurement is generally described as the assignment of numbers or labels to qualities of a variable or outcome by following a set of rules. There are a few important items to note in this definition. First, measurement is described as an assignment because the researcher decides what values to assign to each quality. For instance, on a football team, the coach might assign each team member a number. The actual number assigned does not necessarily have any significance, as player #12 could just have easily been assigned #20 instead. The important point is that each player was assigned a number. Second, it is also important to notice that the number or label is assigned to a quality of the variable or outcome. Each thing that is measured generally measures only one aspect of that variable. So one could measure an individual's weight, height, intelligence, or shoe size, and one would discover potentially important information about an aspect of that individual. However, just knowing a person's shoe size does not tell everything there is to know about that individual. Only one piece of the puzzle is known. Finally, it is important to note that the numbers or labels are not assigned willy-nilly but rather according to a set of rules. Following these rules keeps the assignments constant, and it allows other researchers to feel confident that their variables are measured using a similar scale to other researchers, which makes the measurements of the same qualities of variables comparable.

These scales (or levels) of measurement were first introduced by Stanley Stevens in 1946. As a psychologist who had been debating with other scientists and mathematicians on the subject of measurement, he proposed what is referred to today as the levels of measurement to bring all interested parties to an agreement. Stevens wanted researchers to recognize that different varieties of measurement exist and that types of measurement fall into four proposed classes. He selected the four levels through determining what was required to measure each level as well as what statistical processes could reasonably be performed with variables measured at those levels. Although much debate has ensued on the acceptable statistical processes (which are explored later), the four levels of measurement have essentially remained the same since their proposal so many years ago.

The Four Levels of Measurement

Nominal

The first level of measurement is called nominal. Nominal-level measurements are names or category labels. The name of the level, nominal, is said to derive from the word nomin-, which is a Latin prefix meaning name. This fits the level very well, as the goal of the first level of measurement is to assign classifications or names to qualities of variables. If “type of fruit” was the variable of interest, the labels assigned might be bananas, apples, pears, and so on. If numbers are used as labels, they are significant only in that their numbers are different but not in amount. For example, for the variable of gender, one might code males = 1 and females = 2. This does not signify that there are more females than males, or that females have more of any given quality than males. The numbers assigned as labels have no inherent meaning at the nominal level. Every individual or item that has been assigned the same label is treated as if they are equivalent, even if they might differ on other variables. Note also from the previous examples that the categories at the nominal level of measurement are discrete, which means mutually exclusive. A variable cannot be both male and female in this example, only one or the other, much as one cannot be both an apple and a banana. The categories must not only be discrete, but also they must be exhaustive. That is, all participants must fit into one (and only one) category. If participants do not fit into one of the existing categories, then a new category must be created for them. Nominal-level measurements are the least precise level of measurement and as such, tell us the least about the variable being measured. If two items are measured on a nominal scale, then it would be possible to determine whether they are the same (do they have the same label?) or different (do they have different labels?), but it would not possible to identify whether one is different from the other in any quantitative way. Nominal-level measurements are used primarily for the purposes of classification.

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