Measurement in research

Measurement in research

If it exists, it can be measured. In everyday usage, measurement occurs when an established yardstick verifies the height, weight, or other features of a physical object. How well you like a song, a painting, or the personality of a friend is also a measurement. In a dictionary sense, to measure is to discover the extent, dimensions, quantity, or capacity of something, especially by comparison with a standard. We measure casually in daily life, but in research the requirements for measurement are rigorous. 

What is measured?

Variables being studied in research may be classified as objects or as properties. Objects include the things of ordinary experience, such as tables, people, books, and automobiles. Objects also include things that are not as concrete, such as genes, attitudes, neutrons, and peer-group pressure. Properties are the characteristics of the objects. A person's physical properties may be stated in terms of weight, height, and posture. Psychological properties include attitudes and intelligence.

Social properties include leadership ability, class affiliation, or status. These and many other properties of an individual can be measured in a research study.

Types (levels) of Measurement

Combinations of these characteristics of classification, order, distance, and origin provide four widely used classifications of measurement scales: (1) nominal, (2) ordinal, (3) interval, and (4) ratio.

1. Nominal Measurement

Nominal data are counted data. Each individual can be a member of only one set, and all other members of the set have the same defining characteristic. Such categories as nationality, gender, socioeconomic status, race, occupation, or religious affiliation provide examples. Nominal scales are non-orderable, but in some situations, this simple enumeration or counting is the only feasible method of quantification and may provide an acceptable basis for statistical analysis. In nominal (classificatory) measurement the numerical values simply name the attribute uniquely. No ordering of the cases is implied. For example, jersey numbers in football are measures at the nominal level. A player with the number 30 is not more of anything than a player withnumber15 and is certainly not twice whatever number 15 is.

In business and social science research, nominal data are probably more widely collected than any other is. With nominal data, you are collecting information on a variable that naturally or by design can be grouped into two or more categories that are mutually exclusive and collectively exhaustive. A nominal scale is the least precise method of quantification. A nominal scale describes differences between things by assigning them to categories.

In nominal measurement members of any two groups are never equivalent but all members of any one group are always equivalent. And this equivalence relationship is reflexive, transitive, and symmetrical (Singh, 1998: 7).

2. Ordinal Measurement

In ordinal measurement, the attributes can be rank-ordered. Ordinal data are possible if the transitivity postulate is fulfilled. Sometimes it is possible to indicate not only that things differ but that they differ in amount or degree. Ordinal measurement permits the ranking of items or individuals from highest to lowest (Best & Kahn, 2002: 209). The criteria for highest to lowest ordering is expressed as relative position or rank in a group: 1st, 2nd, 3rd, 4th, 5th, ..., nth. Ordinal measures have not absolute values, and the real differences between adjacent ranks may not be equal. Ranking spaces them equally, though they may not actually be equally spaced.

Ordinal measures reflect which person or object is larger or smaller, heavier or lighter, brighter or duller, harder or softer, etc ., than others. Socioeconomic status is a good example of ordinal measurement.

3. Interval Measurement

An arbitrary scale based on equal units of measurements indicates how much of a given characteristic is present. The difference in the amount of the characteristic possessed by persons with scores of 90 and 91 is assumed to be equivalent to that between persons with scores of 60 and 61.

The interval scale represents a decided advantage over nominal and ordinal scales because it indicates the relative amount of a trait or characteristic. Its primary limitation is the lack of a true zero. It does not have the capacity to measure the complete absence of the trait, and a measure of 90 does not mean that a person has twice as much of the trait as someone with a score of 45. Psychological tests and inventories are interval scales and have this limitation, although they can be added, subtracted, multiplied, and divided. This measurement includes all the characteristics of the nominal and ordinal scale of measurement. Here the unit of measurement is constant and equal. This is the reason why interval measurement is also referred to as equal interval measurement. Since the numbers are after equal intervals, they can legitimately be added and subtracted from each other.

4. Ratio Measurement

It is the highest level of measurement and has all the properties of nominal ordinal and interval scales plus an absolute or true zero point. The salient feature of the ratio scale is that the ratio of any two numbers is independent of the unit of measurement and therefore, it can meaningfully be equated. For example, the ratio of 16:28 is equal to 4:7.

The common examples of ratio scale are the measures of weight, width, length, loudness, and so on. It is obvious, therefore, that ratio scales are common among physical sciences rather than among social sciences. To be clearer, a student must know the distinction between the interval scales and the ratio scale. The fundamental difference is that in the former the zero points are arbitrary but in the latter the zero points are true.

Temperature measured in terms of Fahrenheit and Celsius is an example of interval scale and length measured in terms of feet and inches is an example of the ratio scale. When we measure the length of two sticks and say the one stick is 3' long and another 6' long, we have a clear idea that the second stick is twice the length of the first stick. This is because 6'means actually 6' from 0', and 3' from 0'.

But suppose the maximum temperature of weather today is 40 degrees C and it was 20 degrees C last year on the same date. Can we say now, that today is twice as warm as it was on the same date last year? Obviously, the answer is no because 0 degrees C does not reflect the complete absence of temperature (true zero points) in Celsius measurement. A value on either scale can be converted to the other by using the formula F = 32+9/5C.