Chapter 6

Overview
Sensitivity
Scales of measurement
Visual summary

Overview

Chapter 6 begins by showing students that picking a measure is not simply a matter of picking a measure with the highest validity correlation for at least two reasons.

To get valid measurements, the fit between a measure's weaknesses and the particular research design's strengths is often more important than the measure's reported validity.
Researchers always have concerns beyond validity, such as:
- Sensitivity: Being able to detect even small differences between groups
- Scales of Measurement: Being able to make specific statements about differences between groups
- Ethics: Complying with APA's ethical code
- Practical: Concerns such as using a measure that you can afford and that your research sponsors will accept as valid (the political value of having a measure with face validity).

Sensitivity

We then point out that sensitivity is important because

Researchers cannot accept the null hypothesis
Treatment effects are often small because
- ethical considerations often restrict the intensity of the treatment.
- practical concerns often restrict the duration of the treatment.
- the treatment is, at best, only one of many determinants of the participants' behavior.
Small effects are important.

At one level, having a sensitive measure is simple. All you need to do is make sure

your measure produces a variety of scores,
and produces those different scores for the right¬ rather than the wrong ¬reasons.

One "wrong " reason for getting a variety of scores would be random error. To reduce the chances that the variations in scores are not due to random error, we want a reliable measure. (The rat example on page 124 helps most students see how increased reliability can pay off in increased sensitivity.)
The right reason for getting a variety of scores would be that the measure is measuring what it is supposed to measure. Therefore, to maximize the chances that the variations in scores are for the right reasons, we should maximize the validity of our measure. Novices often fail to maximize the validity of their measures because they haven't precisely defined what it is they are trying to measure.
To get a measure that can produce a wide variety of scores:

avoid "all-or-none" measures such as "alive or dead," "happy or sad," etc.
add scale points to your measure by asking "how much" rather than "whether," and by adding questions/observations.

Once you have a measure that could possibly produce a wide variety of scores, you have a chance of making it actually produce a wide variety of scores. To maximize your chances of producing a measure that will produce a wide variety of scores, pilot test your measure.
Put another way:

Scales of measurement

We start by differentiating between the different scales of measurement. Box 6-1 ("Numbers and the toll ticket") make two concepts quite clear to most students:

the differences between the different scales of measurement, and
why psychological measurements are rarely ratio scale

We then show how different research questions require different scales of measurement. If you want to review the scale of measurement needed to answer different types of research questions, you may want to display Table 6-2.

Having established that answering certain research questions requires having a certain scale of measurement, we discuss which measures are commonly assumed to produce which kind of data. In reviewing this material, you may want to display Table 6-3. You may also want to emphasize a point illustrated by Box 6-1: that indirect measures are not ratio scale measures--and almost all measures of psychological constructs are indirect. To emphasize that indirect measures are imperfect, you may want to remind students of how mirrors may distort things (to let them see that, you may want to use one of these visuals)

Note that you could structure your discussion of scales of measurement by highlighting chapter's key figures, tables, and boxes like so:

Summary

In conclusion, the following concept map summarizes the chapter's main points.

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