How do you set up a study?

Good research is highly dependent on detailed planning. The book provides the following tips when setting up a study:

• Choose the design of your research, for example in the form of an experiment, a questionnaire, or an observational study. Weigh all the pros and cons of each method.
• If you opt for an experiment: decide whether to opt for a between-groups design (different subjects in each experimental condition) or a repeated measures design (all subjects in all conditions).
• If you choose an experiment, make sure you have enough levels of your independent variable.
• Always select more test subjects than you actually need, as there is a high chance that test subjects will drop out.
• If possible, randomly assign subjects to each experimental condition. It is important that these groups do not differ from each other on other matters. You can check this by performing a covariance analysis.
• Choose reliable and valid dependent variables.
• Anticipate possible confounding variables. These are variables other than the independent variable that can give a possible explanation for your result. Check for these confounding variables if possible.
• If you opt for the method of a survey, check in advance whether the instructions, questions and scales are formulated clearly. You do this by means of pilot testing.

How do you choose the right scales and methods?

When choosing the right scale and method, two concepts are important: reliability and validity. Both concepts can influence the quality of your data.

What does reliability mean?

The reliability of a scale indicates to what extent the scale is free from random error. There are two types of reliability:

1. Test-retest reliability: this is measured by presenting the relevant scale to two different persons in two different situations and then calculating the correlation between these two scores. The higher this correlation, the greater the test-retest reliability.
2. Internal consistency: the degree to which the items of a scale are interrelated. This can be calculated, for example, with the Cronbach's coefficient alpha in SPSS. A Cronbach's alpha of .7 or greater indicates a reliable scale.

What does validity mean?

The validity of a scale refers to the extent to which the methods measure what they intend to measure. There are different types of validity:

1. Content validity: the degree of accuracy with which the method or scale tests the intended domain or content.
2. Criterion validity: the relationship between different scale scores and a specified measurement criterion.
3. Construct validity: the relationship with other constructs; both related constructs (convergent validity) and unrelated constructs (discriminant validity).

How do you prepare a questionnaire?

When preparing a questionnaire, it is important to keep in mind what statistical methods you will need to analyze the data. Depending on the statistical technique, you have to ask a certain question in a specific way.

What are different types of questions?

Many questions can be classified into two groups: open-ended questions and closed questions. A closed question gives respondents multiple answer options. Closed questions can be quickly converted to a numeric format in SPSS. For example, answer "yes" can be coded with number 1 and answer "no" with number 2. The answers to open-ended questions can be divided into different categories, for example work or relationships. A combination of open-ended and closed questions often works best in a study.

What are different scales of answers?

It is important to choose the correct scale when creating answer formats. For example, if you want to calculate a correlation, you need to know the exact ages of your respondents. In addition, it is often useful to apply a Likert-type scale: People do not simply answer whether they agree or disagree with the question, but indicate to what extent they agree with a statement; for example on a scale from 1 to 6.