The advantages of analysing multiple individuals are that it allows for generalization of findings to others. However, it does not tell us anything about the individual. The analysis of an individual does not allow for generalization to others but does tell us something about the individual.

In an N=1 analysis, the baseline is compared with a treatment for a single individual. Normative comparisons make use of comparing a single individual to a distribution of the norm (e.g. normal distribution of test scores of a normative sample).

The question of whether there is an improvement requires a comparison while the question of whether there is a significant improvement requires multiple observations (e.g. baseline). There are several ways in which N=1 designs bridge the gap between science and practice:

1. Multiple N=1 studies in practice indicating improvement implies the need for a randomized controlled trial as

There are three types of theories:

1. Focusing on manifest variables
   This entails focusing on the variables that can be observed (e.g. a person is distracted and has trouble organizing tasks).
2. Focusing on latent variables
   This entails focusing on the variables that are indirectly observed (e.g. based on other variables.) (e.g. a person has ADHD).
3. Focusing on relations between manifest variables (i.e. network models)
   This entails focusing on the relations between the variables that can be observed (e.g. a person is distracted and thus has trouble organizing tasks).

The DSM-5 makes use of theories based on latent variables.

A theory focusing on manifest variables has the problem of whether there is a cut-off or not (e.g. a person is distracted or not). Besides that, if there is a cut-off, the question is what the cut-off is. Lastly,