Sampling design

This is the landing page for everything related to how you select a subset of occasions and/or individuals from the total population of occasions and individuals you want to generalize your results to.

The way your sampling procedure is designed will directly impact what you will be able to capture about your construct. This depends for example on the distribution of your construct in reality, the presence of missing data, and how you select a subset of occasions and units from your poulation.

Think more about your sampling design

We have collected various topics for you to read more about below.

How your construct is distributed in reality

Ideally, your sample distribution closely resembles the real-world distribution of your construct.

Missing data

The sampling procedure may introduce missing data.

  • [Missing observations]
  • [Night gaps in sampling designs]
Selecting a subset of occassions

The sampling design determines how often you sample from the population of occasions.

Selecting a subset of persons

The sampling design determines how many units you sample from the population of units.


Noémi K. Schuurman

Last modified: 2025-03-31