Measurement modeling

Measurement modeling

This is the landing page for everything related to the measurement model that applies to your constructs and measurement instrument.

Your measurement model represents how the true scores of your construct result in the observations you make with your measurement instrument.

Measurement models are useful for gaining an understanding about your measurement procedure, which is in turn essential for knowing what you can and cannot learn based on your measurements. This understanding is attained by using the measurement model to make explicit what is known about the measurement mechanism, and what is unknown or assumed about the measurement mechanism, preferably in math.

If the measurement model can be fitted to your data, it can also be a useful tool, for example to filter out measurement error during analyses, or estimating the reliability of your instrument.

Below we have specified multiple articles where you can read more about modeling your measurements.

Think more about you sampling design

Constructing your measurement theory

A good measurement theory provides a coherent framework that links your construct(s) to observable data.

Measurement theory
[Classical test theory]
[Modern test theory]
[Formulating a measurement model]

Common measurement models

Available measurement models which may be applicable to your study or may serve as inspiration to build your own measurement model.

[Reflective and formative measurement models]
[Means and sum scores versus latent variable models]
The measurement error autoregressive model

Measurement design

Some design aspects which may influence your measurement model.