08.Latent variable modeling02.Validity - sporedata/researchdesigneR GitHub Wiki

1. Use cases: in which situations should I use this method?

  • When a latent variable is to be compared to an external variable in order to verify whether it might indeed be measuring what it is supposed to measure, rather than something else/

2. Input: what kind of data does the method require?

  • A latent variable
  • One of more variables representing the concepts against which the latent variable should be validated

3. Algorithm: how does the method work?

Model mechanics

The validation is often performed with simple inferential tests, but could also be performed with more complex modeling strategies.

The validity of a procedure indicates how correctly it measures something. A method is regarded as valid if it measures what it promises to measure and the findings strongly correlate to real-world values. There are four main types of validity:

  1. Construct validity that assesses whether a measurement tool accurately represents the object being measured. It is critical for determining a method's overall validity.

  2. Content validity assesses whether a test is representative of all aspects of the construct.

  3. Face validity analyzes how appropriate the content of a test appears on the surface. Face validity is similar to content validity, but it is a more casual and subjective examination.

  4. Criterion validity assesses how effectively a test can predict a specific outcome, or how well your test's results approximate the outcomes of another test.

Validity is usually assessed through some kind of statistical method that measures the strength of the association between the scale or index's score and some other metric (depending on the type of validity being evaluated).

Reporting guidelines

Reporting to Improve Reproducibility and Facilitate Validity Assessment for Healthcare Database Studies V1.0

Data science packages

Suggested companion methods

Learning materials

  1. Books
  2. Articles

4. Output: how do I interpret this method's results?

Mock conclusions or most frequent format for conclusions reached at the end of a typical analysis.

Tables, plots, and their interpretation

Use of scatter plot with spline to demonstrate the validity to compare the scale versus the numeric variable(which could be another scale) [1]

5. SporeData-specific

Templates

Data science functions

References

[1] Patt VM, Brown GG, Thomas ML, Roesch SC, Taylor MJ, Heaton RK. Factor analysis of an Expanded Halstead-Reitan Battery and the structure of neurocognition.Archives of Clinical Neuropsychology. 2018 Feb 1;33(1):79-101.

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