Structural equation modelling
Fit a path model that can include latent factors.
When to use it
Use structural equation modelling when the claim is a set of paths, not only a measurement model. Factors are defined with =~. Regressions between factors or observed variables use ~. A measurement-only model is confirmatory factor analysis.
Assumptions
Observed variables in the spec must be numeric columns. Rows with a missing value on those columns are dropped. Each factor needs enough indicators to be identified, and the first loading on a factor is fixed at 1. A model that is not identified, or that names a column that is not in the data, fails with an error rather than a blank table.
Running it in Tensr
Options
Prop
Type
Reading the output
Focus measured by item1 to item3, then exam score predicted from Focus and study hours, on 96 people.
| To | Op | From | Estimate | Std. Err | p-value |
|---|---|---|---|---|---|
| item1 | ~ | Focus | 1 | — | — |
| item2 | ~ | Focus | 1.38684 | 0.476729 | p = .004 |
| item3 | ~ | Focus | 1.40377 | 0.496276 | p = .005 |
| score | ~ | Focus | -0.309337 | 1.74098 | p = .859 |
| score | ~ | hours | 2.23996 | 0.655468 | p < .001 |
Structural equation model with semopy fit indices. Structural equation model with semopy fit indices. Metrics: CFI = 1.036; RMSEA = 0; SRMR = 0.077.
Reporting (APA 7)
Structural equation model with semopy fit indices. Report the estimate in the table. This procedure is not summarised by one p-value.
Coming from SPSS
The product menu is Multivariate → SEM. SPSS fits path models in Amos. =~ defines a factor and ~ defines a regression, as in lavaan.