Abstract
We show how to estimate a Cronbach's alpha reliability coefficient
in Stata after running a principal component or factor analysis. Alpha evaluates
to what extent items measure the same underlying content when the items are
combined into a scale or used for latent variable. Stata allows for testing the
reliability coefficient (alpha) of a scale only when all items receive homogenous
weights. We present a user-written program that computes reliability coefficients
when implementation of principal component or factor analysis shows heterogeneous
item loadings. We use data on management practices from Bloom and Van
Reenen (2010) to explain how to implement and interpret the adjusted internal
consistency measure using afa.
in Stata after running a principal component or factor analysis. Alpha evaluates
to what extent items measure the same underlying content when the items are
combined into a scale or used for latent variable. Stata allows for testing the
reliability coefficient (alpha) of a scale only when all items receive homogenous
weights. We present a user-written program that computes reliability coefficients
when implementation of principal component or factor analysis shows heterogeneous
item loadings. We use data on management practices from Bloom and Van
Reenen (2010) to explain how to implement and interpret the adjusted internal
consistency measure using afa.
| Original language | English |
|---|---|
| Place of Publication | Utrecht |
| Publisher | UU USE Tjalling C. Koopmans Research Institute |
| Number of pages | 8 |
| Publication status | Published - 2011 |
Publication series
| Name | Discussion Paper Series / Tjalling C. Koopmans Research Institute |
|---|---|
| No. | 19 |
| Volume | 11 |
| ISSN (Electronic) | 2666-8238 |
Keywords
- afa
- factor analysis
- Cronbach's alpha
- reliability
- heterogeneous scale construction
- latent variable