Invariance in Measurement and Prediction Revisited
By R. Millsap. 2007
109 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/1b193dbc8e6b6cc29613d31ed7a2556c38ce3518
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Gordon W. Cheung
- Rebecca S. Lau
- Daniel F McCaffrey
- D. Dimitrov
- Denny Borsboom
- J. R. Lockwood
- Daniel A. Sass
- Florian Kunze
In Experimental and Cognitive Psychology
- Daniel F McCaffrey
- D. Dimitrov
- Rebecca S. Lau
- Denny Borsboom
- J. R. Lockwood
- Gordon W. Cheung
- Sacha Epskamp
- Eiko I. Fried
In Management Science and Operations Research
- Rebecca S. Lau
- Gordon W. Cheung
- D. Dimitrov
- Daniel F McCaffrey
- J. R. Lockwood
- Denny Borsboom
- Rex Bryan Kline
- Robert M. Klassen
Citations in the corpus
- Testing for Factorial Invariance in the Context of Construct Validation (2010, methodology): “…can be based, ideally, on sound theoretical considerations or recently developed procedures for selecting RIs (e.g., Rensvold & Cheung, 2001; Yoon & Millsap, 2007); the computations in the procedure proposed by Yoon and Millsap (2007) are less complicated than those in the procedure proposed by…”
- Correcting for Test Score Measurement Error in ANCOVA Models for Estimating Treatment Effects (2014, background): “Culpepper and Aguinis (2011) and Millsap (2007) provide expressions for bias in group differences when ME is ignored.”
- Educational Measurement (4th ed.) (2009, background): “…appear to have been missed entirely by the educational testing field (e.g., the issue of prediction vs. measurement invariance as discussed in Millsap, 1997, 2007; the distinction between reflective and formative models as discussed in Bollen & Lennox, 1991; Edwards & Bagozzi, 2000; Howell,…”
- A Direct Comparison Approach for Testing Measurement Invariance (2012, methodology): “Nevertheless, it should be noted that the MI method tends to have high Type I error and inadequate power (Yoon & Millsap, 2007).”