TY - JOUR
T1 - Temporal Patterns of Variable Relationships in Person-Oriented Research
T2 - Longitudinal Models of Configural Frequency Analysis
AU - von Eye, Alexander
AU - Mun, Eun Young
AU - Bogat, G. Anne
PY - 2008/3/1
Y1 - 2008/3/1
N2 - This article reviews the premises of configural frequency analysis (CFA), including methods of choosing significance tests and base models, as well as protecting α, and discusses why CFA is a useful approach when conducting longitudinal person-oriented research. CFA operates at the manifest variable level. Longitudinal CFA seeks to identify those temporal patterns that stand out as more frequent (CFA types) or less frequent (CFA antitypes) than expected with reference to a base model. A base model that has been used frequently in CFA applications, prediction CFA, and a new base model, auto-association CFA, are discussed for analysis of cross-classifications of longitudinal data. The former base model takes the associations among predictors and among criteria into account. The latter takes the auto-associations among repeatedly observed variables into account. Application examples of each are given using data from a longitudinal study of domestic violence. It is demonstrated that CFA results are not redundant with results from log-linear modeling or multinomial regression and that, of these approaches, CFA shows particular utility when conducting person-oriented research.
AB - This article reviews the premises of configural frequency analysis (CFA), including methods of choosing significance tests and base models, as well as protecting α, and discusses why CFA is a useful approach when conducting longitudinal person-oriented research. CFA operates at the manifest variable level. Longitudinal CFA seeks to identify those temporal patterns that stand out as more frequent (CFA types) or less frequent (CFA antitypes) than expected with reference to a base model. A base model that has been used frequently in CFA applications, prediction CFA, and a new base model, auto-association CFA, are discussed for analysis of cross-classifications of longitudinal data. The former base model takes the associations among predictors and among criteria into account. The latter takes the auto-associations among repeatedly observed variables into account. Application examples of each are given using data from a longitudinal study of domestic violence. It is demonstrated that CFA results are not redundant with results from log-linear modeling or multinomial regression and that, of these approaches, CFA shows particular utility when conducting person-oriented research.
KW - auto-association configural frequency analysis
KW - configural frequency analysis
KW - longitudinal models
KW - person-oriented research
KW - prediction configural frequency analysis
UR - http://www.scopus.com/inward/record.url?scp=42049096301&partnerID=8YFLogxK
U2 - 10.1037/0012-1649.44.2.437
DO - 10.1037/0012-1649.44.2.437
M3 - Article
C2 - 18331134
AN - SCOPUS:42049096301
SN - 0012-1649
VL - 44
SP - 437
EP - 445
JO - Developmental Psychology
JF - Developmental Psychology
IS - 2
ER -