TY - JOUR

T1 - A Second-Order Longitudinal Model for Binary Outcomes

T2 - Item Response Theory Versus Structural Equation Modeling

AU - Wang, Chun

AU - Kohli, Nidhi

AU - Henn, Lisa

PY - 2016/5/3

Y1 - 2016/5/3

N2 - Measuring academic growth, or change in aptitude, relies on longitudinal data collected across multiple measurements. The National Educational Longitudinal Study (NELS:88) is among the earliest, large-scale, educational surveys tracking students’ performance on cognitive batteries over 3 years. Notable features of the NELS:88 data set, and of almost all repeated measures educational assessments, are (a) the outcome variables are binary or at least categorical in nature; and (b) a set of different items is given at each measurement occasion with a few anchor items to fix the measurement scale. This study focuses on the challenges related to specifying and fitting a second-order longitudinal model for binary outcomes, within both the item response theory and structural equation modeling frameworks. The distinctions between and commonalities shared between these two frameworks are discussed. A real data analysis using the NELS:88 data set is presented for illustration purposes.

AB - Measuring academic growth, or change in aptitude, relies on longitudinal data collected across multiple measurements. The National Educational Longitudinal Study (NELS:88) is among the earliest, large-scale, educational surveys tracking students’ performance on cognitive batteries over 3 years. Notable features of the NELS:88 data set, and of almost all repeated measures educational assessments, are (a) the outcome variables are binary or at least categorical in nature; and (b) a set of different items is given at each measurement occasion with a few anchor items to fix the measurement scale. This study focuses on the challenges related to specifying and fitting a second-order longitudinal model for binary outcomes, within both the item response theory and structural equation modeling frameworks. The distinctions between and commonalities shared between these two frameworks are discussed. A real data analysis using the NELS:88 data set is presented for illustration purposes.

KW - binary outcomes

KW - item response theory

KW - longitudinal

KW - structural equation modeling

UR - http://www.scopus.com/inward/record.url?scp=84948768973&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84948768973&partnerID=8YFLogxK

U2 - 10.1080/10705511.2015.1096744

DO - 10.1080/10705511.2015.1096744

M3 - Article

AN - SCOPUS:84948768973

VL - 23

SP - 455

EP - 465

JO - Structural Equation Modeling

JF - Structural Equation Modeling

SN - 1070-5511

IS - 3

ER -