I am an Assistant Professor in Special Education at Utah State University focusing on preventing reading failure. I am interested in how individual differences in children and teachers influence the effectiveness of reading intervention. I use advanced statistical models and single case research designs to answer my questions and try to share all aspects of my work openly.
Contributions
This is the data sample needed to run the CFA for PV wave 1.
These are the generated factor scores through MNLFA for PV.
This is the data sample needed to generate factor scores for the PV MNLFA models
This is the calibration data sample to run the measurement invariance models for PV using MNLFA in Mplus.
This is the accepted Stage 1 registered report version of the paper "Examining differential intervention effects: Do Individualized Student Intervention effects vary by student abilities and characteristics?".
This code takes 4 different datasets generated through the R code (EC_IDA_QR) and runs the MNLFA procedures in Mplus. All aspects of MNLFA are included, CFA, initial measurement variance, calibration, and scoring. Each section should be run separately in Mplus.
This code takes 4 different datasets generated through the R code (EC_IDA_QR) and runs the MNLFA procedures in Mplus. All aspects of MNLFA are included, CFA, initial measurement variance, calibration, and scoring. Each section should be run separately in Mplus.
This code includes everything necessary to replicate analyses in the Instructional Coaches Typology paper (see preprint).
This document contains the definitions of the three types of support that were shared with participants.
These data are ties between alters in the network. These data are needed to visualize the complete network using ego and alter data as well.
