J L Schafer
Affiliation: Pennsylvania State University
- Using data augmentation to obtain standard errors and conduct hypothesis tests in latent class and latent transition analysisStephanie T Lanza
The Methodology Center, Pennsylvania State University, State College, PA 16801, USA
Psychol Methods 10:84-100. 2005..DA is demonstrated with an example involving tests of ethnic differences, gender differences, and an Ethnicity x Gender interaction in the development of adolescent problem behavior...
- Multiple imputation: a primerJ L Schafer
Department of Statistics, Pennsylvania State University, University Park 16802 6202, USA
Stat Methods Med Res 8:3-15. 1999..Essential features of multiple imputation are reviewed, with answers to frequently asked questions about using the method in practice...
- Missing data: our view of the state of the artJoseph L Schafer
Department of Statistics and The Methodology Center, Pennsylvania State University, University Park 16802, USA
Psychol Methods 7:147-77. 2002..Although not yet in the mainstream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art...
- Average causal effects from nonrandomized studies: a practical guide and simulated exampleJoseph L Schafer
Department of Statistics, The Pennsylvania State University, PA, USA
Psychol Methods 13:279-313. 2008..Throughout the article, the authors offer insights and practical guidance for researchers who attempt causal inference with observational data...
- A comparison of inclusive and restrictive strategies in modern missing data proceduresL M Collins
The Methodology Center and Department of Human Development and Family Studies, The Pennsylvania State University, University Park 16802, USA
Psychol Methods 6:330-51. 2001..As implemented in currently available software, the ML approach tends to encourage the use of a restrictive strategy, whereas the MI approach makes it relatively simple to use an inclusive strategy...
- On the performance of random-coefficient pattern-mixture models for non-ignorable drop-outHakan Demirtas
Department of Statistics and The Methodology Center, Pennsylvania State University, University Park, PA 16802, U S A
Stat Med 22:2553-75. 2003....