Planned missing data designs in psychological research.
…, BJ Taylor, AE Olchowski, PE Cumsille�- Psychological�…, 2006 - psycnet.apa.org
… discussion of missing data analysis, please see Graham, Cumsille, and Elek-Fisk (2003). …
However, this design is less useful for estimating correlations between items (see Graham et al.…
However, this design is less useful for estimating correlations between items (see Graham et al.…
Perceived exposure to peer and adult drinking as predictors of growth in positive alcohol expectancies during adolescence.
PE Cumsille, AG Sayer, JW Graham�- Journal of consulting and�…, 2000 - psycnet.apa.org
This study investigated the effects of change in exposure to peer and adult drinking on
changes in positive alcohol expectancies during adolescence. Covariance and mean structure …
changes in positive alcohol expectancies during adolescence. Covariance and mean structure …
Methods for handling missing data
JW Graham, PE Cumsille…�- Handbook of psychology, 2003 - Wiley Online Library
This chapter describes a general approach to handling missing data in psychological research.
It provides a theoretical background in readable, nontechnical fashion. Our overall goal …
It provides a theoretical background in readable, nontechnical fashion. Our overall goal …
Modeling prevention program effects on growth in substance use: Analysis of five years of data from the Adolescent Alcohol Prevention Trial
BJ Taylor, JW Graham, P Cumsille, WB Hansen�- Prevention Science, 2000 - Springer
… Based on the initial hypotheses for AAPT (Hansen & Graham, 1991), we could predict that
RT, Norm, and COMB programs would each be more effective than ICU in reducing cigarette …
RT, Norm, and COMB programs would each be more effective than ICU in reducing cigarette …
Missing data analysis: Making it work in the real world
JW Graham�- Annual review of psychology, 2009 - annualreviews.org
This review presents a practical summary of the missing data literature, including a sketch of
missing data theory and descriptions of normal-model multiple imputation (MI) and …
missing data theory and descriptions of normal-model multiple imputation (MI) and …
Structural equation modeling with missing data.
JW Graham, DL Coffman - 2012 - psycnet.apa.org
The missing data problem has long been an issue for data analysis of all kinds, and structural
equation modeling (SEM) was, in the early days, not exempt from such problems. The …
equation modeling (SEM) was, in the early days, not exempt from such problems. The …
Using modern missing data methods with auxiliary variables to mitigate the effects of attrition on statistical power
JW Graham, JW Graham, LM Collins�- Missing data: analysis and design, 2012 - Springer
Missing data in a field experiment may arise from a number of sources. Participants may skip
over questions inadvertently or refuse to answer them; they may offer an illegible response; …
over questions inadvertently or refuse to answer them; they may offer an illegible response; …
Adding missing-data-relevant variables to FIML-based structural equation models
JW Graham�- Structural Equation Modeling, 2003 - Taylor & Francis
Conventional wisdom in missing data research dictates adding variables to the missing
data model when those variables are predictive of (a) missingness and (b) the variables …
data model when those variables are predictive of (a) missingness and (b) the variables …
Missing data: our view of the state of the art.
JL Schafer, JW Graham�- Psychological methods, 2002 - psycnet.apa.org
Statistical procedures for missing data have vastly improved, yet misconception and unsound
practice still abound. The authors frame the missing-data problem, review methods, offer …
practice still abound. The authors frame the missing-data problem, review methods, offer …
[CITATION][C] Research methods in psychology
JW Graham, PE Cumsille, E Elek-Fisk, JA Schinka…�- Methods of handling�…, 2003