Effectiveness of Valid Mean Substitution in Treating Missing Data in Attitude Assessment
By H. Dodeen. 2003
123 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a92358f28e64d0803339a67f22f72e9abfabb7a1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Aubrey L. DeCarlo
- K. Bertsch
- Candice Presseau
- M. Brewster
- Bonnie Moradi
- C. DeBlaere
- Karen Kegel
- Mike C. Parent
In Management Science and Operations Research
- Aubrey L. DeCarlo
- K. Bertsch
- Candice Presseau
- M. Brewster
- Bonnie Moradi
- C. DeBlaere
- Karen Kegel
- Brandon L. Velez
In Statistics and Probability
- Aubrey L. DeCarlo
- K. Bertsch
- Candice Presseau
- M. Brewster
- Bonnie Moradi
- C. DeBlaere
- Karen Kegel
- Brandon L. Velez
Citations in the corpus
- The Protective Power of Collective Action for Sexual Minority Women of Color (2014, methodology): “For the remaining cases, ipsative (or valid) mean substitution (Dodeen, 2003) was utilized to replace missing data points on a particular measure with the participant’s mean of nonmissing data points on that measure.”
- Multiple Oppressions and the Mental Health of Sexual Minority Latina/o Individuals (2015, background): “%) were removed because they were missing more than 20% of the survey’s items, which falls outside the tolerance range recommended by prior researchers (e.g., Dodeen, 2003).”
- Handling Item-Level Missing Data (2013, background): “Dodeen (2003) provided an analysis that indicates that participant mean substitution functions well with item-level missing data compared to multiple imputation, even with fairly substantial amounts of missing data.”