Skip to main navigation
Skip to search
Skip to main content
Arizona State University Home
Home
Profiles
Departments and Centers
Scholarly Works
Activities
Equipment
Grants
Datasets
Prizes
Search by expertise, name or affiliation
The performance of the full information maximum likelihood estimator in multiple regression models with missing data
Craig K. Enders
Psychology
Research output
:
Contribution to journal
›
Article
›
peer-review
500
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'The performance of the full information maximum likelihood estimator in multiple regression models with missing data'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Multiple Models
82%
Multiple Regression
76%
Missing Data
67%
Maximum Likelihood Estimator
57%
Regression Model
53%
Performance
38%
Deletion
26%
Regression Coefficient
26%
Missing Completely at Random
18%
Missing at Random
16%
Imputation
15%
Maximum Likelihood Estimation
12%
Maximum Likelihood
11%
Pairwise
11%
Monte Carlo Simulation
11%
Sample Size
9%
Estimate
5%
Medicine & Life Sciences
Likelihood Functions
100%
Selection Bias
74%
Sample Size
58%
Health Care Outcome Assessment
42%
Engineering & Materials Science
Maximum likelihood
61%
Sampling
45%
Maximum likelihood estimation
37%
Social Sciences
regression
41%
performance
30%
trend
19%
simulation
10%