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Fitting Residual Error Structures for Growth Models in SAS PROC MCMC
Daniel McNeish
Research output
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Contribution to journal
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Article
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peer-review
2
Scopus citations
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Dive into the research topics of 'Fitting Residual Error Structures for Growth Models in SAS PROC MCMC'. Together they form a unique fingerprint.
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Mathematics
Growth Model
100%
Markov Chain Monte Carlo
91%
Software
80%
Covariance Structure
75%
Bayesian Methods
48%
Research Methods
32%
Components of Variance
27%
Guidance
25%
Bayesian Model
25%
Longitudinal Data
23%
Standard error
23%
Prior distribution
22%
Simplification
22%
Likely
22%
Small Sample
21%
Flexibility
21%
Biased
21%
Covariance matrix
20%
Simplify
20%
Tend
16%
Demonstrate
13%
Framework
12%
Estimate
10%
Model
7%
Medicine & Life Sciences
Software
67%
Bayes Theorem
54%
Growth
45%
Behavioral Sciences
31%
Research Personnel
31%
Social Sciences
software
48%
behavioral science
19%
flexibility
14%
literature
7%
Engineering & Materials Science
Covariance matrix
22%