| SESUG |
2022 |
Embracing Cross-Loading to Improve Latent Variable Models Fit: A comparison of available options in SAS, Mplus, and R |
Kevin B. Gittner,
Katherine Mobley |
source |
26 |
| SGF |
2020 |
Analyzing Non-normal Data: Application to Missing Data Problems |
|
source |
10 |
| SESUG |
2019 |
Advanced Statistical Modeling within Machine Learning and Big Data Analytics |
George Mason |
source |
16 |
| SGF |
2018 |
Confirmatory Factor Analysis in SAS : Application to Public Administration |
|
source |
13 |
| WUSS |
2017 |
Modeling Longitudinal and Multilevel Data in SAS |
|
source |
8 |
| SGF |
2017 |
Analyzing Correlated Data in SAS |
|
source |
13 |
| SESUG |
2016 |
Analyzing non-normal data with categorical response variables |
Allameh Tabataba'i |
source |
9 |
| WUSS |
2016 |
How to analyze correlated and longitudinal data? |
|
source |
8 |
| SGF |
2016 |
Analyzing Non-Normal Binomial and Categorical Response Variables under Varying Data Conditions |
|
source |
16 |
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