Generalized Additive Modeling in SAS

Author(s):  
George J. Knafl ◽  
Kai Ding
Author(s):  
Koji Miwa ◽  
Harald Baayen

Abstract This paper introduces the generalized additive mixed model (GAMM) and the quantile generalized additive mixed model (QGAMM) through reanalyses of bilinguals’ lexical decision data from Dijkstra et al. (2010) and Miwa et al. (2014). We illustrate how regression splines can be used to test for nonlinear effects of cross-language similarity in form as well as for controlling experimental trial effects. We further illustrate the tensor product smooth for a nonlinear interaction between cross-language semantic similarity and word frequency. Finally, we show how the QGAMM helps clarify whether the effect of a particular predictor is constant across distributions of RTs.


2021 ◽  
Vol 16 (9) ◽  
pp. 3-13
Author(s):  
Rebekah Leigh ◽  
John B. Tan ◽  
Shirin DeGiorgio ◽  
Minha Cha ◽  
Chelsea Kent ◽  
...  

Objective: Bronchopulmonary dysplasia (BPD) continues to prevail among very preterm infants. While NICHD BPD Outcome Estimator is easy to use, the clinical interpretation remains challenging. This study aims to optimize its use. Study Design: A retrospective study was conducted with 469 infants born between 2015 and 2020. Data were entered into the Estimator to obtain probability scores. Trajectories of the probability scores were modeled using generalized additive modeling. The optimal cutoff number for predicting severe BPD or death was identified by a grid search from a range established by the original population distribution and the ROC curve. Result: Combining probability scores from the severe and death categories and the no-BPD and mild categories may improve BPD outcome prediction. A cutoff of 21% combining outcome probabilities from severe and death categories is predictive of severe BPD or death. Conclusion: Combining probability scores of different categories improves BPD outcome prediction.


2021 ◽  
Vol 8 ◽  
Author(s):  
Jens J. Currie ◽  
Jessica A. McCordic ◽  
Grace L. Olson ◽  
Abigail F. Machernis ◽  
Stephanie H. Stack

The concurrent increase in marine tourism and vessel traffic around the world highlights the need for developing responsible whale watching guidelines. To determine the impact of vessel presence on humpback whale behaviors in Maui Nui, a land-based study was conducted from 2015 to 2018 in Maui, Hawai'i. Theodolite tracks were used to summarize humpback whale swim speed, respiration rate, dive time, and path directness to determine the potential impacts of various types of vessel presence on whale behavior. Vessel presence, proximity, and approach type in conjunction with biological parameters were used in a generalized additive modeling framework to explain changes in whale behaviors. The results presented here show increases in swim speed, respiration rate, and path directness in conjunction with decreasing dive times, which has been shown to be an energetically demanding avoidance strategy. These observations, in conjunction with increasing awareness on the implication of non-lethal effects of human disturbance and changing oceanic environments on humpback whales, highlights the need for a pre-cautionary approach to management. Stricter guidelines on whale watching will limit the level of disturbance to individual humpback whales in Hawai'i and ensure they maintain the fitness required to compensate for varying ecological and anthropogenic conditions.


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