A Mixed Effects Model for Multivariate Ordinal Response Data Including Correlated Discrete Failure Times with Ordinal Responses

Biometrics ◽  
1996 ◽  
Vol 52 (2) ◽  
pp. 473 ◽  
Author(s):  
Thomas R. Ten Have
2005 ◽  
Vol 24 (21) ◽  
pp. 3331-3345 ◽  
Author(s):  
Rema Raman ◽  
Donald Hedeker

2020 ◽  
Vol 39 (15) ◽  
pp. 2051-2066 ◽  
Author(s):  
Rui Wang ◽  
Ante Bing ◽  
Cathy Wang ◽  
Yuchen Hu ◽  
Ronald J. Bosch ◽  
...  

2020 ◽  
Vol 6 (1) ◽  
pp. 132-153
Author(s):  
Brandon M. A. Rogers

AbstractThe current study examines /s/ variation in the southern-central city of Concepción, Chile and its relation to a variety of linguistic and social factors. A proportional-odds mixed effects model, with the random factor of “speaker”, was used to treat the categorically coded data on a continuum of acoustical variation ([s] > [h] > ∅). The results presented show that contrary to the previous assertions, heavy sibilant reduction, especially elision, in Concepción, Chile is the rule, rather than the exception, to the extent that it is no longer a marker of certain social demographics as has been reported previously. Furthermore, based on the trends reported, it is likely that this has been the case for several decades. Finally, the overall observed trends are indicative that the rates of /s/ elision will continue to increase across social demographics and different phonetic and phonological contexts in Concepción, Chile.


Author(s):  
Nicola Orsini

Recognizing a dose–response pattern based on heterogeneous tables of contrasts is hard. Specification of a statistical model that can consider the possible dose–response data-generating mechanism, including its variation across studies, is crucial for statistical inference. The aim of this article is to increase the understanding of mixed-effects dose–response models suitable for tables of correlated estimates. One can use the command drmeta with additive (mean difference) and multiplicative (odds ratios, hazard ratios) measures of association. The postestimation command drmeta_graph greatly facilitates the visualization of predicted average and study-specific dose–response relationships. I illustrate applications of the drmeta command with regression splines in experimental and observational data based on nonlinear and random-effects data-generation mechanisms that can be encountered in health-related sciences.


Author(s):  
Avinash Chandran ◽  
Derek W. Brown ◽  
Gabriel H. Zieff ◽  
Zachary Y. Kerr ◽  
Daniel Credeur ◽  
...  

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