Random weighting approximation for Tobit regression models with longitudinal data

2014 ◽  
Vol 79 ◽  
pp. 235-247 ◽  
Author(s):  
L.Q. Xiao ◽  
B. Hou ◽  
Z.F. Wang ◽  
Y.H. Wu
Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Samar R El Khoudary ◽  
Kelly Shields ◽  
Matthew Budoff ◽  
Emma Barinas-Mitchell ◽  
Imke Janssen ◽  
...  

Introduction: Increasing evidence demonstrates a role of cardiovascular fat in the pathogenesis of CAD. It is unknown whether heart and vascular fat depots are related to atherosclerotic burden in women transitioning through menopause, a time of increasing CAD risk. Hypothesis: We hypothesize that volumes of epicardial (EAT), pericardial (PAT), total heart (TAT=EAT+PAT) and peri-aortic (PVAT) adipose tissues are associated with presence and severity of coronary artery calcification (CAC) in a sample of white and black midlife women. Methods: CAC and cardiovascular fat depots were quantified by electron beam CT. Outcomes were presence of CAC (none vs. any: Agatston score >0), and severity of CAC (CAC Agatston score). Logistic and tobit regression were used. Final models were adjusted for age, race, study site, menopausal status, obesity (BMI ≥30 Kg/m 2 ), systolic blood pressure, lipids, homeostasis model assessment insulin resistance index, current smoking, physical activity, comorbidity (history of hypertension, stroke, angina, heart attack or diabetes) and medication use (cholesterol lowering, antihypertensive or antidiabetic medications). Results: The study included 509 women (37.9% black; 58.4% pre-/early perimenopausal, 41.6% late peri-/postmenopausal) aged 46-59 years with data on any of the 4 fat depots. CAC was found in 47.4% of the participants. Odds ratios (95% CI) from final logistic regression models showed that higher volumes of EAT (2.43 (1.22, 4.86), PAT (1.57 (1.04, 2.37), and TAT (2.43 (1.22, 4.87), were significantly associated with higher odds of presence of CAC. Similarly, tobit regression models showed that higher volumes per 1 log-unit increase of EAT (β (SE): 28.0 (10.7)), PAT (16.5 (6.6)), and TAT (30.0 (10.7)), were significantly associated with greater severity of CAC in final adjusted models. PVAT was not associated with either CAC presence or severity in final models. Conclusions: Heart fat (EAT, PAT and TAT), but not peri-aortic fat were independently associated with greater presence and severity of CAC in women at midlife, suggesting that local cardiovascular fat depots may contribute to CAD in midlife women. Future work is warranted to understand the underlying mechanistic pathways.


2021 ◽  
Vol 35 (4) ◽  
Author(s):  
Vinícius S. O. Ribeiro ◽  
Juvêncio S. Nobre ◽  
José Roberto S. dos Santos ◽  
Caio L. N. Azevedo

2019 ◽  
Vol 29 (8) ◽  
pp. 2179-2197
Author(s):  
Hua He ◽  
Wan Tang ◽  
Tanika Kelly ◽  
Shengxu Li ◽  
Jiang He

Measures of substance concentration in urine, serum or other biological matrices often have an assay limit of detection. When concentration levels fall below the limit, the exact measures cannot be obtained. Instead, the measures are censored as only partial information that the levels are under the limit is known. Assuming the concentration levels are from a single population with a normal distribution or follow a normal distribution after some transformation, Tobit regression models, or censored normal regression models, are the standard approach for analyzing such data. However, in practice, it is often the case that the data can exhibit more censored observations than what would be expected under the Tobit regression models. One common cause is the heterogeneity of the study population, caused by the existence of a latent group of subjects who lack the substance measured. For such subjects, the measurements will always be under the limit. If a censored normal regression model is appropriate for modeling the subjects with the substance, the whole population follows a mixture of a censored normal regression model and a degenerate distribution of the latent class. While there are some studies on such mixture models, a fundamental question about testing whether such mixture modeling is necessary, i.e. whether such a latent class exists, has not been studied yet. In this paper, three tests including Wald test, likelihood ratio test and score test are developed for testing the existence of such latent class. Simulation studies are conducted to evaluate the performance of the tests, and two real data examples are employed to illustrate the tests.


2007 ◽  
Vol 26 (20) ◽  
pp. 3782-3800 ◽  
Author(s):  
Ying Yang ◽  
Jian Kang ◽  
Kai Mao ◽  
Jie Zhang

2001 ◽  
Vol 20 (21) ◽  
pp. 3295-3311 ◽  
Author(s):  
Christopher H. Schmid

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