Covariate-Adjusted Constrained Bayes Predictions of Random Intercepts and Slopes. Sujit Ghosh is a

Constrained Bayes methodology represents an alternative to the posterior mean (empirical Bayes) method commonly used to produce random effect predictions under mixed linear models. The general constrained Bayes methodology of Ghosh (1992) is compared to a direct implementation of constraints, and it is suggested that the former approach could feasibly be incorporated into commercial mixed model software. Simulation studies and a real-data example illustrate the main points and support the conclusions

A note on proportional hazards and proportional odds models

The proportional hazards model has been used as a major model for analyzing survival data. When there are heavy ties, the proportional odds model is often recommended as an alternative. In this paper, we explore theoretical properties of these two models. We obtain a necessary condition for the discrete proportional odds model. We study the relationship between the proportional hazards and proportional odds models when the continuous times are discretized. Using this relationship, we derive a characterization result for the proportional hazards model, showing that the proportional hazards model is only related to the geometric distribution, a special case of the proportional odds model. We highlight this important difference between the two models that seems to be ignored in the analysis of real data. Using small numerical studies, we show that caution should be taken in using a proportional odds model in place of a proportional hazards model.Characterization Geometric distribution Interval censored data Survival analysis

A new representation of Cox's score statistic and its variance

We represent Cox's (1972) score statistic and its variance in a form analogous to Hoeffding's (1948) 'U-statistics', and suggest how these representations may be used to investigate asymptotic properties in nonstandard situations.Frailty martingale partial likelihood proportional hazards U-statistic

A longitudinal model for repeated interval-observed data with informative dropouts

We consider repeated measures interval-observed data with informative dropouts. We model the repeated outcomes via an unobserved random intercept and it is assumed that the probability of dropout during the study period is linearly related to the random intercept in a complementary log-log scale. Assuming the random effect follows the power variance function (PVF) family suggested by Hougaard (2000), we derive the marginal likelihood in a closed form. We evaluate the performance of the maximum likelihood estimation via simulation studies and apply the proposed method to a real data set.Interval-observed data Informative dropouts Power variance function

A Measure of Association for Bivariate Frailty Distributions

A general formula is derived for the variance of Kendall's coefficient of concordance for absolutely continuous bivariate distributions generated by frailties. The formula is specialized to the case of Gumbel's Type II distribution of extreme values, which arises when the frailty has a positive stable distribution. A new diagnostic is suggested for the goodness of fit of a bivariate frailty distribution, based on the value of Kendall's tau for a truncated sample. It is shown that as a function of the proportion of the sample truncated, this truncated tau characterizes the original frailty distribution. The methods are applied to some cable insulation failure data.extreme value distribution Kendall's tau stable distributions survival analysis (null)

A note on assessing agreement for frailty models

Assessing agreement is often of interest in biomedical sciences to evaluate the similarity of measurements produced by different raters or methods on the same subjects. We investigate the agreement structure for a class of frailty models that are commonly used for analyzing correlated survival outcomes. Conditional on the shared frailty, bivariate survival times are assumed to be independent with Weibull baseline hazard distribution. We present the analytic expressions for the concordance correlation coefficient (CCC) for several commonly used frailty distributions. Furthermore, we develop a time-dependent CCC for measuring agreement between survival times among subjects who survive beyond a specified time point. We characterize the temporal pattern in the time-dependent CCC for various frailty distributions. Our results provide a better understanding of the agreement structure implied by different frailty models.

Racial Disparities in Hospitalization Among Patients Who Receive a Diagnosis of Acute Coronary Syndrome in the Emergency Department

Background Timely hospitalization of patients who are diagnosed with an acute coronary syndrome (ACS) at the emergency department (ED) is a crucial step to lower the risk of ACS mortality. We examined whether there are racial and ethnic differences in the risk of being discharged home among patients who received a diagnostic code of ACS at the ED and whether having health insurance plays a role. Methods and Results We examined 51 022 910 discharge records of ED visits in Florida, New York, and Utah in the years 2008, 2011, 2014, and 2016/2017 using state‐specific data from the Healthcare Cost and Utilization Project. We identified ED admissions for acute myocardial infarction or unstable angina using the International Classification of Diseases, Ninth Revision (ICD‐9)/International Statistical Classification of Diseases, Tenth Revision (ICD‐10) diagnostic codes. We used generalized estimating equation models to compare the risk of being discharged home across racial and ethnic groups. We used Poisson marginal structural models to estimate the mediating role of health insurance status. The proportion discharged home with a diagnostic code of ACS was 12% among Black patients, 6% among White patients, 9% among Hispanic patients, and 9% among Asian/Pacific Islander patients. The incidence risk ratio for being discharged home was 1.26 (95% CI, 1.18–1.34) in Black patients, 1.23 (95% CI, 1.15–1.32) in Hispanic patients, and 1.11 (95% CI, 0.93–1.31) in Asian/Pacific Islander patients compared with White patients. Race and ethnicity were marginally associated with discharge home via pathways not mediated by health insurance. Conclusions Racial and ethnic disparities exist in the hospitalization of patients who received a diagnostic code of ACS in the ED. Possible causes need to be investigated