Regression Analysis of Recurrent Gap Times with Time-Dependent Covariates

Individual subjects may experience recurrent events of same type over a relatively long period of time in a longitudinal study. Researchers are often interested in the distributional pattern of gaps between the successive recurrent events and their association with certain concomitant covariates as well. In this article, their probability structure is investigated in presence of censoring. According to the identified structure, we introduce the proportional reverse-time hazards models that allow arbitrary baseline function for every individual in the study, when the time-dependent covariates effect is of main interest. Appropriate inference procedures are proposed and studied to estimate the parameters of interest in the models. The proposed methodology is demonstrated with the Monte-Carlo simulations and applied to a well-known Denmark schizophrenia cohort study data set

Semiparametric Regression Analysis on Longitudinal Pattern of Recurrent Gap Times

In longitudinal studies, individual subjects may experience recurrent events of the same type over a relatively long period of time. The longitudinal pattern of the gaps between the successive recurrent events is often of great research interest. In this article, the probability structure of the recurrent gap times is first explored in the presence of censoring. According to the discovered structure, we introduce the proportional reverse-time hazards models with unspecified baseline functions to accommodate heterogeneous individual underlying distributions, when the ongitudinal pattern parameter is of main interest. Inference procedures are proposed and studied by way of proper riskset construction. The proposed methodology is demonstrated by Monte-Carlo simulations and an application to the well-known Denmark schizophrenia cohort study data se

Detection of Progressive Deterioration in Early Onset Schizophrenia with a New Statistical Method

Much controversy exists over whether the course of schizophrenia, as defined by the lengths of repeated community tenures, is progressively ameliorating or deteriorating. This article employs a new statistical method proposed by Wang and Chen (2000) to analyze the Denmark registry data in Eaton, et al (1992). The new statistical method correctly handles the bias caused by induced informative censoring, which is an interaction of the heterogeneity of schizophrenia patients and long-term follow-up. The analysis shows a progressive deterioration pattern in terms of community tenures for the full registry cohort, rather than a progressive amelioration pattern as reported for a selected sub-cohort in Eaton, et al (1992). When adjusted for the long-term chronicity of calendar time, no significant progressive pattern was found for the full cohort

Additive Hazards Models with Latent Treatment Effectiveness Lag Time

In many clinical trials to evaluate treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical procedure or chemical compound would be in full effect. In this article, semiparametric regression models are proposed and studied to estimate the treatment effect accounting for such latent lag times. The new models take advantage of the invariance property of the additive hazards model in marginalizing over random effects, so parameters in the models are easy to be estimated and interpreted, while the flexibility without specifying baseline hazard function is kept. Monte Carlo simulation studies demonstrate the appropriateness of the proposed semiparametric estimation procedure. Data collected in the actual randomized clinical trial, which evaluates the effectiveness of biodegradable carmustine polymers for treatment of recurrent brain tumors, are analyzed

Cosmological Interpretation for the Stochastic Signal in Pulsar Timing Arrays

The pulsar timing array (PTA) collaborations have recently provided compelling evidence for the presence of a stochastic signal consistent with a gravitational-wave background. In this letter, we combine the latest data sets from NANOGrav, PPTA and EPTA collaborations to explore the cosmological interpretations for the detected signal from first-order phase transitions, domain walls and cosmic strings separately. We find that the first-order phase transitions and cosmic strings can give comparable interpretations compared to supermassive black hole binaries (SMBHBs) characterized by a power-law spectrum, but the domain wall model is strongly disfavored with the Bayes factor compared to the SMBHBs model being 0.009. Furthermore, the constraints on the parameter spaces indicate that: 1) a strong phase transition at temperatures below the electroweak scale is favored and the bubble collisions make the dominant contribution to the energy spectrum; 2) the cosmic string tension is $G \mu \in [1.46, 15.3]\times 10^{-12}$ at $90\%$ confidence interval and a small reconnection probability $p<6.68\times 10^{-2}$ is preferred at $95\%$ confidence level, implying that the strings in (super)string theory are strongly preferred than the classical field strings.Comment: 10 pages, 5 figures, 2 table

Searching for Isotropic Stochastic Gravitational-Wave Background in the International Pulsar Timing Array Second Data Release

We search for isotropic stochastic gravitational-wave background (SGWB) in the International Pulsar Timing Array second data release. By modeling the SGWB as a power-law, we find very strong Bayesian evidence for a common-spectrum process, and further this process has scalar transverse (ST) correlations allowed in general metric theory of gravity as the Bayes factor in favor of the ST-correlated process versus the spatially uncorrelated common-spectrum process is $30\pm 2$. The median and the $90\%$ equal-tail amplitudes of ST mode are $\mathcal{A}_{\mathrm{ST}}= 1.29^{+0.51}_{-0.44} \times 10^{-15}$, or equivalently the energy density parameter per logarithm frequency is $\Omega_{\mathrm{GW}}^{\mathrm{ST}} = 2.31^{+2.19}_{-1.30} \times 10^{-9}$, at frequency of 1/year. However, we do not find any statistically significant evidence for the tensor transverse (TT) mode and then place the $95\%$ upper limits as $\mathcal{A}_{\mathrm{TT}}< 3.95 \times 10^{-15}$, or equivalently $\Omega_{\mathrm{GW}}^{\mathrm{TT}}< 2.16 \times 10^{-9}$, at frequency of 1/year.Comment: 7 pages, 4 figures, 3 table

Implications for the Supermassive Black Hole Binaries from the NANOGrav 15-year Data Set

NANOGrav, EPTA, PPTA, and CPTA have announced the evidence for a stochastic signal from their latest data sets. Supermassive black hole binaries (SMBHBs) are supposed to be the most promising gravitational-wave (GW) sources of pulsar timing arrays. Assuming an astro-informed formation model, we use the NANOGrav 15-year data set to constrain the gravitational wave background (GWB) from SMBHBs. Our results prefer a large turn-over eccentricity of the SMBHB orbit when GWs begin to dominate the SMBHBs evolution. Furthermore, the GWB spectrum is extrapolated to the space-borne GW detector frequency band by including inspiral-merge-cutoff phases of SMBHBs and should be detected by LISA, Taiji and TianQin in the near future.Comment: 8 pages, 3 figures, 3 tables; version accepted for publication in SCPM

Serum alkaline phosphatase predicts survival outcomes in patients with skeletal metastatic nasopharyngeal carcinoma

OBJECTIVE: Bone metastasis is frequently associated with nasopharyngeal carcinoma. The diagnosis and follow-up of bone metastatic patients usually relies on skeletal X-ray and bone scintigraphy, which are time-consuming and costly. This study aimed to evaluate whether serum alkaline phosphatase offers clinical value in predicting the clinical response and survival outcome for skeletal metastatic nasopharyngeal carcinoma. METHODS: Serum alkaline phosphatase was measured at baseline and then before each cycle of treatment in 416 nasopharyngeal carcinoma patients with bone metastasis. The correlations between the pre-treatment and post-treatment alkaline phosphatase levels and the treatment efficacy were analyzed using the chi-square test. Survival was analyzed using the Kaplan–Meier method and then compared using the log-rank test. RESULTS: Patients with elevated pre-treatment alkaline phosphatase (>;110 IU/L) had significantly worse progression-free survival (

Distribution of Spectral Lags in Gamma Ray Bursts

Using the data acquired in the Time To Spill (TTS) mode for long gamma-ray bursts (GRBs) collected by the Burst and Transient Source Experiment on board the Compton Gamma Ray Observatory (BATSE/CGRO), we have carefully measured spectral lags in time between the low (25-55 keV) and high (110-320 keV) energy bands of individual pulses contained in 64 multi-peak GRBs. We find that the temporal lead by higher-energy gamma-ray photons (i.e., positive lags) is the norm in this selected sample set of long GRBs. While relatively few in number, some pulses of several long GRBs do show negative lags. This distribution of spectral lags in long GRBs is in contrast to that in short GRBs. This apparent difference poses challenges and constraints on the physical mechanism(s) of producing long and short GRBs. The relation between the pulse peak count rates and the spectral lags is also examined. Observationally, there seems to be no clear evidence for systematic spectral lag-luminosity connection for pulses within a given long GRB.Comment: 20 pages, 4 figure