Factors Determining Birth Intervals: A Multilevel Mixed Effect Parametric Survival Approach

Interval between births plays an important role in maternal health as well as child health. This study applies the methodology of Flexible parametric survival models to data on successive births among Nigeria women using the dataset from 2018 National Demographic Health survey. The flexible parametric survival model with Weibull baseline distribution was found to be the best among other fitted baseline distributions. The factors, zone of residence, educational qualification, religion, economic status and age at first birth were found to be significant in predicting the birth intervals. It was found that random effect parameter indicates that the interval between successive births is similar from the same woman. Keywords: Birth intervals, Baseline hazard, Mixed effect, Flexible parametric model, AIC.

Performance evaluation of survival regression models in analysing Swedish dental implant complication data with frailty

The use of inappropriate methods for estimating the effects of covariates in survival data with frailty leads to erroneous conclusions in medical research. This study evaluated the performance of 13 survival regression models in assessing the factors associated with the timing of complications in implant-supported dental restorations in a Swedish cohort. Data were obtained from randomly selected cohort (n = 596) of Swedish patients provided with dental restorations supported in 2003. Patients were evaluated over 9 years of implant loss, peri-implantitis or technical complications. Best Model was identified using goodness, AIC and BIC. The loglikelihood, the AIC and BIC were consistently lower in flexible parametric model with frailty (df = 2) than other models. Adjusted hazard of implant complications was 45% (adjusted Hazard Ratio (aHR) = 1.449; 95% Confidence Interval (CI): 1.153–1.821, p = 0.001) higher among patients with periodontitis. While controlling for other variables, the hazard of implant complications was about 5 times (aHR = 4.641; 95% CI: 2.911–7.401, p<0.001) and 2 times (aHR = 2.338; 95% CI: 1.553–3.519, p<0.001) higher among patients with full- and partial-jaw restorations than those with single crowns. Flexible parametric survival model with frailty are the most suitable for modelling implant complications among the studied patients.

Patient Age and Survival After Surgery for Esophageal Cancer

Background Esophagectomy for esophageal cancer is associated with a substantial risk of life-threatening complications and a limited long-term survival. This study aimed to clarify the controversial questions of how age influences short-term and long-term survival. Methods This population-based cohort study included almost all patients who underwent curatively intended esophagectomy for esophageal cancer in Sweden in 1987–2010, with follow-up through 2016. The exposure was age, analyzed both as a continuous and categorical variable. The probability of mortality was computed using a novel flexible parametric model approach. The reported probabilities are proper measures of the risk of dying, and the related odds ratios (OR) are therefore more suitable measures of association than hazard ratios. The outcomes were 90-day all-cause mortality, 5-year all-cause mortality, and 5-year disease-specific mortality. A novel flexible parametric model was used to derive the instantaneous probability of dying and the related OR along with 95% confidence intervals (CIs), adjusted for sex, education, comorbidity, tumor histology, pathological tumor stage, and resection margin status. Results Among 1737 included patients, the median age was 65.6 years. When analyzed as a continuous variable, older age was associated with slightly higher odds of 90-day all-cause mortality (OR 1.05, 95% CI 1.02–1.07), 5-year all-cause mortality (OR 1.02, 95% CI 1.01–1.03), and 5-year disease-specific mortality (OR 1.01, 95% CI 1.01–1.02). Compared with patients aged < 70 years, those aged 70–74 years had no increased risk of any mortality outcome, while patients aged ≥ 75 years had higher odds of 90-day mortality (OR 2.85, 95% CI 1.68–4.84), 5-year all-cause mortality (OR 1.56, 95% CI 1.27–1.92), and 5-year disease-specific mortality (OR 1.38, 95% CI 1.09–1.76). Conclusions Patient age 75 years or older at esophagectomy for esophageal cancer appears to be an independent risk factor for higher short-term mortality and lower long-term survival.

A bivariate power generalized Weibull distribution: A flexible parametric model for survival analysis

We are concerned with the flexible parametric analysis of bivariate survival data. Elsewhere, we argued in favour of an adapted form of the ‘power generalized Weibull’ distribution as an attractive vehicle for univariate parametric survival analysis. Here, we additionally observe a frailty relationship between a power generalized Weibull distribution with one value of the parameter which controls distributional choice within the family and a power generalized Weibull distribution with a smaller value of that parameter. We exploit this relationship to propose a bivariate shared frailty model with power generalized Weibull marginal distributions linked by the BB9 or ‘power variance function’ copula, then change it to have adapted power generalized Weibull marginals in the obvious way. The particular choice of copula is, therefore, natural in the current context, and the corresponding bivariate adapted power generalized Weibull model a novel combination of pre-existing components. We provide a number of theoretical properties of the models. We also show the potential of the bivariate adapted power generalized Weibull model for practical work via an illustrative example involving a well-known retinopathy dataset, for which the analysis proves to be straightforward to implement and informative in its outcomes.

Frequency Modulated Möbius Model Accurately Predicts Rhythmic Signals in Biological and Physical Sciences

Motivated by applications in physical and biological sciences, we developed a Frequency Modulated Möbius (FMM) model to describe rhythmic patterns in oscillatory systems. Unlike standard symmetric sinusoidal models, FMM is a flexible parametric model that allows deformations to sinusoidal shape to accommodate commonly seen asymmetries in applications. FMM model parameters are easy to estimate and the model is easy to interpret complex rhythmic data. We illustrate FMM model in three disparate applications, namely, circadian clock gene expression, corticoptropin levels in depressed patients and the temporal light intensity patterns of distant stars. In each case, FMM model is demonstrated to be flexible, scientifically plausible and easy to interpret. Analysis of synthetic data derived from patterns of real data, suggest that FMM model fits the data very well both visually as well as in terms of the goodness of fit measure total mean squared error. An R language based software for implementing FMM model is available.

A parametric model for estimating nuptiality patterns in modern populations

Nuptiality is a phenomenon closely related to fertility. The age-specific marriage distribution has a typical shape common in all human populations. In order to estimate this pattern, alternative parametric models have been proposed. However recent evidence suggests that mixture models are required to estimate nuptiality patterns. In this paper, a flexible parametric model is proposed in three versions, appropriate to describe the age pattern of first marriage rates. For evaluation purposes the models as well as the alternative existing models are fitted to a variety of empirical datasets.

STEREOLOGICAL ANALYSIS OF SHAPE

This paper concerns the problem of making stereological inference about the shape variability in a population of spatial particles. Under rotational invariance the shape variability can be estimated from central planar sections through the particles. A simple, but flexible, parametric model for rotation invariant spatial particles is suggested. It is shown how the parameters of the model can be estimated from observations on central sections. The corresponding model for planar particles is also discussed in some detail.