A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.     

The Geometric Birnbaum-Saunders regression model with cure rate

In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area.     

A Bayesian analysis of the Conway–Maxwell–Poisson cure rate model

The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway–Maxwell–Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.     

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.     

Small-Sample Comparisons for Goodness-of-Fit Statistics in One-Way Multinomials with Composite Hypotheses

The small-sample behaviour of power-divergence goodness-of-fit statistics with composite hypotheses was evaluated with multinomial models of up to five cells and up to three parameters. Their performance was assessed by comparing asymptotic test sizes with exact test sizes obtained by enumeration in the near right tail, where 1-?∈?(0.90,?0.95], and in the far right tail, where 1-?∈?(0.95,?0.99]. The study addressed all combinations of power-diparse JAS312HH01.sgmvergence estimates of indices ν?∈?{-1/2,?0,?1/3,?1/2,?2/3,?1,?3/ 2} and power-divergence statistics of indices λ?∈?{-1/2,?0,?1/3,?1/2,?2/3,?1,?3/2}. The results indicate that the asymptotic approximation is sufficiently accurate (by the criterion that the average exact size is no larger than ±10% of the nominal asymptotic test size) in the near right tail when ν=0 and λ=1/2, and in the far right tail when ν=0 and λ=1/3, in both cases providing that the smallest expectation in the composite hypothesis exceeds 5. The only exception to this rule is the case of models that render a near-equiprobable composite hypothesis on the boundaries of the parameter space, where average exact sizes are usually quite different from nominal sizes despite the fact that the smallest expectation in these conditions is usually well above 5.     

The Catholic response to the population problem

A survey of efforts led or sponsored by the Catholic church in response to the population problem in the Philippines. These efforts stem from the Church's belief that population growth is related to the overall picture of development, and that priority must go to social and economic justice. The Catholic Church of the Philippines (to which 85% of the population belong) views it as a problem basically involving care of people, and directs its efforts primarily at internal human sexual control rather than external contraceptive control. Family Life Education began as a program in the church in the 1960s. Efforts by priests, nuns, and lay leaders in Mindanao eventually resulted in counseling in husband-wife relations, marriage commitment, human sexuality, parent-child relations, and responsible parenthood, and to the creation of college courses to prepare teachers in tackling sex education. A program offering natural family planning was also started, initially for employees of a packing firm and later expanding throughout the province. In 1975, the program was launched in Manila, and a year later had 3 family life centers. The ovulation (or Billings) method is offered -- an advantage to low income people because it does not require purchase of a thermometer. Success of this method requires a sense of responsibility on the part of both husband and wife. Widespread international interest in the ovulation method has led to formation of an International Federation for Family Life Promotion, to which the Philippine Federation for Natural Family Planning has applied for membership. The IFFLP is working with the WHO Human Reproduction Unit on 2 projects, part of one of them (a field trial for evaluation) being conducted in Iligan City, Iloilo City, and Manila. Among the concerns of the IFFLP-WHO collaboration is developing a standardized Natural Family Planning curriculum or educational package.     

Single‐ and Multiple‐Informant Research Designs to Examine the Human Resource Management−Performance Relationship

During the last decades, many empirical studies have analysed the relationship between human resource management and firm performance. Despite the call for multiple‐rater designs, a relatively large number of researchers still rely on survey responses provided by a single informant in each organization. Single‐informant designs suffer from a number of problems, especially when the responses provided by different types of raters across firms are pooled into a single dataset prior to assessing their equivalence across raters. Using an illustration of the relationship between high performance work systems and firm performance, in this paper we observe that responses provided by managers holding different positions (human resource managers and sales managers) differ significantly and therefore pooling their responses into a single dataset may result in confusing conclusions. Furthermore, we demonstrate that differences arise in the estimated parameters when a multiple‐key‐informant approach, compared to a single‐informant design, is adopted. For these reasons, data collection using multiple key informants is recommended, based on the assumption that some raters in the firm will be more knowledgeable about the variables of interest than others.     

Quality of Work and Aggregate Productivity

We inspect the relationship between quality of work and productivity. Using Spanish aggregate data for the period 2001–2006, we find that quality of work is an additional factor to explain productivity levels in sectors and regions. Consequently, quality of work is not only an objective per se, but it also may be a production factor able to increase the wealth of regions. In our work we use two alternatives definitions of quality of work, coming respectively from survey data and from a social indicators approach. Besides, we employ two different measurements of labour productivity, in order to test the robustness of our result. We estimate our model using a simultaneous equation model for our panel of data, and we find important differences in high and low human capital sectors. The former display a positive relationship between quality of work and productivity, while the latter show a negative relationship.     

A comparison of three physical activity programs for health and fitness tested with older women: Benefits of aerobic activity,aqua fitness,and strength training

ABSTRACT

Inactivity has been associated with decreased quality of life of older people, and many physical activity programs are encouraged. However, the heterogeneity of the different exercise programs available is well recognized. The objective was to compare three physical activity programs (strength training, aqua fitness, and aerobic exercise) to discern the differences in the benefits achieved by each of them in older women over a period of 6 months. For that, a double-blind randomized trial sorted 347 women over 50 years old into three groups of exercise programs; they completed three sessions of evaluation that included the measurement of weight and body mass index and used the Senior Fitness Test (SFT) and SF-12 questionnaire. A t-test for related samples compared the evolution of each group, and ANOVA statistic was used to compare the effect of the different exercise programs. The results showed that women should consider performing aerobic activity up to age 60. After that age, aerobic activity or strength training can provide greater benefits.     

Small-sample comparisons for powerdivergence goodness-of-fit statistics for symmetric and skewed simple null hypotheses

Power-divergence goodness-of-fit statistics have asymptotically a chi-squared distribution. Asymptotic results may not apply in small-sample situations, and the exact significance of a goodness-of-fit statistic may potentially be over- or under-stated by the asymptotic distribution. Several correction terms have been proposed to improve the accuracy of the asymptotic distribution, but their performance has only been studied for the equiprobable case. We extend that research to skewed hypotheses. Results are presented for one-way multinomials involving k = 2 to 6 cells with sample sizes N = 20, 40, 60, 80 and 100 and nominal test sizes f = 0.1, 0.05, 0.01 and 0.001. Six power-divergence goodness-of-fit statistics were investigated, and five correction terms were included in the study. Our results show that skewness itself does not affect the accuracy of the asymptotic approximation, which depends only on the magnitude of the smallest expected frequency (whether this comes from a small sample with the equiprobable hypothesis or a large sample with a skewed hypothesis). Throughout the conditions of the study, the accuracy of the asymptotic distribution seems to be optimal for Pearson's X² statistic (the power-divergence statistic of index u = 1) when k > 3 and the smallest expected frequency is as low as between 0.1 and 1.5 (depending on the particular k, N and nominal test size), but a computationally inexpensive improvement can be obtained in these cases by using a moment-corrected h² distribution. If the smallest expected frequency is even smaller, a normal correction yields accurate tests through the log-likelihood-ratio statistic G² (the power-divergence statistic of index u = 0).