Prediction of disease status: A regressive model approach for repeated measures

In this paper, regressive models are proposed for modeling a sequence of transitions in longitudinal data. These models are employed to predict the future status of the outcome variable of the individuals on the basis of their underlying background characteristics or risk factors. The estimation of parameters and also estimates of conditional and unconditional probabilities are shown for repeated measures. The goodness of fit tests are extended in this paper on the basis of the deviance and the Hosmer–Lemeshow procedures and generalized to repeated measures. In addition, to measure the suitability of the proposed models for predicting the disease status, we have extended the ROC curve approach to repeated measures. The procedure is shown for the conditional models for any order as well as for the unconditional model, to predict the outcome at the end of the study. The test procedures are also suggested. For testing the differences between areas under the ROC curves in subsequent follow-ups, two different test procedures are employed, one of which is based on permutation test. In this paper, an unconditional model is proposed on the basis of conditional models for the disease progression of depression among the elderly population in the USA on the basis of the Health and Retirement Survey data collected longitudinally. The illustration shows that the disease progression observed conditionally can be employed to predict the outcome and the role of selected variables and the previous outcomes can be utilized for predictive purposes. The results show that the percentage of correct predictions of a disease is quite high and the measures of sensitivity and specificity are also reasonably impressive. The extended measures of area under the ROC curve show that the models provide a reasonably good fit in terms of predicting the disease status during a long period of time. This procedure will have extensive applications in the field of longitudinal data analysis where the objective is to obtain estimates of unconditional probabilities on the basis of series of conditional transitional models.     

A note on the queue with a random set-up time under a restricted admissibility policy with a Bernoulli vacation schedule

This paper deals with the queue size distribution of an M^x/G/1 queue with a random set-up time and with a Bernoulli vacation schedule under a restricted admissibility policy. This generalizes the model studied by Madan and Choudhury [Sankhyá 66 (2004) 175–193].     

A two phases queueing system with Bernoulli vacation schedule under multiple vacation policy

This paper deals with a single server Poisson arrival queue with two phases of heterogeneous service along with a Bernoulli schedule vacation model, where after two successive phases service the server either goes for a vacation with probability p (0≤p≤1) or may continue to serve the next unit, if any, with probability q(=1−p). Further the concept of multiple vacation policy is also introduced here. We obtained the queue size distributions at a departure epoch and at a random epoch, Laplace Stieltjes Transform of the waiting time distribution and busy period distribution along with some mean performance measures. Finally we discuss some statistical inference related issues.     

The Impact of Family Planning on Fertility in a Rural Area of East Pakistan

This pape revaluates a family planning pilot project conducted by the Pakistan Academy for Rural Development in Comilla, East Pakistan. The evaluation is based upon an analysis of the extent to which adoption of conventional contraceptives (condoms and foam tablets) has reduced fertility in selected villages of the Comilla-Kotwali precinct, during the years 1962-66.The study was carried out by comparing adopter and non-adopter rates of pregnancy and analyzing the trends in pregnancy reduction that resulted from adoption. The findings indicate that (1) although the pregnancy rate of adopters has increased steadily throughout the time period, in 1966 the rate is still less than half of what was expected had adoption not occurred; (2) contraceptive use-effectiveness decreases with length of time of use; and (3) pregnancy reduction has been declining since 1964.     

Female status and fertility behaviour in a Metropolitan Urban area of Bangladesh

The paper examines hypotheses that certain aspects of status of married women such as (i) decision-making power; (ii) employment status and (iii) educational status, are positively associated with use of contraception and inversely related to fertility performance. The study is based on 1,130 women of reproductive age (15-49) who are currently married and living with their husbands and reported to be fecund. The data are drawn from a cross-section of working and non-working women of Dacca City. The hypothesis that each of the above status variables is related to fertility behaviour (measured as current use of contraception and number of children ever-born) is confirmed, with the sole exception of the relationship between female employment status and fertility behaviour. Female participation in the labour force has little or no effect on use of contraception, particularly among those who belong to higher education and income groups. However, in the lower education and income groups, fertility and use of contraception vary with work experience. The findings clearly point out the need to improve the status of women in order to achieve a breakthrough in the use of contraception and a reduction in fertility.     

Perceptions of Civil Servants Toward Privatization and Development: A New Exploratory Study

This study examines the perceptions of civil servants towards privatization with respect to national development. Using case studies and official interview data, it also examines the efficacy and effectiveness of privatization programs in a developing country, Bangladesh. The study rejects the conventional beliefs about the role of bureaucracies as anti-privatization by revealing that civil servants of Bangladesh have positive perceptions towards privatization with respect to national development. The study, however, finds no significant differences in the perceptions of different levels of civil servants towards privatization with respect to national development; they all share a common goal. Research demonstrates that civil servants generally believe that privatization positively affects economic, social, political and administrative development, although it negatively affects equity, fairness and social justice issues by widening the gap between the rich and the poor. Additionally, the study demonstrates that privatization is not conducive to employee empowerment.

A generalized bivariate Bernoulli model with covariate dependence

Dependence in outcome variables may pose formidable difficulty in analyzing data in longitudinal studies. In the past, most of the studies made attempts to address this problem using the marginal models. However, using the marginal models alone, it is difficult to specify the measures of dependence in outcomes due to association between outcomes as well as between outcomes and explanatory variables. In this paper, a generalized approach is demonstrated using both the conditional and marginal models. This model uses link functions to test for dependence in outcome variables. The estimation and test procedures are illustrated with an application to the mobility index data from the Health and Retirement Survey and also simulations are performed for correlated binary data generated from the bivariate Bernoulli distributions. The results indicate the usefulness of the proposed method.     

A Fairly Accurate Approximation to the Area Under Normal Curve

In this article, we present a new approximation to the cumulative distribution function of standard normal distribution. The approximation is fairly accurate with minimum accuracy of seven decimal digits. To the best of our knowledge, this formula outperforms other such approximations available in literature.     

Analyzing dependence in incidence of diabetes and heart problem using generalized bivariate geometric models with covariates

For analyzing incidence data on diabetes and health problems, the bivariate geometric probability distribution is a natural choice but remained unexplored largely due to lack of models linking covariates with the probabilities of bivariate incidence of correlated outcomes. In this paper, bivariate geometric models are proposed for two correlated incidence outcomes. The extended generalized linear models are developed to take into account covariate dependence of the bivariate probabilities of correlated incidence outcomes for diabetes and heart diseases for the elderly population. The estimation and test procedures are illustrated using the Health and Retirement Study data. Two models are shown in this paper, one based on conditional-marginal approach and the other one based on the joint probability distribution with an association parameter. The joint model with association parameter appears to be a very good choice for analyzing the covariate dependence of the joint incidence of diabetes and heart diseases. Bootstrapping is performed to measure the accuracy of estimates and the results indicate very small bias.