Regression models for bivariate survival data

Multivariate lifetime data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated lifetime when an individual is followed for the occurrence of two or more types of events, or when distinct individuals have dependent event times. In most studies there are covariates such as treatments, group indicators, individual characteristics, or environmental conditions, whose relationship to lifetime is of interest. This leads to a consideration of regression models.The well known Cox proportional hazards model and its variations, using the marginal hazard functions employed for the analysis of multivariate survival data in literature are not sufficient to explain the complete dependence structure of pair of lifetimes on the covariate vector. Motivated by this, in Chapter 2, we introduced a bivariate proportional hazards model using vector hazard function of Johnson and Kotz (1975), in which the covariates under study have different effect on two components of the vector hazard function. The proposed model is useful in real life situations to study the dependence structure of pair of lifetimes on the covariate vector . The well known partial likelihood approach is used for the estimation of parameter vectors. We then introduced a bivariate proportional hazards model for gap times of recurrent events in Chapter 3. The model incorporates both marginal and joint dependence of the distribution of gap times on the covariate vector . In many fields of application, mean residual life function is considered superior concept than the hazard function. Motivated by this, in Chapter 4, we considered a new semi-parametric model, bivariate proportional mean residual life time model, to assess the relationship between mean residual life and covariates for gap time of recurrent events. The counting process approach is used for the inference procedures of the gap time of recurrent events. In many survival studies, the distribution of lifetime may depend on the distribution of censoring time. In Chapter 5, we introduced a proportional hazards model for duration times and developed inference procedures under dependent (informative) censoring. In Chapter 6, we introduced a bivariate proportional hazards model for competing risks data under right censoring. The asymptotic properties of the estimators of the parameters of different models developed in previous chapters, were studied. The proposed models were applied to various real life situations.

Nonparametric Estimation of Survivor Function in Bivariate Competing Risk Models’

So far, in the bivariate set up, the analysis of lifetime (failure time) data with multiple causes of failure is done by treating each cause of failure separately. with failures from other causes considered as independent censoring. This approach is unrealistic in many situations. For example, in the analysis of mortality data on married couples one would be interested to compare the hazards for the same cause of death as well as to check whether death due to one cause is more important for the partners’ risk of death from other causes. In reliability analysis. one often has systems with more than one component and many systems. subsystems and components have more than one cause of failure. Design of high-reliability systems generally requires that the individual system components have extremely high reliability even after long periods of time. Knowledge of the failure behaviour of a component can lead to savings in its cost of production and maintenance and. in some cases, to the preservation of human life. For the purpose of improving reliability. it is necessary to identify the cause of failure down to the component level. By treating each cause of failure separately with failures from other causes considered as independent censoring, the analysis of lifetime data would be incomplete. Motivated by this. we introduce a new approach for the analysis of bivariate competing risk data using the bivariate vector hazard rate of Johnson and Kotz (1975).

Commitment of women industrial workers with special reference to electronics industry in Kerala

In this study of workers of the two industrial units, it has been found that the women workers are more committed to the organization than the men workers. The organizational commitment has been a popular research topic among organizational sociologists, industrial psychologists and labour relations specialists. Much of the early research was directed on organizational commitment of men workers and studies on organizational commitment of women workers were less when compared to that of men workers. The results of this study is partially supported by the findings of Aranya and Jacobson (1975) who found that parental responsibility is linked with maintaining stable patterns of employment.

Serotonin Receptor Gene Expression And Insulin Function In Streptozotocin Induced Diabetic Rats

Recent studies have established a fimctional correlation of serotonergic and adrenergic function in the brain regions with insulin secretion in diabetic rats (Vahabzadeh et al., 1995). Administration of 5-HT”. agonist 8-OH-DPAT to conscious rats caused an increase in blood glucose level. This increase in blood glucose is due to inhibition of insulin secretion by increased circulating EPI (Chaouloff et al., 1990a; Chaouloff et al., 1990d; Chaoulo1T& Jeanrenaud, 1987). The increase in EPI is brought about by increased sympathetic stimulation. This increase can lead to increased sympatho-medullary stimulation thereby inhibiting insulin release (Bauhelal & Mir, 1993, Bauhelal & Mir, 1990a; Chaouloffet al., 1990d). Also, studies have shown that Gi protein in the liver has been decreased in diabetes which will increase gluconeogenesis and glycogenolysis thereby causing hyperglycaemia (Pennington, 1987). Serotonergic control is suggested to exert different effects on insulin secretion according to the activation of different receptor subclasses (Pontiroli et al., 1975). In addition to this mechanism, the secretion of insulin is dependent on the turnover ratio of endogenous 5-hydroxy tryptophan (5-HTP) to 5-HT in the pancreatic islets (Jance er al., 1980). The reports so far stated does not explain the complete mechanism and the subclass of 5-HT receptors whose expression regulate insulin secretion in a diabetic state. Also, there is no report of a direct regulation of insulin secretion by 5-HT from the pancreatic islets even though there are reports stating that the pancreatic islets is a rich source of 5-HT (Bird et al., 1980). Therefore, in the present study the mechanism by which 5-HT and its receptors regulate insulin secretion from pancreatic [3-cells was investigated. Our results led to the following hypotheses by which 5-HT and its receptors regulate the insulin secretion.