The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

The exponentiated generalized gamma distribution with application to lifetime data

A four-parameter extension of the generalized gamma distribution capable of modelling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone and non-monotone failure rate functions, which are quite common in lifetime data analysis and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the exponentiated Weibull, exponentiated generalized half-normal, exponentiated gamma and generalized Rayleigh, among others. We derive two infinite sum representations for its moments. We calculate the density of the order statistics and two expansions for their moments. The method of maximum likelihood is used for estimating the model parameters and the observed information matrix is obtained. Finally, a real data set from the medical area is analysed.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Biochemistry of the Envenomation Response-a Generator Theme for Interdisciplinary Integration

The understanding of complex physiological processes requires information from many different areas of knowledge. To meet this interdisciplinary scenario, the ability of integrating and articulating information is demanded. The difficulty of such approach arises because, more often than not, information is fragmented through under graduation education in Health Sciences. Shifting from a fragmentary and deep view of many topics to joining them horizontally in a global view is not a trivial task for teachers to implement. To attain that objective we proposed a course herein described Biochemistry of the envenomation response aimed at integrating previous contents of Health Sciences courses, following international recommendations of interdisciplinary model. The contents were organized by modules with increasing topic complexity. The full understanding of the envenoming pathophysiology of each module would be attained by the integration of knowledge from different disciplines. Active-learning strategy was employed focusing concept map drawing. Evaluation was obtained by a 30-item Likert-type survey answered by ninety students; 84% of the students considered that the number of relations that they were able to establish as seen by concept maps increased throughout the course. Similarly, 98% considered that both the theme and the strategy adopted in the course contributed to develop an interdisciplinary view.

Assessing flow in physical activity: The Flow State Scale-2 and Dispositional Flow Scale-2

The Flow State Scale-2 (FSS-2) and Dispositional Flow Scale-2 (DFS-2) are presented as two self-report instruments designed to assess flow experiences in physical activity. Item modifications were made to the original versions of these scales in order to improve the measurement of some of the flow dimensions. Confirmatory factor analyses of an item identification and a cross-validation sample demonstrated a good fit of the new scales. There was support for both a 9-first-order factor model and a higher order model with a global flow factor. The item identification sample yielded mean item loadings on the first-order factor of .78 for the FSS-2 and .77 for the DFS-2. Reliability estimates ranged from .80 to .90 for the FSS-2, and .81 to .90 for the DFS-2. In the cross-validation sample, mean item loadings on the first-order factor were .80 for the FSS-2, and .73 for the DFS-2. Reliability estimates ranged between .80 to .92 for the FSS-2 and .78 to .86 for the DFS-2. The scales are presented as ways of assessing flow experienced within a particular event (FSS-2) or the frequency of flow experiences in chosen physical activity in general (DFS-2).

The Coefficient of Variance as an index of L2 lexical processing skill

The Coefficient of Variance (mean standard deviation/mean Response time) is a measure of response time variability that corrects for differences in mean Response time (RT) (Segalowitz & Segalowitz, 1993). A positive correlation between decreasing mean RTs and CVs (rCV-RT) has been proposed as an indicator of L2 automaticity and more generally as an index of processing efficiency. The current study evaluates this claim by examining lexical decision performance by individuals from three levels of English proficiency (Intermediate ESL, Advanced ESL and L1 controls) on stimuli from four levels of item familiarity, as defined by frequency of occurrence. A three-phase model of skill development defined by changing rCV-RT.values was tested. Results showed that RTs and CVs systematically decreased as a function of increasing proficiency and frequency levels, with the rCV-RT serving as a stable indicator of individual differences in lexical decision performance. The rCV-RT and automaticity/restructuring account is discussed in light of the findings. The CV is also evaluated as a more general quantitative index of processing efficiency in the L2.

Creating proactive interference in immediate recall: Building a DOG from a DART, a MOP, and a FIG

Phonemic codes are accorded a privileged role in most current models of immediate serial recall, although their effects are apparent in short-term proactive interference (PI) effects as well. The present research looks at how assumptions concerning distributed representation and distributed storage involving both semantic and phonemic codes might be operationalized to produce PI in a short-term cued recall task. The four experiments reported here attempted to generate the phonemic characteristics of a nonrhyming, interfering foil from unrelated filler items in the same list. PI was observed when a rhyme of the foil was studied or when the three phonemes of the foil were distributed across three studied filler items. The results suggest that items in short-term memory are stored in terms of feature bundles and that all items are simultaneously available at retrieval.

Attributions for the performance of self and other: It matters who the "other" is

This study tested hypotheses that locus of causality attributions for the academic performance of others are influenced by whether the other is a specific individual, or a typical other, and whether the other is similar or dissimilar to self. The research was carried out in two studies. Study 1 entailed development of two scales to measure perceptions of interpersonal similarity: 254 Australian undergraduates rated their similarity to either a specific other or to typical other students. In Study 2, 332 subjects completed one of the 16-item scales developed in Study 1, along with Rosenberg's self-esteem scale, and self-attribution and other-attribution versions of the Multidimensional Multi-attribution Causation Scale (MMCS). Results showed that attributions for the academic performance of others were strongly affected by whether the other was perceived to be similar or dissimilar to self, especially when the other was a specific individual. In particular, causal attributions for similar specific others were more favourable than attributions for self.

Adolescent reputation enhancement: Differentiating delinquent, nondelinquent, and at-risk youths

This research reports the findings of two studies conducted to measure and then investigate differences between delinquent, nondelinquent, and at-risk youths' orientations towards reputation enhancement. In the first study, concerning item selection and scale development, the factor structure and content validity of a potential Reputation Enhancement Scale were tested by examining the item responses of the scale completed by 230 high-school students. In the second study, the scale was validated by comparing the item responses of 80 delinquent, 90 at-risk, and 90 nondelinquent adolescents with the responses of the original students. The instrument was found to be reliable (alphas from .64 to .92), indicating that the factors are dependable across different samples, and the coefficients of congruence were sufficiently high to investigate meaningful group differences. Three second-order factors (Conforming Reputation, Nonconforming Reputation, Self-presentation) were derived from the 15 first-order factors. Although multivariate analyses revealed significant differences between the reputational orientations of delinquent, at-risk, and nondelinquent participants, the self-presentation second-order factor did not differentiate the three groups.

On modifications to the long-term survival mixture model in the presence of competing risks

A mixture model for long-term survivors has been adopted in various fields such as biostatistics and criminology where some individuals may never experience the type of failure under study. It is directly applicable in situations where the only information available from follow-up on individuals who will never experience this type of failure is in the form of censored observations. In this paper, we consider a modification to the model so that it still applies in the case where during the follow-up period it becomes known that an individual will never experience failure from the cause of interest. Unless a model allows for this additional information, a consistent survival analysis will not be obtained. A partial maximum likelihood (ML) approach is proposed that preserves the simplicity of the long-term survival mixture model and provides consistent estimators of the quantities of interest. Some simulation experiments are performed to assess the efficiency of the partial ML approach relative to the full ML approach for survival in the presence of competing risks.

Suicide attempts by psychiatric patients in acute inpatient, long-stay inpatient and community care

Background: This study examined rates of and risk factors associated with suicide attempts by psychiatric patients under active care. It was especially focussed on the relative rates across three standard treatment settings: acute inpatient care, long-stay inpatient care and community-based carl. Methods: A total of 12,229 patients in 13,632 episodes of care were rated on the Health of the Nation Outcome Scales (HoNOS) Item 2. For the purposes of the current investigation, a score of 4 was deemed to indicate a suicide attempt. Results: Incidence densities per 1000 episode days were 5.4 (95% CI = 4.8-6.1) for patients under care in acute inpatient settings, 0.6 (95% CI = 0.5-0.8) for patients under care in long-stay inpatient settings, and 0.5 (95% CI = 0.5-0.6) for patients under carl in community-based arrangements. Predictors varied by treatment setting. Risk was elevated for personality disorders across all settings: 22.7 attempts per 1000 episode days (95% CI = 17.2-30.0) in acute inpatient care; 2.1 (95% CI = 1.0-4.5) in long-stay inpatient care; and 2.3 (95% CI = 1.7-3.0) in community-based care. This effect remained after adjustment for demographics. Conclusion: Rates of suicide attempts among psychiatric patients are a major issue facing contemporary mental health care systems, and risk factors vary across different treatment settings.

Endorsement of CIDI psychosis screening items in the Australian Survey of Mental Health and Well being

This paper presents preliminary analysis of the endorsement of the CIDI Psychosis Screening items in a large Australian community sample. CIDI interviews were completed on a representative sample of 10,641 individuals living in private dwellings in Australia. The items examined constructs related to thought control/interference (G1), ideas of reference (G2), and special powers (G3). If endorsed, each item had a follow-up probe (G1A telepathy; G2A things arranged with special meaning; G3A -- group acceptability). The final item (G4) asked if the respondent had been told that they had schizophrenia. This paper presents the frequency of endorsement, and examines the impact of age and sex on these items. Endorsement of the items was G1 =5.86°/,,, G1A=0.70%, G2=4.84%, G2A=l.31%, G3=3.41%, G3A=2.65%, and G4=0.65%. If screen-positives are defined as two or more 'hits', then 0.41% of the sample met this criterion. Younger participants were significantly more likely to be screen-positive. Items G1, G1A, G2 and G2A were endorsed more frequently by younger participants while there were no significant age effects identified in items G3 or G4. There was a nonsignificant trend for females to endorse item G1 more frequently than males (p = 0.07), but there were no signficant gender differences on the other items. Many individuals who were 'screen-negative' for psychosis endorsed CIDI items related to thought controls, ideas of reference and special powers, suggesting that there may be a 'continuum' of experiences in the population. The impact of age on the distribution of these measures suggests either differential biological vulnerability to these experiences and/or differential cultural factors influencing endorsement of the items. The implications of these findings on our understanding of the symptoms of psychosis will be discussed. The survey was funded by the Commonwealth Dept. of Health and Family Services. The Stanley Foundation supported this project.