Forecast horizon aggregation in integer autoregressive moving average (INARMA) models

This paper addresses aggregation in integer autoregressive moving average (INARMA) models. Although aggregation in continuous-valued time series has been widely discussed, the same is not true for integer-valued time series. Forecast horizon aggregation is addressed in this paper. It is shown that the overlapping forecast horizon aggregation of an INARMA process results in an INARMA process. The conditional expected value of the aggregated process is also derived for use in forecasting. A simulation experiment is conducted to assess the accuracy of the forecasts produced by the aggregation method and to compare it to the accuracy of cumulative h-step ahead forecasts over the forecasting horizon. The results of an empirical analysis are also provided.     

A new useful four-parameter extension of the Gumbel distribution: Properties,regression model and applications using the GAMLSS framework

In this paper we introduce a flexible extension of the Gumbel distribution called the odd log-logistic exponentiated Gumbel distribution. The new model was implemented in GAMLSS package of R software and a brief tutorial on how to use this package is presented throughout the paper. We provide a comprehensive treatment of its general mathematical properties. Further, we propose a new extended regression model considering four regression structures. We discuss estimation methods based on censored and uncensored data. Two simulation studies are presented and four real data sets are applied to illustrating the usefulness of the new model.     

The Effectiveness of Fisher’s Rebuilding Group Intervention on Divorce Adjustment and General Health of Iranian Divorced Women

This research explores the effects of participating in the Rebuilding Seminar on postdivorce adjustment and the general health of divorced women in Arak, Iran. For this quasi-experimental study, 15 participants were recruited through convenience sampling. Prior to the participation in group intervention, participants were asked to complete a demographic questionnaire, the Fisher Divorce Adjustment Scale (FDAS), and the General Health Questionnaire (GHQ–28). Participants then completed the 10 weekly, 2-hour group intervention program. After the completion of the group intervention, postintervention questionnaires were administered. Results indicate that this particular educational program affected adjustment in participants on all subscales of the FDAS, except for social self-worth. The results also suggest that the intervention program was effective on all subscales of the GHQ–28, except for somatic symptoms. Due to numerous changes in the life of divorced women and the stressful nature of divorce, designing and implementing effective intervention plans seems necessary and constructive.     

Personal resilience and identity capital among young people leaving care: enhancing identity formation and life chances through involvement in volunteering and social action

This study explored identity capital and personal resilience among care leavers and young people in care engaging in social activities through volunteering. Care leavers and young people in care are disadvantaged developmentally by lack of identity resources and an accelerated transition to independence. This study analysed material from semi-structured interviews to explore the Identity Capital Model and theories of individualisation, agentic identity development and resilience in explaining the identity resources of young people transitioning out of care. The analysis identified links between the exploration opportunities of volunteering with the development of agentic individualisation and enhanced identity capital. The findings indicate that developmental processes may be enhanced through supported and personalised volunteering opportunities to aid vulnerable young people transitioning out of care. Young people leaving care can make substantial gains particularly in social capital, personal resilience and identity capital. This study indicates that volunteering opportunities for this group of vulnerable young people may assist in compensating for the lack of resources often experienced by care leavers when transitioning to adulthood.     

Comparative analysis of emergency department patients lost to follow-up after computerized alcohol screening and brief intervention

Many studies have evaluated the effectiveness of alcohol screening and brief intervention (SBI) but most of them have reported substantial loss to follow-up without investigating the characteristics of those lost to follow-up. We examined the association between Alcohol Use Disorders Identification Test (AUDIT) scores, readiness-to-change scores and the demographic factors with lost to follow-up. This retrospective study compared demographic characteristics, AUDIT and readiness-to-change scores for 190 lost to follow-up patients to 221 completed follow-up patients who participated in SBI in the Emergency Department between June 2006 and May 2007. Comparing the association between baseline characteristics and completed follow-up rate, those 30–39, 40–49 and 50 years and older had 0.46 (95% CI 0.32–0.91), 0.49 (95% CI 0.29–0.90) and 0.58 (95%CI 0.22–0.79) lower odds of completing follow-up, respectively, in comparison to those 18–29 years of age. The loss to follow-up group reported more negative consequences of alcohol and binge drinking than the completed follow-up group (p = 0.04). Using logistic regression, patients who experienced more negative effects of alcohol had 0.87 lower odds of completing follow-up (95% CI 0.79–0.96). The patients lost to follow-up in this study were significantly different in age and alcohol drinking habits compared to those completed follow-ups. It is important to consider differential loss to follow-up in assessing the validity and generalizability of intervention studies. This could help in tailoring methods of approaching patients based on target population characteristics.     

The Dyadic Effects of Controlling Emotional Abuse on Subjective Emotional Experience in Iranian Older Married Couples

This randomised control trial study examines the impact of an emotional‐focused intervention on emotional abuse and subjective emotional experience in Iranian older married couples. In the study, 57 older couples were randomly assigned into control and experimental groups with the latter taking part in an intervention program over 4 weeks, twice a week, with sessions lasting 90 minutes. In the experimental group, significant improvements were found for reducing emotional abuse behaviours and increasing subjective emotional experience. Dyadic analysis revealed that a partner's ability to control their own emotional abuse significantly effects both his/her subjective emotional experience and that of their spouse.     

Comparison of different estimation methods in growth curve models for categorical data: A simulation study

This simulation study aims at investigating the performance of maximum likelihood and weighted least-square estimation approaches in growth curve models with categorical data. The goodness-of-fit indices were compared with a number of scenarios (different trajectories, sample sizes, replications, and number of categories). The results show that when the number of categories and replications are small, using weighted least-square estimating methods leads to better goodness-of-fit indices. However, when the number of categories and replications are large, both maximum likelihood and weighted least squares in estimating methods will result in similar fit indices.     

Rates of convergence of autocorrelation estimates for periodically correlated autoregressive Hilbertian processes

Autoregressive Hilbertian (ARH) processes are of great importance in the analysis of functional time series data and estimation of the autocorrelation operators attracts the attention of various researchers. In this paper, we study estimators of the autocorrelation operators of periodically correlated autoregressive Hilbertian processes of order one (PCARH(1)), which is an extension of ARH(1) processes. The estimation method is based on the spectral decomposition of the covariance operator and considers two main cases: known and unknown eigenvectors. We show the consistency in the mean integrated quadratic sense of the estimators of the autocorrelation operators and present upper bounds for the corresponding rates.     

The effect of weight function on hypothesis testing in weighted sampling

In this paper the problem of statistical hypothesis testing under weighted sampling is considered for obtaining the most powerful test. Some simulated powers of tests, using the Monte Carlo method, are performed. Using a convenient sample of the specialist physicians of Social Security Organization of Ahvaz in Iran, two weighted samplings versus random sampling are tested. Among the three mentioned sampling, the size-biased sampling order 0.2 is more appropriate for the mechanism of data collection.