Interrupted time-series analysis and its application to behavioral data

Journal ArticleThis paper uses a question-and-answer format to present the technical aspects of interrupted time-series analysis (ITSA). Topics include the potential relevance of ITSA to behavioral researchers, serial dependency, time-series models, tests of significance, and sources of ITSA information

How pairs of partners emerge in an initially fully connected society

A social group is represented by a graph, where each pair of nodes is connected by two oppositely directed links. At the beginning, a given amount $p(i)$ of resources is assigned randomly to each node $i$. Also, each link $r(i,j)$ is initially represented by a random positive value, which means the percentage of resources of node $i$ which is offered to node $j$. Initially then, the graph is fully connected, i.e. all non-diagonal matrix elements $r(i,j)$ are different from zero. During the simulation, the amounts of resources $p(i)$ change according to the balance equation. Also, nodes reorganise their activity with time, going to give more resources to those which give them more. This is the rule of varying the coefficients $r(i,j)$. The result is that after some transient time, only some pairs $(m,n)$ of nodes survive with non-zero $p(m)$ and $p(n)$, each pair with symmetric and positive $r(m,n)=r(n,m)$. Other coefficients $r(m,i\ne n)$ vanish. Unpaired nodes remain with no resources, i.e. their $p(i)=0$, and they cease to be active, as they have nothing to offer. The percentage of survivors (i.e. those with with $p(i)$ positive) increases with the velocity of varying the numbers $r(i,j)$, and it slightly decreases with the size of the group. The picture and the results can be interpreted as a description of a social algorithm leading to marriages.Comment: 7 pages, 3 figure

Feedback: The Foundation of Kind Leadership

Brene Brown states that “Clear is kind. Unclear is unkind.” To give clear and direct feedback requires brave academic leaders who understand that feedback is critical to leadership success. This presentation will use a feedback model – Johari’s Window (Luft & Ingham, 1955), as a backdrop for understanding how to give productive feedback in higher education

More than One Way to be Happy: A Typology of Marital Happiness

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100129/1/famp12028.pd

Finding fault: Criticism as a care management strategy and its impact on outcomes for dementia caregivers

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148350/1/gps5052_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148350/2/gps5052.pd

Предрогнозна оцінка структури майна і капіталу промислового підприємства

Однією зі складових управління фінансами підприємства є прогнозування фінансового стану, яке дозволяє виявити здатність підприємства до стійкого функціонування і розвитку в умовах зміни зовнішнього і внутрішнього середовища господарювання. Сьогодні неможна недооцінювати роль прогнозування, оскільки функціонування підприємства завжди пов'язане з невизначеністю майбутніх наслідків дій того або іншого управлінського рішення. Однією із дисциплінуючих умов прогнозування фінансового стану промислових підприємств виступає оцінка їх фінансового стану у динаміці взагалі та предпрогнозна оцінка структури майна і капіталу зокрема.Одной из составляющих управления финансами предприятия является прогнозирование финансового состояния, которое позволяет выявить способность предприятия к стойкому функционированию и развитию в условиях изменения внешней и внутренней среды ведения хозяйства. Сегодня невозможно недооценивать роль прогнозирования, поскольку функционирование предприятия всегда связано с неопределенностью будущих последствий действий того или другого управленческого решения. Одним из дисциплинирующих условий прогнозирования финансового состояния промышленных предприятий выступает оценка их финансового состояния в динамике вообще и предпрогнозируемая оценка структуры имущества и капитала в частности

Understanding weekly cycles in suicide: an analysis of Austrian and Swiss data over 40 years

BACKGROUND: Seasonal as well as weekly cycles in suicide have been described, replicated and poorly understood for a long time. In Western countries, suicides are typically least frequent on weekends and most frequent on Mondays and Tuesdays. To improve understanding of this phenomenon a strategy is required which focuses on anomalous findings beyond the regular patterns. Here, we focused on instances where the weekly suicide patterns disappear or are interrupted. METHODS: We used data from Swiss and Austrian mortality statistics for the periods 1969-2010 and 1970-2010, respectively. First, the data were cross-tabulated by days of the week and the available socio-demographic information (sex, age, religious affiliation and region). Second, time series of cumulated daily frequencies of suicide were analysed by seasonal Autoregressive Integrated Moving Average (ARIMA) models which included intervention effects accounting for Easter and Pentecost (Whit) holidays. RESULTS: First, the cross tabulations showed that weekly cycles may be smoothed above all in young persons and smoothed in drowning, jumping and car gas exhaustion suicides. Second, the ARIMA analyses displayed occasional preventive effects for holidays Saturdays and Sundays, and more systematic effects for holiday Mondays. There were no after effects on Tuesdays following holiday Mondays. CONCLUSIONS: In general, the weekend dip and the Monday backlog effect in suicide show striking similarities to the Advent season effect and are interpretable within the same template. The turning points between low and high frequencies possibly provide promising frames for the timing of prevention activities

Understanding the Role of Relationship Maintenance in Enduring Couple Partnerships in Later Adulthood

Intimate relationships in later adulthood are understudied despite their positive association with health and well-being. This cross-sectional mixed methods study sought to redress this gap by investigating relationship maintenance in later adulthood. Our international sub-sample comprised 1,565 participants aged 55 + and in an ongoing relationship. Results from hierarchical multiple regression indicated that overall happiness with the relationship had the largest effect size on relationship maintenance, with 53% of the variance explained. Content analyses of open-ended questions identified companionship and laughter as some of the “best liked” aspects of the relationship. Housework/cooking and saying “I love you” were among the behaviors that made participants feel appreciated. Results illustrated the types of maintenance behaviors adults in later adulthood who are in enduring partnerships employ