Exact Bayesian curve fitting and signal segmentation.

We consider regression models where the underlying functional relationship between the response and the explanatory variable is modeled as independent linear regressions on disjoint segments. We present an algorithm for perfect simulation from the posterior distribution of such a model, even allowing for an unknown number of segments and an unknown model order for the linear regressions within each segment. The algorithm is simple, can scale well to large data sets, and avoids the problem of diagnosing convergence that is present with Monte Carlo Markov Chain (MCMC) approaches to this problem. We demonstrate our algorithm on standard denoising problems, on a piecewise constant AR model, and on a speech segmentation problem

Population issues and social indicators of well-being

Relating demographers' measures of various population characteristics (size, growth/decline, density, age/sex structures, migration, et cetera) to measures of well-being recently developed within the social indicators movement promises to provide new knowledge about the linkage of population and well-being that can enhance decision making about important population issues.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43515/1/11111_2005_Article_BF01363887.pd

The meaning of my feelings depends on who I am: work-related identifications shape emotion effects in organizations

Theory and research on affect in organizations has mostly approached emotions from a valence perspective, suggesting that positive emotions lead to positive outcomes and negative emotions to negative outcomes for organizations. We propose that cognition resulting from emotional experiences at work cannot be assumed based on emotion valence alone. Instead, building on appraisal theory and social identity theory, we propose that individual responses to discrete emotions in organizations are shaped by, and thus depend on, work-related identifications. We elaborate on this proposition specifically with respect to turnover intentions, theorizing how three discrete emotions - anger, guilt, and pride - differentially affect turnover intentions, depending on two work-related identifications - organizational and occupational identification. A longitudinal study involving 135 pilot instructors reporting emotions, work-related identifications, and turnover intentions over the course of one year provides general support for our proposition. Our theory and findings advance emotion and identity theories by explaining how the effects of emotions are dependent on the psychological context in which they are experienced

Assessment of Childhood Depression: Sampling Multiple Data Sources with One Instrument

The low correspondence among reporting sources in the measurement of childhood depression is well documented. However, no effort has been made to quantify the effects of using different measures with different sources. In this research the administration of the Peer Nomination Inventory of Depression (PNID) was modified to obtain three scores: (1) each child\u27s rating of depression as given by his/her peers; (2) each child\u27s self-rating of depression and (3) the number of times children assigned ratings of depression to others. The Children\u27s Depression Inventory (CDI) was administered for comparative purposes. Results suggest that differences in test items and formats can explain some, but not all, of the low correlations among reporting sources. Gender differences in the three modified PNID scores also were investigated

Validity Studies the Children\u27S Depression Inventory: A Comparison of Generalizability and Classical Test Theory Analyses

Issues surrounding accurate assessment of depression in children have received much attention. However, the stability of scores from depression measures has generally been estimated using only classical test score theory, rather than the more powerful generalizability theory. This study investigated the dependability of scores from the Children\u27s Depression Inventory using both generalizability and classical test score analyses. Results suggest that the sources of error variance interact to decrease the dependability of CDI scores. Several sample measurement protocols were also investigated. Results indicate that depression in children might be better assessed using planned, multiple testing sessions

Self-Report, Peer-Report, and Teacher-Report Measures of Childhood Depression: An Analysis by Item

We explored the low correlation among different types of childhood depression measures at the item level. The items from the Children\u27s Depression Inventory (CDI), Peer Nomination Inventory of Depression (PNID), and the Child Behavior Checklist-Teacher Report Form (CBCL-T) were combined, and both first- and second-order factor analyses were conducted. Results indicate that self-report, peer-report, and teacher-report assessments of depression measure generally uncorrelated constructs. Second-order analysis suggests that depression as a global construct is being measured to some degree by items from all three instruments. Canonical analysis was employed to identify items that best predicted CDI, PNID, and CBL-T summary scores simultaneously. Also, the relationship between specific items with similar content was investigated. Results from these analyses generally supported a conclusion that the three types of measures yield scores that are primarily independent and that the use of summary scores is not masking stronger relationships within measures. These findings have implications for clinical practice and construct elaboration