Effects of unilateral hippocampus-amygdala-partial temporal lobe resection on auditory EEG/MEG responses: a case study

Auditory orienting and discrimination were studied with combined multi-channel EEG and MEG recordings in a patient with unilateral amygdala-hippocampus-partial temporal lobe resection of the right hemisphere. The results revealed abnormalities of habituation in alerting- and orienting-related responses, and discrimination-related responses, elicited by auditory stimulation contralateral to the resected cerebral hemisphere. These results give support to the notions about the role of the amygdala and hippocampus in alerting and orienting, respectively, and of the temporal cortex in auditory discrimination.     

Improved Regression Calibration

The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration approach, a general pseudo maximum likelihood estimation method based on a conveniently decomposed form of the likelihood. It is both consistent and computationally efficient, and produces point estimates and estimated standard errors which are practically identical to those obtained by maximum likelihood. Simulations suggest that improved regression calibration, which is easy to implement in standard software, works well in a range of situations.     

MCDM methods in strategic planning of forestry on state‐owned lands in Finland: applications and experiences

The forests in Finland have been under intensive planning for decades. Currently, mathematical programming is widely used in planning of wood production. Today's multi‐functional forestry, however, calls for more flexible decision support methods. MCDM tools have been used in responding to fresh planning challenges. For example, the Finnish Forest and Park Service, entrusted with the care of the vast majority of state‐owned natural resources in Finland, endeavours to produce large‐scale natural resource plans satisfying the needs of both economic, social, and ecological sustainability. Participatory approach is applied in the process. Several forestry applications of MCDM methods, particularly those making use of the AHP or the HIPRE program, have been presented. Also, the outranking methods ELECTRE and PROMETHEE have been tested. Due to the nature of forestry applications, statistical techniques for analysing uncertainties in pairwise comparisons and for utilizing interval judgement data have been developed to improve the usability of the AHP. Recently, a hybrid method called A'WOT, making use of the AHP and SWOT, was also introduced into strategic forest planning. This paper summarizes the experiences gained in applying a MAVT and two outranking methods in connection with a participatory natural resource planning process in Finland. In addition, some results of the method development work related to application needs are briefly presented. The details of the planning cases reviewed here have previously been presented in forestry journals. The purpose of this paper is not only to show how MCDM methods have been applied in forestry, but also to discuss the usability and usefulness of MCDM methods from the viewpoint of supporting forestry decision making—and how they might further be improved. Also, some perspectives for the future development work of MCDM applications in the field of natural resource management are focused on. As a conclusion, the use of more than just one MCDM method in a single planning process is seen usually recommendable. In addition, developing hybrid MCDM methods is regarded as a potential direction for future research. Also, closer co‐operation between method developers and appliers is called for to produce more useful applications. Copyright © 2002 John Wiley & Sons, Ltd.     

Consumer segments in social commerce: A latent class approach

Social commerce is thriving; therefore, it becomes essential to recognize different types of social commerce shopper. In this study, we assume that social networking sites such as Facebook contain differently behaving consumer segments. Based on the assumption that the majority of social commerce shoppers are young adults, we are interested in identifying unobservable shopper segments that the young group may contain. A conceptual model has been tested that incorporates the psychological factor (trust), the unified theory of acceptance and the use of technology (UTAUT2), and behavioral aspects using mixture modeling techniques to reveal the unobservable consumer segments who have searched for clothing items through Facebook when shopping (n = 309). Three segments were found: social patrons (n = 219), wary explorers (n = 72), and sporadic explorers (n = 18). The study is a rare attempt to specifically categorize social commerce shopper segments by using mixture modeling techniques. The study offers further research avenues. Copyright © 2016 John Wiley & Sons, Ltd.     

Relating latent class membership to external variables: An overview

In this article we provide an overview of existing approaches for relating latent class membership to external variables of interest. We extend on the work of Nylund-Gibson et al. (Structural Equation Modeling: A Multidisciplinary Journal, 2019, 26, 967), who summarize models with distal outcomes by providing an overview of most recommended modeling options for models with covariates and larger models with multiple latent variables as well. We exemplify the modeling approaches using data from the General Social Survey for a model with a distal outcome where underlying model assumptions are violated, and a model with multiple latent variables. We discuss software availability and provide example syntax for the real data examples in Latent GOLD.     

Spiritual care in the last phase of life: a comparison between the Church of Sweden and the Church of Finland

This article deals with the Church of Sweden and the Church of Finland and their spiritual support for parishioners during their end-of-life phase. Support for the dying seemed uncommon in both countries, while most parishes offered support for the bereaved. The Finnish respondents expressed more confidence in their spiritual role than did the Swedes. This may have to do with the role of the churches in their respective countries and the varying geographies of death.     

Two-Step Estimation of Models Between Latent Classes and External Variables

We consider models which combine latent class measurement models for categorical latent variables with structural regression models for the relationships between the latent classes and observed explanatory and response variables. We propose a two-step method of estimating such models. In its first step, the measurement model is estimated alone, and in the second step the parameters of this measurement model are held fixed when the structural model is estimated. Simulation studies and applied examples suggest that the two-step method is an attractive alternative to existing one-step and three-step methods. We derive estimated standard errors for the two-step estimates of the structural model which account for the uncertainty from both steps of the estimation, and show how the method can be implemented in existing software for latent variable modelling.