Robustheit metrischer und nichtmetrischer Conjoint-Analyse auf der Grundlage simulierter Präferenzdaten

Der Begriff Conjoint-Analyse (CA) bezeichnet statistische Verfahren zur Dekomposition ordinaler Relationen zwischen multiattributiven Stimuli unter Zugrundlegung des Modells (additiv) verbundener Messung. Neben spezifischen Algorithmen, die die ordinale Qualität der Daten berücksichtigen (nichtmetrische CA), wird hierfür auch konventionelle OLS-Regression benutzt (metrische CA), obwohl dabei eine Verletzung de Modellannahme metrischer Qualität der abhängigen Variablen gegeben ist. Die vorliegende Simulationsstudie vergleicht LINMAP - ein Verfahren nichtmetrischer CA - und metrische CA, variiert wurde der Typus des datengenerierenden Modells (kompensatorisch, Interaktion, dominantes Attribut), der Anteil Fehlervarianz sowie die Größe des faktoriellen Designs. Entgegen den zugrundegelegten Hypothesen führte unter nahezu allen simulierten Bedingungen das metrische Verfahren zu einer besseren Vorhersage der ordinalen Relationen zwischen den multiattributiven Stimuli, als das nichtmetrische

Längsschnittliche Analysen zur Entwicklung der Zufriedenheit im höheren Lebensalter

Ausgehend von Befunden zur Lebenszufriedenheit im höheren Erwachsenenalter, die bei querschnittlichen Altersgruppenvergleichen keine Abnahme durchschnittlicher Zufriedenheiten bis weit ins hohe Alter hinein zeigen (sogenanntes "Wohlbefindensparadox" des höheren Lebensalters), wurde die Veränderung bzw. Stabilität von Zufriedenheitsurteilen über die hochaltrige Lebensphase längsschnittlich untersucht. Insbesondere wurde die folgenden möglichen Charakteristika der Entwicklung von Zufriedenheit im höheren Alter analysiert, durch die das Wohlbefindensparadox erklärt werden könnte: (1) Überlagerung negativer Alters- und Kohorteneffekte, (2) erhöhte Variabilität von Zufriedenheitsurteilen im höheren Lebensalter infolge häufiger Veränderungen in positiver und negativer Richtung, (3) lebenslang hohe oder (4) im höheren Alter erhöhte Stabilität von Zufriedenheitsurteilen. Zur Analyse dieser Fragestellungen wurden längsschnittliche Random-Effects-Regressionsmodelle und autoregressive Strukturgleichungsmodelle (sogenanntes Quasi-Markov Simplex) berechnet, als Datengrundlage dienten Zufriedenheitsratings des deutschen Sozioökonomischen Panels aus den jährlichen Befragungen 1984 bis 1999. Die Ergebnisse zeigen die Überlagerung eines negativen Alterseffekts mit einem negativen Effekt des Geburtsjahres bei den zum Ende des 20. Jahrhunderts Älteren, sowie eine insgesamt sehr hohe relative Stabilität (Tendenz zur intraindividuellen Aufrechterhaltung der relativen Ausprägung) der Zufriedenheitsurteile, unabhängig vom Alter der Befragungspersonen. Ein bei längsschnittlicher Betrachtung der Lebenszufriedenheit erkennbarer negativer Alterseffekt (Abnahme der Durchschnittswerte) im höheren Lebensalter stellt das Wohlbefindensparadox in Frage

Associations of Wellbeing Levels, Changes, and Within-Person Variability With Late-Life All-Cause Mortality Across 12 Years: Contrasting Hedonic vs. Eudaimonic Wellbeing Among Very Old Adults

Advanced old age has been characterized as a biologically highly vulnerable life phase. Biological, morbidity-, and cognitive impairment-related factors play an important role as mortality predictors among very old adults. However, it is largely unknown whether previous findings confirming the role of different wellbeing domains for mortality translate to survival among the oldest-old individuals. Moreover, the distinction established in the wellbeing literature between hedonic and eudaimonic wellbeing as well as the consideration of within-person variability of potentially relevant mortality predictors has not sufficiently been addressed in prior mortality research. In this study, we examined a broad set of hedonic and eudaimonic wellbeing indicators, including their levels, their changes, as well as their within-person variability, as predictors of all-cause mortality in a sample of very old individuals. We used data from the LateLine study, a 7-year longitudinal study based on a sample of n = 124 individuals who were living alone and who were aged 87–97 years (M = 90.6, SD = 2.9) at baseline. Study participants provided up to 16 measurement occasions (mean number of measurement occasions per individual = 5.50, SD = 4.79) between 2009 and 2016. Dates of death were available for 118 individuals (95.2%) who had deceased between 2009 and 2021. We ran longitudinal multilevel structural equation models and specified between-person level differences, within-person long-term linear change trends, as well as the “detrended” within-person variability in three indicators of hedonic (i.e., life satisfaction and positive and negative affect) and four indicators of eudaimonic wellbeing (i.e., purpose in life, autonomy, environmental mastery, and self-acceptance) as all-cause mortality predictors. Controlling for age, gender, education, and physical condition and testing our sets of hedonic and eudaimonic indictors separately in terms of their mortality impact, solely one eudaimonic wellbeing indicator, namely, autonomy, showed significant effects on survival. Surprisingly, autonomy appeared “paradoxically” related with mortality, with high individual levels and intraindividual highly stable perceptions of autonomy being associated with a shorter residual lifetime. Thus, it seems plausible that accepting dependency and changing perceptions of autonomy over time in accordance with objectively remaining capabilities might become adaptive for survival in very old age.Peer Reviewe

Trajectories of Pain in Very Old Age: The Role of Eudaimonic Wellbeing and Personality

Pain is common in very old age and in the last years prior to death. However, little is known regarding longitudinal trajectories of pain in very old age and at the end of life. Moreover, whereas medical and morbidity-related factors contributing to pain are established, the role of psychosocial factors, such as eudaimonic wellbeing or personality as potential determinants of late-life pain trajectories has so far not been sufficiently investigated. We used data from the LateLine project. The sample consisted of n = 118 very old adults (M = 90.5 years, SD = 2.8 years) who were living alone at baseline and who had died between 2009 and 2021. They took part in up to 16 measurement occasions (M = 5.2, SD = 4.7, range 1–16) within an observational interval of 7 years. Assessment of pain was based on the SF-36 bodily pain subscale. Key indicators of eudaimonic wellbeing (autonomy, environmental mastery, and purpose in life) as well two of the Big Five personality traits (neuroticism and extraversion) were included as predictors. We controlled in all analyses for gender, education, subjective health, and depressive symptoms. Contrasting pain trajectories over chronological age (time since birth) vs. time to death, a time-to-death-related model resulted in a better model fit and accounted for a larger amount of pain variability than the age-related model. Mean-level change in pain, both over age and time to death, was not significant, but there was substantial interindividual variability in intraindividual trajectories. Age-related change in pain was significantly predicted by autonomy and neuroticism, with increasing pain among those who had lower initial autonomy scores and higher initial neuroticism scores. With regard to time-to-death-related trajectories of pain, higher purpose in life as well as lower extraversion at baseline predicted less increase or even steeper decrease in pain with approaching death. Our findings suggest that, despite overall mean-level stability in pain both over age and time to death, there is a substantial proportion of individuals who reveal deterioration in pain over time. Regarding the role of psychosocial predictors, personality traits and eudaimonic wellbeing are related with late-life pain trajectories both over age and time-to-death.Peer Reviewe

EasyMLServe: Easy Deployment of REST Machine Learning Services

Various research domains use machine learning approaches because they can solve complex tasks by learning from data. Deploying machine learning models, however, is not trivial and developers have to implement complete solutions which are often installed locally and include Graphical User Interfaces (GUIs). Distributing software to various users on-site has several problems. Therefore, we propose a concept to deploy software in the cloud. There are several frameworks available based on Representational State Transfer (REST) which can be used to implement cloud-based machine learning services. However, machine learning services for scientific users have special requirements that state-of-the-art REST frameworks do not cover completely. We contribute an EasyMLServe software framework to deploy machine learning services in the cloud using REST interfaces and generic local or web-based GUIs. Furthermore, we apply our framework on two real-world applications, i. e., energy time-series forecasting and cell instance segmentation. The EasyMLServe framework and the use cases are available on GitHub

Analysing farmers' use of price hedging instruments: an experimental approach

This paper analyses the influencing factors of farmers' use of price hedging instruments (PHIs) based upon a discrete choice experiment with German grain farmers. A mixed logit model is used to determine whether farmers' choices of PHIs against cash sales are influenced by their price expectation, their risk attitude and their available storage capacities. The results show that farmers with a price expectation below the actual price level have a higher preference for using PHIs against cash sales in general and that the individual degree of risk aversion can have a significant impact on farmers' choices of a specific PHI. A generally lower preference of farmers with available storage capacities for using PHIs as assumed in many theoretical contributions in the literature, however, cannot be confirmed

Factor Xa subsite mapping by proteome-derived peptide libraries improved using WebPICS, a resource for proteomic identification of cleavage sites

Proteomic identification of protease cleavage site specificity (PICS) is a recent proteomic approach for the easy mapping of protease subsite preferences that determines both the prime- and non-prime side specificity concurrently. Here we greatly facilitate user access by providing an automated and simple web-based data-analysis resource termed WebPics (http://clipserve.clip.ubc.ca/pics/). We demonstrate the utility of WebPics analysis of PICS data by determining the substrate specificity of factor Xa from P6-P6', an important blood coagulation protease that proteolytically generates thrombin from prothrombin. PICS confirms existing data on non-prime site specificity and refines our knowledge of factor Xa prime-site selectivit

Four-year stability, change, and multidirectionality of well-being in very-old age

We examined stability, change, and dedifferentiation of well-being in 124 participants with a baseline age between 87 and 97 years (M = 90.56, SD = 2.92) across 7 measurement occasions over 4 years. Measures of hedonic (life satisfaction, positive affect and negative affect) and eudaimonic well-being (autonomy, purpose in life, self-acceptance, environmental mastery), as well as indicators of mental distress (depressive symptoms, attitudes toward death and dying, disease phobia) were included. Average levels indicated high well-being at all measurement occasions in the majority of indicators analyzed. However, mean numbers of depressive symptoms were close to the cutoff point of clinical depression. Analyses of intra-individual correlations revealed high loadings of depressive symptoms, positive affect, and environmental mastery on a common factor. However, several well-being indicators were not substantially interrelated on the intra-individual level, suggesting their trajectories were rather independent of each other. Acceptance of death and dying was surprisingly high and even increased, whereas mean levels in fear of death were very low and declined over time. Overall, our findings do not suggest late-life dedifferentiation of well-being trajectories in very-old age. Our results rather support the need to consider indicators of hedonic and eudaimonic well-being, as well as mental distress, to understand the multifaceted and multidirectional dynamics of well-being in very-old age