Exact Variance of Indirect Effects in Recursive Linear Models

1995 ◽  
Vol 25 ◽  
pp. 253 ◽  
Author(s):  
Paul D. Allison
Keyword(s):  
Indirect Effects ◽  
Linear Models

scholarly journals Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins

Toxins ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 156 ◽  
Author(s):  
Evanthia Mantzouki ◽  
Miquel Lürling ◽  
Jutta Fastner ◽  
Lisette De Senerpont Domis ◽  
Elżbieta Wilk-Woźniak ◽  
...  
Keyword(s):  
Indirect Effects ◽  
Linear Models ◽  
Diversity Index ◽  
Toxin Production ◽  
Direct And Indirect Effects ◽  
Cyanobacterial Toxins ◽  
Toxic Species ◽  
Continental Scale ◽  
Production And Distribution ◽  
The Relationship

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.

scholarly journals Inferring species interactions from co-occurrence data with Markov networks

2015 ◽  
Author(s):  
David J. Harris
Keyword(s):  
Indirect Effects ◽  
Species Interactions ◽  
Markov Random Fields ◽  
Linear Models ◽  
Abiotic Factors ◽  
Species Interaction ◽  
Pairwise Interaction ◽  
Interaction Matrix ◽  
Markov Networks ◽  
Occurrence Data

Inferring species interactions from co-occurrence data is one of the most controversial tasks in community ecology. One difficulty is that a single pairwise interaction can ripple through an ecological network and produce surprising indirect consequences. For example, the negative correlation between two competing species can be reversed in the presence of a third species that is capable of outcompeting both of them. Here, I apply models from statistical physics, called Markov networks or Markov random fields, that can predict the direct and indirect consequences of any possible species interaction matrix. Interactions in these models can also be estimated from observed co-occurrence rates via maximum likelihood, controlling for indirect effects. Using simulated landscapes with known pairwise interaction strengths, I evaluated Markov networks and six existing approaches. The Markov networks consistently outperformed other methods, correctly isolating direct interactions between species pairs even when indirect interactions or abiotic factors largely overpowered them. Two computationally efficient approximations, based on controlling for indirect effects with linear or generalized linear models, also performed well. Indirect effects reliably caused a common null modeling approach to produce incorrect inferences, however.

A Note on Effects of Digital Approximation in Linear Models

1974 ◽  
Vol 3 (9) ◽  
pp. 893-897
Author(s):  
Gerald McWilliams ◽  
James Poirot†
Keyword(s):  
Linear Models

Effects of Momentary Affect on Satisfaction Judgments

2020 ◽  
Vol 41 (2) ◽  
pp. 61-67
Author(s):  
Marko Tončić ◽  
Petra Anić
Keyword(s):  
Linear Models ◽  
Time Frame ◽  
Hierarchical Linear Models ◽  
Curvilinear Relationship ◽  
Positive And Negative Affect ◽  
Transient Events ◽  
Time Frames ◽  
Events Data ◽  
Level Satisfaction ◽  
Source Of Information

Abstract. This study aims to examine the effect of affect on satisfaction, both at the between- and the within-person level for momentary assessments. Affect is regarded as an important source of information for life satisfaction judgments. This affective effect on satisfaction is well established at the dispositional level, while at the within-person level it is heavily under-researched. This is true especially for momentary assessments. In this experience sampling study both mood and satisfaction scales were administered five times a day for 7 days via hand-held devices ( N = 74 with 2,122 assessments). Several hierarchical linear models were fitted to the data. Even though the amount of between-person variance was relatively low, both positive and negative affect had substantial effects on momentary satisfaction on the between- and the within-person level as well. The within-person effects of affect on satisfaction appear to be more pronounced than the between-person ones. At the momentary level, the amount of between-person variance is lower than in studies with longer time-frames. The affect-related effects on satisfaction possibly have a curvilinear relationship with the time-frame used, increasing in intensity up to a point and then decreasing again. Such a relationship suggests that, at the momentary level, satisfaction might behave in a more stochastic manner, allowing for transient events/data which are not necessarily affect-related to affect it.

Does Ego-Resilience Impact Friendship Outcomes?

2016 ◽  
Vol 37 (2) ◽  
pp. 128-134 ◽  
Author(s):  
Elizabeth B. Lozano ◽  
Mahzad Hojjat ◽  
Judith Sims-Knight
Keyword(s):  
Social Support ◽  
Young Adults ◽  
Indirect Effects ◽  
Positive Emotions ◽  
Positive Outcomes ◽  
Ego Resilience ◽  
Maintenance Behaviors ◽  
Received Social Support ◽  
Trait Resilience ◽  
The Relationship

Abstract. The present study examined the relationship between resilience and positive outcomes in friendships of young adults. SEM and bootstrapping analyses were performed to test whether positive emotions mediate the relationship between ego-resilience and enhanced friendship outcomes. Findings revealed indirect effects for friendship closeness, maintenance behaviors, and received social support. Our findings demonstrate the importance of positive emotions and its connection with trait resilience in the realm of friendships.

Interpersonal Stress and Poor Health

2010 ◽  
Vol 15 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Mette M. Aanes ◽  
Maurice B. Mittelmark ◽  
Jørn Hetland
Keyword(s):  
Psychological Distress ◽  
Depressive Symptoms ◽  
Social Relationships ◽  
Indirect Effects ◽  
Social Connectedness ◽  
Somatic Symptoms ◽  
Total Effect ◽  
Subjective Feeling ◽  
Interpersonal Stress ◽  
The Relationship

This paper investigated whether the lack of social connectedness, as measured by the subjective feeling of loneliness, mediates the well-known relationship between interpersonal stress and psychological distress. Furthermore, a relationship between interpersonal stress and somatic symptoms was hypothesized. The study sample included 3,268 women and 3,220 men in Western Norway. The main findings were that interpersonal stress was significantly related to psychological distress as well as to somatic symptoms, both directly and indirectly via paths mediated by loneliness. The size of the indirect effects varied, suggesting that the importance of loneliness as a possible mediator differs for depressive symptoms, anxiety symptoms, and somatic symptoms. In the case of depressive symptoms, more than 75% of the total effect was mediated through loneliness, while in the case of somatic symptoms just over 40% of the total effect was mediated through loneliness. This study supports the hypotheses that social connectedness mediates a relationship between interpersonal stress and psychological distress. The study also provides the first link between interpersonal stress, as measured by the Bergen Social Relationships Scale, and somatic symptoms, extending earlier research on the relationship between interpersonal stress and psychological distress.

Introduction to Hierarchical Linear Models

1994 ◽  
Vol 39 (5) ◽  
pp. 475-476
Author(s):  
Paula L. Woehlke
Keyword(s):  
Linear Models ◽  
Hierarchical Linear Models
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