scholarly journals Reliable hypotheses testing in animal social network analyses: global index, index of interactions and residual regression

2021 ◽  
Author(s):  
Sebastian Sosa ◽  
Cristian Pasquaretta ◽  
Ivan Puga-Gonzalez ◽  
F Stephen Dobson ◽  
Vincent A Viblanc ◽  
...  
Keyword(s):  
Social Network ◽  
Type I Error ◽  
Statistical Hypothesis ◽  
Type I ◽  
Global Index ◽  
Statistical Hypothesis Testing ◽  
False Negatives ◽  
Network Analyses ◽  
Wide Range ◽  
Social Network Analyses

Animal social network analyses (ASNA) have led to a foundational shift in our understanding of animal sociality that transcends the disciplinary boundaries of genetics, spatial movements, epidemiology, information transmission, evolution, species assemblages and conservation. However, some analytical protocols (i.e., permutation tests) used in ASNA have recently been called into question due to the unacceptable rates of false negatives (type I error) and false positives (type II error) they generate in statistical hypothesis testing. Here, we show that these rates are related to the way in which observation heterogeneity is accounted for in association indices. To solve this issue, we propose a method termed the "global index" (GI) that consists of computing the average of individual associations indices per unit of time. In addition, we developed an "index of interactions" (II) that allows the use of the GI approach for directed behaviours. Our simulations show that GI: 1) returns more reasonable rates of false negatives and positives, with or without observational biases in the collected data, 2) can be applied to both directed and undirected behaviours, 3) can be applied to focal sampling, scan sampling or "gambit of the group" data collection protocols, and 4) can be applied to first- and second-order social network measures. Finally, we provide a method to control for non-social biological confounding factors using linear regression residuals. By providing a reliable approach for a wide range of scenarios, we propose a novel methodology in ASNA with the aim of better understanding social interactions from a mechanistic, ecological and evolutionary perspective.

scholarly journals Workflow for constructing social networks from automated telemetry systems

2020 ◽  
Author(s):  
Daizaburo Shizuka ◽  
Sahas Barve ◽  
Allison Johnson ◽  
Eric Walters
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Radio Telemetry ◽  
Base Stations ◽  
Breeding Bird ◽  
Spatial And Temporal Scales ◽  
Network Analyses ◽  
Wide Range ◽  
Social Network Analyses ◽  
Automated Telemetry

1.Advances in datalogging technologies have provided a way to monitor the movement of individual animals at unprecedented spatial and temporal scales, both large and small. When used in conjunction with social network analyses, these data can provide insight into fine scale associative behaviors. The variety of technologies demand continuous progress in workflows to translate data streams from automated systems to social networks, based on biologically relevant metrics. 2.Here we present a workflow for generating flexible association matrices from automated radio-telemetry data that can be parsed into both spatial and temporal dimensions. These can then be used to generate and compare social networks across space and time.3.We illustrate this workflow using data collected from an automated telemetry study of acorn woodpeckers (Melanerpes formicivorus), a cooperatively breeding bird. The data were collected continuously over two years at base stations placed within social group territories. We use this system to demonstrate how this flexible data structure can be used to answer a number of biological questions, specifically 1) how assortative are social associations at the population scale, 2) how do association patterns among territory visitors vary across territories, 3) and how does seasonality affect assortative affiliation within groups?4.This flexible method allows one to generate social networks that can be used to ask a variety of biological questions pertinent to a wide range of animal systems, exploiting the investigative power that can be gained by using automated radio-telemetry in conjunction with social network analyses.

scholarly journals Experimental evidence for delayed contingent cooperation among wild dwarf mongooses

2018 ◽  
Vol 115 (24) ◽  
pp. 6255-6260 ◽  
Author(s):  
Julie M. Kern ◽  
Andrew N. Radford
Keyword(s):  
Social Network ◽  
Experimental Evidence ◽  
Causal Link ◽  
Temporal Delay ◽  
Biological Markets ◽  
Network Analyses ◽  
Group Members ◽  
Access To Food ◽  
Social Network Analyses ◽  
Social Network Position

Many animals participate in biological markets, with strong evidence existing for immediate cooperative trades. In particular, grooming is often exchanged for itself or other commodities, such as coalitionary support or access to food and mates. More contentious is the possibility that nonhuman animals can rely on memories of recent events, providing contingent cooperation even when there is a temporal delay between two cooperative acts. Here we provide experimental evidence of delayed cross-commodity grooming exchange in wild dwarf mongooses (Helogale parvula). First, we use natural observations and social-network analyses to demonstrate a positive link between grooming and sentinel behavior (acting as a raised guard). Group members who contributed more to sentinel behavior received more grooming and had a better social-network position. We then used a field-based playback experiment to test a causal link between contributions to sentinel behavior and grooming received later in the day. During 3-h trial sessions, the perceived sentinel contributions of a focal individual were either up-regulated (playback of its surveillance calls, which are given naturally during sentinel bouts) or unmanipulated (playback of its foraging close calls as a control). On returning to the sleeping refuge at the end of the day, focal individuals received more grooming following surveillance-call playback than control-call playback and more grooming than a matched individual whose sentinel contributions were not up-regulated. We believe our study therefore provides experimental evidence of delayed contingent cooperation in a wild nonprimate species.

Location Tests for Biomarker Studies: A Comparison Using Simulations for the Two-sample Case

2013 ◽  
Vol 52 (04) ◽  
pp. 351-359 ◽  
Author(s):  
M. O. Scheinhardt ◽  
A. Ziegler
Keyword(s):  
Heavy Tails ◽  
Type I Error ◽  
Adaptive Methods ◽  
Type I ◽  
Skewed Data ◽  
Error Level ◽  
Adaptive Tests ◽  
Wide Range ◽  
Heavy Tailed ◽  
Non Parametric

Summary Background: Gene, protein, or metabolite expression levels are often non-normally distributed, heavy tailed and contain outliers. Standard statistical approaches may fail as location tests in this situation. Objectives: In three Monte-Carlo simulation studies, we aimed at comparing the type I error levels and empirical power of standard location tests and three adaptive tests [O’Gorman, Can J Stat 1997; 25: 269 –279; Keselman et al., Brit J Math Stat Psychol 2007; 60: 267– 293; Szymczak et al., Stat Med 2013; 32: 524 – 537] for a wide range of distributions. Methods: We simulated two-sample scena -rios using the g-and-k-distribution family to systematically vary tail length and skewness with identical and varying variability between groups. Results: All tests kept the type I error level when groups did not vary in their variability. The standard non-parametric U-test per -formed well in all simulated scenarios. It was outperformed by the two non-parametric adaptive methods in case of heavy tails or large skewness. Most tests did not keep the type I error level for skewed data in the case of heterogeneous variances. Conclusions: The standard U-test was a powerful and robust location test for most of the simulated scenarios except for very heavy tailed or heavy skewed data, and it is thus to be recommended except for these cases. The non-parametric adaptive tests were powerful for both normal and non-normal distributions under sample variance homogeneity. But when sample variances differed, they did not keep the type I error level. The parametric adaptive test lacks power for skewed and heavy tailed distributions.

scholarly journals Comment on "Why and When 'Flawed' Social Network Analyses Still Yield Valid Tests of no Contagion"

2012 ◽  
Vol 3 (1) ◽  
Author(s):  
Cosma Rohilla Shalizi
Keyword(s):  
Social Network ◽  
Observational Data ◽  
Network Analyses ◽  
Social Network Analyses

VanderWeele et al.'s paper is a useful contribution to the on-going scientific conversation about the detection of contagion from purely observational data. It is especially helpful as a corrective to some of the more extreme statements of Lyons (2011). Unfortunately, this paper, too, goes too far in some places, and so needs some correction itself.

scholarly journals Predicting behavior change from persuasive messages using neural representational similarity and social network analyses

NeuroImage ◽  
2017 ◽  
Vol 157 ◽  
pp. 118-128 ◽  
Author(s):  
Teresa K. Pegors ◽  
Steven Tompson ◽  
Matthew Brook O’Donnell ◽  
Emily B. Falk
Keyword(s):  
Social Network ◽  
Behavior Change ◽  
Persuasive Messages ◽  
Network Analyses ◽  
Predicting Behavior ◽  
Social Network Analyses

scholarly journals How does individual variation in sociality influence fitness in prairie voles?

2019 ◽  
Author(s):  
Anne C. Sabol ◽  
Connor T. Lambert ◽  
Brian Keane ◽  
Nancy G. Solomon ◽  
Ben Dantzer
Keyword(s):  
Social Network ◽  
Social Behavior ◽  
Individual Variation ◽  
Mating Success ◽  
Social Connections ◽  
Prairie Voles ◽  
Network Analyses ◽  
Fitness Consequences ◽  
Opposite Sex ◽  
Social Network Analyses

AbstractComparative studies aid in our understanding of specific conditions favoring the initial evolution of different types of social behaviors, yet there is much unexplained intraspecific variation in the expression of social behavior that comparative studies have not yet addressed. The proximate causes of this individual variation in social behavior within a species have been examined in some species but its fitness consequences have been less frequently investigated. In this study, we quantified the fitness consequences of variation in the sociality of prairie voles (Microtus ochrogaster). We characterized sociality of voles in semi-natural enclosures using an automated behavioral tracking system paired with social network analyses to quantify the degree of spatial and temporal co-occurrence of different voles. We then assessed the relationship between sociality with mating success (number of different conspecifics with which an individual produced offspring) and reproductive success (total number of offspring surviving to first capture). We measured the number of social connections each individual had with all voles and only with opposite-sex voles by calculating unweighted degree through social network analyses. Both female and male voles varied in the number of social connections they had with all conspecifics and with opposite-sex conspecifics. Voles with an intermediate number of social connections with voles of both sexes had higher mating success overall. In our analyses that considered all social connections with voles of both sexes, voles with an intermediate number of social connections produced more offspring. Males with a very high or low number of social connections also had the lowest average body mass. Overall, our results suggest some limit on the fitness benefits of sociality. Although there was substantial individual-variation in our measure of vole social behavior, intermediate levels of social connections may be most favorable.

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