Data from: Group-level differences in social network structure remain repeatable after accounting from environmental drivers
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https://figshare.com/articles/dataset/Data_from_Group-level_differences_in_social_network_structure_remain_repeatable_after_accounting_from_environmental_drivers/23576601
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资源简介:
Datasets and R scripts for the analysis in Ogino M, Maldonado-Chaparro A, Aplin L, Farine D. 2023. Group-level differences in social network structure remain repeatable after accounting from environmental drivers.
Data:
AllAdults.csv: List of individuals in aviaries
Aviary_metrics_daily_Pre_Socper.csv, Aviary_metrics_daily_Post_Socper.csv, Aviary_metrics_daily_Pre_Feeder.csv, Aviary_metrics_daily_Post_Feeder.csv: files containing all response variables (colony-level social network metrics), predictors (external drivers), and random effects (colony ID, day ID)
Socper_CameraDetection_EachDay.csv, Feeder_CameraDetection_EachDay.csv: the number of camera detections for each day for each colony
SocPerch_dailyNWs_Allday, Feeding_dailyNWs_Allday: Social networks for each day for each colony
WeatherInfo: temperature and humidity data for each day
R scripts:
Script1__DailySocialNetworkMetrics.R: code to determine colony-level social network metrics
Script2__InformedModel__PlottingGLM_FixedEffects_Post_Socper.R: code to visualise the effects of each external driver on colony-level social network metrics. This code requires outcome from Script 1 and a function (FUNCTION__PlottingFunction.R) below.
Script2__InformedModel__Repeatability_informedmodels_bootstrapping.R, Script2__UninformedModel__Repeatability_uninformedmodels_bootstrapping.R: code to determine confidence intervals for the repeatability estimates of colony ID. This code requires outcome from Script 1 and functions below.
Script2__InformedModel__Repeatability_Post_Socper_brms.R, Script2__UninformedModel__Repeatability_False-Positive-Model_brms.R: code to estimate repeatability estimates of colony ID. This code requires outcome from Script 1.
Script2__InformedModel__Rsquare_Post_Socper.R: code to estimate R square for each model. This code requires outcome from Script 1 and a function (FUNCTION__get_variance_components) below.
Script2__VIF.R: code to check collinearity.
FUNCTION__get_variance_components.R: function to determine R square values.
FUNCTION__PlottingFunction.R: function to visualise the effect of external drivers on social network metrics.
创建时间:
2024-02-05



