Follower behavior renders leader behavior endogenous: The simultaneity problem, estimation challenges, and solutions

This page contains all data needed to replicate the results reported in the article "Follower behavior renders leader behavior endogenous: The simultaneity problem, estimation challenges, and solutions ". First, we mathematically demonstrate the problem of simultaneity bias using a simulated dataset and show how the identification problem can be analytically solved by means of an instrumental variables-approach(Study 1). Second, we present data from naturally occurring interactions between leaders and followers that make the simultaneous influence processes particularly salient (n = 108; Study 2). Third, we present how simultaneity can be resolved from a research design perspective using experimental approaches (n = 31; Study 3). The file "data_study1" contains the simulated data (in .csv format). The file "data_study2" contains the frequencies of behavior codes (in .csv format) derived from dyadic conversations between leaders and followers from Study 2. Data was analyzed using lag sequential analysis implemented in the Generalized Sequential Querier (GSEQ, Bakeman & Quera, 1995). The file "data_study3" contains the frequencies of behavior codes (in .csv format) derived from an experiment involving dyadic conversations between leaders and followers from Study 3. The results from this data are reported in Table 1 and 2 of the manuscript. The point-by-point estimation procedure is provided in the manuscript.本页面包含复现论文《追随者行为使领导者行为呈现内生性：同步性难题、估计挑战与解决方案》中报告结果所需的全部数据。首先，我们通过模拟数据集从数学层面论证了同步性偏差问题，并展示了如何借助工具变量法（instrumental variables approach）从分析层面解决该识别难题（研究1）。其次，我们提供了来自领导者与追随者自然互动场景的数据，该场景使得同步影响过程尤为凸显（样本量n=108；研究2）。第三，我们展示了如何从研究设计视角出发，通过实验方法解决同步性问题（样本量n=31；研究3）。文件"data_study1"包含模拟数据（格式为.csv）。文件"data_study2"包含源自研究2中领导者与追随者双边对话的行为编码频次数据（格式为.csv）。本研究数据采用广义序列查询器（Generalized Sequential Querier, GSEQ, Bakeman & Quera, 1995）中实现的滞后序列分析法进行分析。文件"data_study3"包含源自研究3中领导者与追随者双边对话实验的行为编码频次数据（格式为.csv）。该数据的分析结果已在论文的表1与表2中呈现，逐点估计程序详见论文正文。