Establishing causal order in longitudinal studies combining binary and continuous dependent variables

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Main author: Kling, Gerhard
Other authors: Harvey, Charles
Maclean, Mairi
Format: Journal Article           
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id eprints-21140
recordtype eprints
institution SOAS, University of London
collection SOAS Research Online
language English
language_search English
description Longitudinal studies with a mix of binary outcomes and continuous variables are common in organizational research. Selecting the dependent variable is often difficult due to conflicting theories and contradictory empirical studies. In addition, organizational researchers are confronted with methodological challenges posed by latent variables relating to observed binary outcomes and within-subject correlation. We draw on Dueker’s (2005) qualitative vector autoregression (QVAR) and Lunn et al.’s (2014) multivariate probit model to develop a solution to these problems in the form of a qualitative short panel vector autoregression (QSP-VAR). The QSP-VAR combines binary and continuous variables into a single vector of dependent variables, making every variable endogenous a priori. The QSP-VAR identifies causal order, reveals within-subject correlation and accounts for latent variables. Using a Bayesian approach, the QSP-VAR provides reliable inference for short time dimension longitudinal research. This is demonstrated through analysis of the durability of elite corporate agents, social networks and firm performance in France. We provide our OpenBUGS code to enable implementation of the QSP-VAR by other researchers.
format Journal Article
author Kling, Gerhard
author_facet Kling, Gerhard
Harvey, Charles
Maclean, Mairi
authorStr Kling, Gerhard
author_letter Kling, Gerhard
author2 Harvey, Charles
Maclean, Mairi
author2Str Harvey, Charles
Maclean, Mairi
title Establishing causal order in longitudinal studies combining binary and continuous dependent variables
publisher Sage
publishDate 2017
url https://eprints.soas.ac.uk/21140/

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