Christmas cards, Easter bunnies, and Granger-causality

Atukeren, Erdal

doi:10.1007/s11135-007-9078-2

Cited by 19 publications

(13 citation statements)

References 15 publications

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“…In other words, the time-ordered significance denoted by Granger causality tests identifies explanatory mechanisms but does not prove actual causation, as Atukeren (2008) demonstrated in a study of Christmas cards, Easter bunnies, and Granger causality (see also Sayre et al, 2010). Stated more simply, Granger causality testing is in some ways similar to interpreting bivariate correlations, with the notable exception that Granger models identify more clearly when a time-ordered change in one variable precedes a change in a related variable.…”

Section: Quantitative Analyses: Modelsmentioning

confidence: 98%

Forecasting and observing: A cross-methodological consideration of Internet and mobile phone diffusion in the Egyptian revolt

Groshek

2012

International Communication Gazette

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This study examines the Egyptian revolt (see Zhuo et al., 2011) of January/February 2011 from two discrete perspectives. The first perspective is a contextual marker that takes into account long-term and forecast trends in democracy from 1952 through 2011. The second perspective reports the opinions and viewpoints of Egyptian citizens living in a remote fishing village and resort town through impromptu in-person interviews conducted between 23 and 30 January 2011. The statistical findings evidence that the Internet and mobile phones have helped to facilitate sociopolitical instability and democratic change over time, while the personal interviews paradoxically suggest circumspection in making generalizations about how these events have proceeded across a large population and through a period of tightly suppressed communication when Internet access was shut down. Taken together, characterizing the events in Egypt as having been just a social media revolution therefore appears to misrepresent the evolution of political change in the country through this time period.

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Section: Quantitative Analyses: Modelsmentioning

confidence: 98%

Forecasting and observing: A cross-methodological consideration of Internet and mobile phone diffusion in the Egyptian revolt

Groshek

2012

International Communication Gazette

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“…The simplest concept is based on estimating the time lag between events occurring in a pair of signals (Nolte et al 2008;Gross et al 2000). This is linked to the principle that a cause must precede its effect, but it should be noted that temporal precedence does not provide direct evidence for causal interactions (Atukeren 2008). In the time domain, the cross correlation function can be used to estimate time lags between signals.…”

Section: Measures Of Directed Interactionsmentioning

confidence: 99%

Studying Dynamic Neural Interactions with MEG

Schoffelen

Groß

2014

Magnetoencephalography

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Interactions between functionally specialized brain regions are crucial for normal brain function. Magnetoencephalography (MEG) is suited to capture these interactions because it provides whole head measurements of brain activity with temporal resolution in the millisecond range. Many different measures of connectivity exist and in order to take the connectivity analysis results at face value one should be aware of the strengths and weaknesses of these measures. Next to this, an important challenge in MEG connectivity analysis lies in the fact that more than one sensor picks up the activity of any underlying source. This field spread severely limits the utility of connectivity measures computed directly between sensor recordings. As a consequence, neuronal interactions should be ideally studied on the level of the reconstructed sources. MEG is well suited for this purpose, since its signal properties and high spatial sampling allows for relatively accurate unmixing of the sensor recordings. This chapter provides some necessary background on connectivity analysis in general, and proceeds by describing the challenges that are associated with the analysis of MEG-based connectivity at the sensor level. Source level approaches are described and some recent advances with respect to MEG-based connectivity during the resting state and graph theoretic approaches are described.

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“…Using concepts pioneered by Granger (1969), the current study aims to establish causal relationships among our three variables by using time series data to improve the prediction of outcome variables of interest. Specifically, Granger causality between stochastic variables X and Y is found when adding the history of X to all other available relevant information “significantly reduces the forecast error variance of Y” (Atukeren, 2008, p. 836). X is said to be the Granger cause of Y when the cross-lagged prediction of X on Y is significant but the cross-lagged prediction of Y on X is not significant, while simultaneously controlling for the autoregression of both X and Y.…”

Section: Granger Causalitymentioning

confidence: 99%

An Idiographic Examination of Day-to-Day Patterns of Substance Use Craving, Negative Affect, and Tobacco Use Among Young Adults in Recovery

Zheng

Wiebe

Cleveland

et al. 2013

Multivariate Behavioral Research

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Psychological constructs, such as negative affect and substance use cravings that closely predict relapse, show substantial intra-individual day-to-day variability. This intra-individual variability of relevant psychological states combined with the “one day of a time” nature of sustained abstinence warrant a day-to-day investigation of substance use recovery. This study examines day-to-day associations among substance use cravings, negative affect, and tobacco use among 30 college students in 12-step recovery from drug and alcohol addictions. To account for individual variability in day-to-day process, it applies an idiographic approach. The sample of 20 males and 10 females (mean age = 21) was drawn from members of a collegiate recovery community at a large university. Data were collected with end-of-day data collections taking place over an average of 26.7 days. First-order vector autoregression models were fit to each individual predicting daily levels of substance use cravings, negative affect, and tobacco use from the same three variables one day prior. Individual model results demonstrated substantial inter-individual differences in intra-individual recovery process. Based on estimates from individual models, cluster analyses were used to group individuals into two homogeneous subgroups. Group comparisons demonstrate distinct patterns in the day-to-day associations among substance use cravings, negative affect, and tobacco use, suggesting the importance of idiographic approaches to recovery management and that the potential value of focusing on negative affect or tobacco use as prevention targets depends on idiosyncratic processes.

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Christmas cards, Easter bunnies, and Granger-causality

Abstract: Semantics of Granger-causality, Granger-Hsiao direct causality, Econometric methodology, B40, C50, A20,

Cited by 19 publications

References 15 publications

Forecasting and observing: A cross-methodological consideration of Internet and mobile phone diffusion in the Egyptian revolt

Forecasting and observing: A cross-methodological consideration of Internet and mobile phone diffusion in the Egyptian revolt

Studying Dynamic Neural Interactions with MEG

An Idiographic Examination of Day-to-Day Patterns of Substance Use Craving, Negative Affect, and Tobacco Use Among Young Adults in Recovery

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