Visualisation of Forking Path Analysis CoScience

Porth et. al 2024, Perfectionism and Error Processing in a Flanker & GoNoGo Task

Here below select the Effect you want to plot.
You can use the first prompts to filter the selection.

Which Measure do you want to explore?

Which Task do you want to explore?

Which Personality Trait do you want to explore?

What kind of effect do you want to explore?

Which effect should be plotted?

Which variable should be plotted in the specification curve? All data will be sorted according to this.

Effect Size p-Value Sample Size Average Epochs

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None Effect Size p-Value Sample Size Average Epochs

Here below select the Forking Steps of interest.
For each selection, the distribution of the different Choices is plotted.

Preprocessing Steps

Resampling

Reference_AC

Bad_Channels

Bad_ChannelsMax

LP_Filter_Early

HP_Filter

LineNoise_Filter

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Epoching_AC

Detrending

Bad_Segments

Run_ICA

OccularCorrection

LP_Filter_Later

Bad_Epochs

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Quantification Steps

Reference

Baseline

Trials_Performance

Cluster_Electrodes

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Trials_MinNumber

Electrodes

TimeWindow

Quantification_ERP

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Statistical Analysis Steps

Attention_Checks

Outliers_Personality

Personality_Variable

Covariate

Outliers_Threshold

Outliers_Treatment

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Outliers_SME

Outliers_EEG

Outliers_ACC

Normalize

Center

Determine_Significance

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The red triangle highlights the main path that was
agreed on within the CoScience members.
Green dots indicate p < 0.05. Effect sizes were recoded to
include the direction of the effects.
For ERPs, three main paths are presented corresponding to
the three electrodes.