PredPsych v0.3


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Predictive Approaches in Psychology

Recent years have seen an increased interest in novel methods for analyzing quantitative data from experimental psychology. Currently, however, they lack an established and accessible software framework. Many existing implementations provide no guidelines, consisting of small code snippets, or sets of packages. In addition, the use of existing packages often requires advanced programming experience. 'PredPsych' is a user-friendly toolbox based on machine learning predictive algorithms. It comprises of multiple functionalities for multivariate analyses of quantitative behavioral data based on machine learning models.

Functions in PredPsych

Name Description
DimensionRed Generic Dimensionallity Reduction Function
KinData Kinematics Dataset A dataset containing part of the motion capture dataset freely available in the publication (Ansuini et al., 2015).The dataset was obtained by recording 15 naive participants performing reach-to-grasp movements towards two differently sized objects: a small object (i.e., hazelnut) and a large object (i.e., grapefruit). The variables are as follows:
ClassPerm Permutation Analysis for classification
DTModel Generic Decision Tree Function
LinearDA Cross-validated Linear Discriminant Analysis
ModelCluster Model based Clustering
PredPsych PredPsych.
classifyFun Generic Classification Analyses
fscore f-score
overallConfusionMetrics Confusion Matrix metrics for Cross-validation
predictNewData Predict Class membership for New Data
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Type Package
Date 2017-08-25
License GPL-3
LazyData TRUE
RoxygenNote 5.0.1
Repository CRAN
NeedsCompilation no
Packaged 2017-08-25 14:34:12 UTC; koul
Date/Publication 2017-09-12 08:02:40 UTC

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