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"extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/spiritspeak/aattools", "_realowner": "spiritspeak", "_cranurl": true, "_releases": [ { "version": "0.0.1", "date": "2020-06-14" }, { "version": "0.0.2", "date": "2022-08-12" }, { "version": "0.0.3", "date": "2024-08-16" } ], "_exports": [ "aat_bootstrap", "aat_compute", "aat_covreliability", "aat_covreliability_jackknife", "aat_doublemeandiff", "aat_doublemediandiff", "aat_dscore", "aat_dscore_multiblock", "aat_getstudydata", "aat_mediandscore", "aat_regression", "aat_simulate", "aat_simulate2", "aat_singlemeandiff", "aat_singlemediandiff", "aat_splithalf", "aat_standardregression", "aat_stimulus_rest", "aat_stimulusscores", "calpha", "case_prune_3SD", "compcorr", "cormean", "covEM", "error_prune_dropcases", "error_replace_blockmeanplus", "FlanaganRulon", "lambda2", "lambda4", "prune_nothing", "q_reliability", 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[ "aat_bootstrap", "plot.aat_bootstrap", "print.aat_bootstrap" ] }, { "page": "aat_compute", "title": "Compute simple AAT scores", "topics": [ "aat_compute" ] }, { "page": "aat_covreliability", "title": "Compute a dataset's reliability from its covariance matrix", "topics": [ "aat_covreliability", "aat_covreliability_jackknife", "plot.aat_covreliability_jackknife", "print.aat_covreliability", "print.aat_covreliability_jackknife" ] }, { "page": "aat_simulate", "title": "Simulate AAT datasets and predict parameters", "topics": [ "aat_getstudydata", "aat_simulate", "aat_simulate2" ] }, { "page": "aat_splithalf", "title": "Compute the bootstrapped split-half reliability for approach-avoidance task data", "topics": [ "aat_splithalf", "plot.aat_splithalf", "print.aat_splithalf" ] }, { "page": "aat_stimulus_rest", "title": "Compute stimulus-rest correlations of double-difference scores This function provides a statistic that can give an indication of how deviant the responses to specific stimuli are, in comparison to the rest of the stimulus set. The algorithm computes stimulus-rest correlations of stimulus-specific double-difference scores. It takes single-difference approach-avoidance scores for each stimulus, and computes every possible subtraction between individual stimuli from both stimulus categories. It then computes correlations between every such subtraction of stimuli on one hand, and the mean double difference score of all other stimuli. Stimulus-rest correlations are then computed by averaging every such subtraction-rest correlation involving a specific stimulus.", "topics": [ "aat_stimulus_rest", "plot.aat_stimulus_rest" ] }, { "page": "aat_stimulusscores", "title": "Compute stimulus-specific bias scores Computes mean single-difference scores (push - pull) for each stimulus.", "topics": [ "aat_stimulusscores" ] }, { "page": "Algorithms", "title": "AAT score computation algorithms", "topics": [ "aat_doublemeandiff", "aat_doublemediandiff", "aat_dscore", "aat_dscore_multiblock", "aat_mediandscore", "aat_regression", "aat_singlemeandiff", "aat_singlemediandiff", "aat_standardregression", "Algorithms" ] }, { "page": "cormean", "title": "Compute a minimally biased average of correlation values", "topics": [ "cormean" ] }, { "page": "correlation-tools", "title": "Correlation tools", "topics": [ "compcorr", "correlation-tools", "print.compcorr", "r2p", "r2t", "r2z", "rconfint", "t2r", "z2r" ] }, { "page": "covEM", "title": 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