
Package index
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add_common_effect_sizes() - Add common effect size columns to FReD dataset
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add_replication_power() - Add power
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add_sampling_variances() - Add confidence intervals
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align_effect_direction() - Align effect direction
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assess_replication_outcome() - Assess Replication Outcomes Based on Various Criteria
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calculate_prediction_interval() - Calculate Prediction Interval for a Correlation Coefficient
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clean_variables() - Clean variables Perform some specific operations (e.g., recoding some NA as "") required to get the Shiny apps to work. This may be a temporary solution, as much of it should likely be handled through validation in the data sheet, and at import time.
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code_replication_outcomes() - Code replication outcomes
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coerce_to_numeric() - Coerce specified variables to numeric and identify problematic values
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convert_effect_sizes() - Convert effect sizes to common metric (r)
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create_citation() - Create FReD dataset citation
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get_dataset_changelog() - Get the dataset changelog from OSF
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get_last_modified() - Get the date of last modification
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load_fred_data() - Load the FReD dataset
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load_variable_descriptions() - Load variable descriptions
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print(<fred_equivalence_test_result>) - Print Method for Equivalence Test Result
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read_fred() - Read the FReD dataset
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run_annotator() - Run the Replication Annotator
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run_app() - Run a shiny app within the package - potentially as an RStudio job
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run_explorer() - Run the Replication Explorer
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setting-parameters - Setting Parameters for the FReD Package
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test_equivalence_r() - Equivalence Test for a Correlation
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update_offline_data() - Update inbuilt data
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use_FReD_offline() - Set FReD to work offline (or back to online)