Package index
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launch_workbench()workbench_app() - Launch the mirtverse workbench
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mv_ask() - Write an analysis script from a plain-language request
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mv_ask_setup() - Set up an AI model for mv_ask()
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mv_plan()update_plan() - An analysis plan for mv_ask()
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run_script()save_script() - Run or save a script written by mv_ask()
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profile_data() - Summarise a data set without revealing its values
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select_model() - Model selection assistant
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interpret() - Plain-language interpretation of IRT results
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interpret_prompt() - Build a prompt for an AI assistant from a fitted model
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tidy(<SingleGroupClass>)tidy(<MultipleGroupClass>) - Tidy a mirt model into a data frame of parameters
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glance(<SingleGroupClass>)glance(<MultipleGroupClass>) - One-row model summary
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augment(<SingleGroupClass>) - Add person scores to the response data
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item_table() - Tidy item statistics and item fit in one table
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gg_dif() - DIF effect sizes plot
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gg_empirical() - Empirical versus model-implied item curve
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gg_info() - Test and item information curves
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gg_itemfit() - Item fit plot
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gg_q3() - Local dependence heatmap (Yen's Q3)
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gg_scores() - Distribution of person scores
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gg_trace() - Item characteristic (trace) curves
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gg_wright() - Wright map (person-item map)
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autoplot(<SingleGroupClass>) - Plot a mirt model with ggplot2
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theme_mirtverse() - A clean ggplot2 theme for psychometric graphics
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dif() - Differential item functioning (DIF) in one call
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item_card() - Item health card
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item_cards() - Health cards for many items
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mv_report() - One-call HTML report
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mv_dashboard() - Results dashboard for sharing
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export_dashboard() - Save a results dashboard to share