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GeomFlatViolin
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geom_flat_violin_HELPER2 |
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baseline_data()
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Baseline pupil data to the average pupil size within a window |
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calculate_mean_pupil_size()
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Calculate a mean size across two pupils over time |
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calculate_missing_data()
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Calculate the missing data amount |
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clean_missing_data()
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Clean missing data above an acceptable threshold |
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create_difference_data()
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Create a difference data frame when dealing with a condition column with 2 levels |
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create_functional_data()
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Makes a functional data with splines from a Pupil_difference_data dataframe. |
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create_time_windows()
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Make PupillometryR dataframe into multiple time windows for easy analysis |
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create_window_data()
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Make PupillometryR dataframe into a single collapsed window for easy analysis |
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downsample_time_data()
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Downsample frequency to reduce number of samples and data size |
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filter_data()
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Run a filter on the data to smooth it out. |
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geom_flat_violin()
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ggplot Flat Violin |
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gfv_helper1
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geom_flat_violin_HELPER1 |
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interpolate_data()
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Interpolate across the gaps in data |
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make_pupillometryr_data()
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Prepare data for pre-processing in PupillometryR |
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mean2()
|
Helper function mean2 |
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plot(<Pupil_difference_data>)
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Pre-prepared plots of PupillometryR data |
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plot(<Pupil_test_data>)
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Pre-prepared plots of PupillometryR data |
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plot(<Pupil_window_data>)
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Pre-prepared plots of PupillometryR data |
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plot(<PupillometryR>)
|
Pre-prepared plots of PupillometryR data |
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pupil_data
|
Data collected in a pupillometry study by Sylvain Sirois |
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regress_data()
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Regress one pupil against another for extra smoothing |
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replace_missing_data()
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replaces missing observations if you have some degree of incomplete observations |
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run_functional_t_test()
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Run a functional t-test on a dataframe previously fitted with b-splines. |
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subset_data()
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Subset data to provide start and finish time windows |