maeve_options: Set or get options for maeve

In wfforrest/maeve: Modeling Accessories Enabling Visualization of Experiments

Description

Set or get options for maeve

Usage

maeve_options(...)

Arguments

...	Option names to retrieve option values or [key]=[value] pairs to set options.

Value

a function as from settings::options_manager()

Supported options

The following options are supported

• group_name (character; 'group_name') The column name for the group name factor

• subject_ID (character; 'animalID') The column name for the subject name factor.

• trace_ID (character; 'animalID') The column name for the trace identifier name factor for maeve::grid_by_trace().

• x_name (character; 'DAY_OF_STUDY') The column name for the x-axis / time field

• endpoint_name (character; 'TUMOR_VOLUME') The column name for the y-axis / response field

• EOS_CR_minval (numeric; 0) numeric threshold to count an end-of-study complete response if a subject_ID has its last endpoint_name value at or below this value.

• PR_threshold (numeric; 0.5) numeric threshold to count a partial response if a subject_ID has any observations at or below this fraction of its baseline endpoint_name value and is NOT an end-of-study complete response (EOS_CR).

• full_study_data_frame (data.frame; NULL) data.frame with untruncated study data. Typically returned from (model_study(...))[['data']][['clean_DF_full_study']]

• modeling_data_frame (data.frame; NULL) data.frame with internal names used for predictions. Typically returned from (model_study(...))[['data']][['clean_DF_restricted']]

• autoset_full_study_data (logical; TRUE) Whether to automatically assign (model_study(...))[['data']][['clean_DF_full_study']] to maeve_options('full_study_data_frame' = full_study_data_frame)

• autoset_modeling_data (logical; TRUE) Whether to automatically assign (model_study(...))[['data']][['clean_DF_restricted']] to maeve_options('modeling_data_frame' = modeling_data_frame)

• truncate_fit (logical; FALSE) Whether to truncate predicted values to the range of observed responses within maeve:predict_study()?

• truncation_return_type (character; 'data.frame') What data type to return from "truncate_study()"?

• truncated_group_levels (character; character(0)) Which group levels are entirely lost when "truncate_study()" is run within model_study()?

• min_n_in_group (numeric; 0) all times in a group are truncated when less than this number of subjects are left in the group.

• min_frac_in_group (numeric; 0) all times in a group are truncated when less than this fraction of subjects are left in the group.

• min_frac_in_study (numeric; 0) all times in a study are truncated when less than this fraction of subjects are left in the entire study.

• overall_x_min (numeric; -Inf) data with x-axis values below this number are truncated.

• overall_x_max (numeric; Inf) data with x-axis values above this number are truncated.

• abbreviate_n (numeric; 1e6) The maximum number of characters in a group name

• reference_Dunnett (character; NULL) Character string with the group factor level to use as Dunnett reference. If NULL, the first level should be used.

• add_to_endpoint (numeric; 1) The offset value added to the endpoint before transformation

• restrict_x (logical; FALSE) Restrict to the x-values found in the specified reference group

• number_basis_vecs (numeric; -1) Default number of basis_vecs to try in fitting a spline.

• min_basis_vecs (numeric; 3) Minimum number of basis_vecs to try in fitting a spline.

• max_basis_vecs (numeric; 15) Maximum number of basis_vecs to try in fitting a spline.

• trans_func_char (character; 'log') Function for transformation of (endpoint_name + add_to_endpoint)

• inv_func_char (character; 'exp') Inverse function for transformation of (endpoint_name + add_to_endpoint)

• test_func_x (numeric; 1:10 ) Values with which to test that trans_func and inv_func are inverse functions.

• weight_lmer_option (character; 'uniform' ) Select how x-values should be weighted in lme4 linear mixed model regression.

• metric (character; c('linear','ITGR','AUC') ) Summarization method(s) for longitudinal response function.

• metrics_supported (character; c('linear','ITGR','AUC', 'ITGR_pwl', 'AUC_pwl', 'ITGR_poly', 'AUC_poly') ) Supported summarization methods for longitudinal response function.

• N_integration_grid (numeric; 25) Number of equally-spaced points to use in the Simpson Rule numerical integration.

• contrast (character; 'Identity') Contrast for group summary comparisons.

• xrange_norm_method (character; 'slope_equivalent') Method for normalization of spline summary statistics.

• progress (logical; FALSE) Print out various progress messages from the functions.

• number_break_points (numeric; 3) Number of break points (including 2 end points) in piecewise linear regression when metric = 'AUC_pwl'. Typically used for 3 time points.

• break_points (numeric; NULL) Break points (including 2 end points) in piecewise linear regression when metric = 'AUC_pwl'. Typically used for 3 time points.

• poly_degree (numeric; 2) Degree of simply polynomial (NOT the spline) fit, when metric = 'AUC_poly'. Typically used for 3 time points.

• poly_object (poly,matrix; NULL) Object returned from stats::poly() call in maeve:::make_basissis_matrix() when metric = 'AUC_poly'. Typically used for 3 time points.

• mismatch_action (character; 'stop') Action when a function is passed arguments that do not match either the function or an element of maeve_options().

• x_pred_type (character; 'observed') One of c( 'observed', 'grid', 'union_observed_and_grid', 'custom' ) determining options for what the x-axis values for predictions should be. If "custom", then the vector 'x_pred_vec' will be used. Otherwise, 'x_pred_vec' is ignored.

• x_pred_vec (numeric; NULL) numeric vector of values to use for x-axis prediction points when x_pred_type = 'custom'.

• x_pred_spacing (numeric; 1) distance between x-values in a prediction grid.

• x_pred_interior_grid (logical; TRUE) whether to truncate the grid endpoints to be the most widely spaced integers within the range.

• include_newdata_ID (logical; TRUE) whether to include subject_ID values in the data.frame.

• title_label (character; ”) ggplot2::labs( title = title_label )

• y_label (character; 'log( tumor volume + 1 )') ggplot2::labs( y = y_label )

• x_label (character; 'day' ) ggplot2::labs( x = x_label )

• legend_position_char (character; 'none') ggplot2::theme( legend.position = legend_position_char )

• axis_text_x_angle (numeric; 0) ggplot2::theme( axis.text.x = element_text( angle = axis_text_x_angle ) )

• axis_text_x_size (numeric; 9) ggplot2::theme( axis.text.x = element_text( size = axis_text_x_size ) )

• axis_text_x_hjust (numeric; 0.5) ggplot2::theme( axis.text.x = element_text( hjust = axis_text_x_hjust ) )

• axis_text_x_vjust (numeric; 0.5) ggplot2::theme( axis.text.x = element_text( vjust = axis_text_x_vjust ) )

• axis_text_y_size (numeric; 9) ggplot2::theme( axis.text.y = element_text( size = axis_text_y_size ) )

• legend_text_size (numeric; 9) ggplot2::theme( legend.text = element_text( size = legend_text_size ) )

• strip_text_size (numeric; 9) ggplot2::theme( strip.text = element_text( size = strip_text_size ) )

• linear_predictor (character; 'pred_lin') column name of linear predictor in data.frame of predicted output.

• linear_color (character; 'red') color of linear predictor.

• linear_lwd (numeric; 1.50) line width parameter for linear predictor, passed to geom_line(...)

• spline_predictor (character; 'pred_gam') column name of spline predictor in data.frame of predicted output.

• spline_color (character; 'black') color of spline predictor.

• spline_lwd (numeric; 1.25) line width parameter for spline predictor, passed to geom_line(...)

• piecewise_predictor (character; 'pred_pwl') column name of piecewise linear predictor in data.frame of predicted output.

• piecewise_color (character; 'blue') color of piecewise linear predictor.

• piecewise_lwd (numeric; 1.75) line width parameter for piecewise linear predictor, passed to geom_line(...)

• poly_predictor (character; 'pred_poly') column name of polynomial predictor in data.frame of predicted output.

• poly_color (character; 'green') color of polynomial predictor.

• poly_lwd (numeric; 2.00) line width parameter for polynomial predictor, passed to geom_line(...)

• geom_na_rm (logical; TRUE ) silently remove NA values in the geom_point() & geom_line() calls?

• geom_point_size (numeric; 2 ) ggplot2::geom_point( size = geom_point_size )

• nrow_value (numeric; NULL ) passed to ggplot2::facet_wrap(...)

• ncol_value (numeric; NULL ) passed to ggplot2::facet_wrap(...)

Author(s)

Bill Forrest [e-mail]

Examples

 cat('maeve::maeve_options() allows reset of parameters called in functions within maeve.')
 ## Not run:  maeve_options( 'spline_color' );
           maeve_options( 'spline_color' = 'orange');
           maeve_options( 'spline_color' );
           maeve_reset()
           maeve_options( 'spline_color' );
          
## End(Not run)

wfforrest/maeve documentation built on Jan. 1, 2021, 12:47 p.m.