clean_perch_data {baker}

Clean PERCH data

Description

clean_perch_data transforms a raw data table (row for subjects, column for variables - named as {pathogen name}_{specimen}{test} for lab tests or other covariates) into a list. It is designed for PERCH data format.

Usage

clean_perch_data(clean_options)

Arguments

clean_options

The list of options for cleaning PERCH data. Its elements are defined as follows:

raw_meas_dir

: The file path to the raw data;

case_def

: Variable name in raw data for case definition;

case_def_val

: The value for case definition;

ctrl_def

: Variable name in raw data for control definition;

ctrl_def_val

: The value for control definition;

X_strat

: A vector of variable names for stratifying the data to perform SEPARATE analyses;

X_strat_val

: A list of values for X_strat. The output data only have individuals with identical(X_strat,X_strat_val)==TRUE. To perform analysis on a single site, say "02GAM", use X_strat="newSITE" and X_strat_val=list("02GAM");

BrS_objects

: A list of BrS objects built by make_meas_object();

SS_objects

: A list of SS objects built by make_meas_object();

X_extra

: A vector of covariate names for regression or visualization;

patho_taxo_dir

: The file path to the pathogen category or taxonomy information (.csv). The information should be as complete as possible for a particular analysis. If not, the pathogen without taxonomy information could not be assigned to bacterial or viral groups (see plot_group_etiology()); See assign_taxo_cause_list() that requires this taxonomy information.

.

Value

A List: list(Mobs,Y,X)

• Mobs A list of bronze- (MBS), silver- (MSS), and gold-standard (MGS, if available) measurements. See the formats of these measurements in extract_data_raw().

• Y 1 for case; 0 for control;

• X Data frame of covariates for cases and controls. The covariate names are specified in X_extra;

This function does not re-order pathogens that only have silver-standard data.

See Also

make_meas_object for wrapping information about a particular type of measurement; extract_data_raw for reading raw data table and organizing them into data_nplcm format. Also see clean_combine_subsites for combining subsites and parse_date_time for parsing date.