View source: R/mod_tableGen_fct_methods.R
app_methods | R Documentation |
Find the proper function to apply to each statistical and column block pairing and use the metadata associated with each column block for the function's arguments
app_methods(agg, column, week, group, data, totals, filter = NA)
agg |
the statistic to apply given the block name |
column |
the column to apply that statistic too, and class of the column dictated by the data frame it came from |
week |
the week if needed for calculation |
group |
whether to perform a group_by and if so by which column |
data |
the dataset to perform all functions on |
totals |
the totals data frame that contains denominator N's use when calculating column percentages |
filter |
a string denoting the additional filter to apply to the dataset |
the table corresponding to the proper function to perform given the supplied column. This is used within a map to apply to all blocks inside the table generator module.
if(interactive()){
data(example_dat1, package = "tidyCDISC")
# Create non-missing table section
app_methods("NON_MISSING",
structure("USUBJID", class = c("character", "ADSL")), NA,
"TRT01P", example_dat1$AE, example_dat1$totals)
# Create ANOVA table section
app_methods("ANOVA",
structure("TEMP", class = c("character", "BDS")), "Week 2",
"TRT01P", example_dat1$BDS, example_dat1$totals)
# Create change table section
app_methods("CHG",
structure("WEIGHT", class = c("character", "BDS")), "Week 12",
"TRT01P", example_dat1$BDS, example_dat1$totals)
# Create mean table section
app_methods("MEAN",
structure("PULSE", class = c("character", "BDS")), "Baseline",
"TRT01P", example_dat1$BDS, example_dat1$totals)
}
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