mutate() adds new variables and preserves existing ones. select() keeps only the listed variables; rename() keeps all variables.

# S3 method for xpose_data
mutate(.data, ..., .problem, .source, .where)

# S3 method for xpose_data
select(.data, ..., .problem, .source, .where)

# S3 method for xpose_data
rename(.data, ..., .problem, .source, .where)

Arguments

.data

An xpose database object.

...

Name-value pairs of expressions. Use NULL to drop a variable.

These arguments are automatically quoted and evaluated in the context of the data frame. They support unquoting and splicing. See the dplyr vignette("programming") for an introduction to these concepts.

.problem

The problem from which the data will be modified

.source

The source of the data in the xpdb. Can either be 'data' or an output file extension e.g. 'phi'.

.where

A vector of element names to be edited in special (e.g. .where = c('vpc_dat', 'aggr_obs') with vpc).

Examples

# Mutate columns xpdb_ex_pk %>% mutate(lnDV = log(DV), sim_count = irep(ID), .problem = 1) %>% dv_vs_idv(aes(y = lnDV))
#> irep: 1 simulations found.
#> Using data from $prob no.1
#> Filtering data by EVID == 0
# Rename/select columns xpdb_ex_pk %>% select(ID:TAD, DV, EVID) %>% rename(TSLD = TAD) %>% dv_vs_idv(aes(x = TSLD))
#> Using data from $prob no.1
#> Filtering data by EVID == 0