app_changes.qmd

---
title: Changes
---

## Important changes with version 0.53

### Single-case studies with cases of varying phase design

Sometimes it is necessary to combine single-cases with different phase-designs into one single-case study (for instance when some cases include an extension phase and others do not). Various functions in scan now can handle such a data structure.

### Piping

The concept of piping is great for writing clean and intelligible code that is easier to debug. We imported the pipe function `%>%` from the `magrittr` package. Since version 4.1, R has its own pipe operator implementation `|>`. This is great and works fine with the `scan` package. But since the `|>` Operator is not backwards compatible for R prior versions 4.1, we will stick with the `%>%` for a while.

To allow for smooth "piping" we began adding some functions `select_phases`, `subset`, `select_cases`, `set_var`, `set_dvar`, `set_mvar`, `set_pvar`, and `add_l2`.

## Important changes with version 0.50

### New function names

With version 0.50 scan introduced new names for its functions. The old function names are still usable but they will return a "deprecated" warning telling you to use the new function names.

@rtbl-aliases shows the changes.

```{r}
#| tbl-cap: Scan previous and current function names
#| echo: false
#| label: tbl-aliases

out <- tribble(
  ~"Current function name", ~"Previous function name",
  "autocorr", "autocorrSC",
  "corrected_tau", "corrected_tauSC",
  "describe [since v0.52]", "describeSC",
  "fill_missing", "fillmissingSC",
  "outlier", "outlierSC",
  "overlap", "overlapSC",
  "power_test", "power_testSC",
  "rand_test", "randSC; rand.test",
  "ranks", "rankSC",
  "rci", "rCi; rciSC",
  "shift", "shiftSC",
  "smooth_cases", "smoothSC",
  "style_plot", "style.plotSC; style_plotSC",
  "tau_u", "tauUSC",
  "trend", "trendSC",
  "truncate_phase", "truncateSC"
)

print_table(out)

```

### Change target variables in functions

All functions in R that analyze data now allow for temporarily changing dependent, phase, and measurement-time variables by adding three argument:

`dvar` sets the dependent variable.\
`pvar` sets the phase variable.\
`mvar` sets the measurement-time variable.

For example, `overlap(exampleAB_add, dvar = "depression")` will report overlap parameters for the variable *depression* while `overlap(exampleAB_add)` while take *wellbeing* as the dependent variable (as defined in the scdf).

After finishing the analysis, the variables are set back to their original values as defined in the scdf.