Create a specifications object for fitting regression models in Julia

Usage

make_jlmer_spec(
  formula,
  data,
  subject = NULL,
  trial = NULL,
  time = NULL,
  drop_terms = NULL,
  ...
)

Arguments

formula: Model formula in R syntax
data: A data frame
subject: Column for subjects in the data.
trial: Column for trials in the data. Must uniquely identify a time series within subject (for example, the column for items in a counterbalanced design where each subject sees exactly one item).
time: Column for time in the data.
drop_terms: (Optional) any terms to drop from the reconstructed model formula
...: Unused, for extensibility.

Value

An object of class jlmer_spec.

Examples

# Bare specification object (minimal spec for fitting a global model)
spec <- make_jlmer_spec(weight ~ 1 + Diet, ChickWeight)
spec
#> ── jlmer specification ───────────────────────────────────────── <jlmer_spec> ──
#> Formula: weight ~ 1 + Diet2 + Diet3 + Diet4
#> Predictors:
#>   Diet: Diet2, Diet3, Diet4
#> Data:
#> # A tibble: 578 × 4
#>   weight Diet2 Diet3 Diet4
#>    <dbl> <dbl> <dbl> <dbl>
#> 1     42     0     0     0
#> 2     51     0     0     0
#> 3     59     0     0     0
#> # ℹ 575 more rows
#> ────────────────────────────────────────────────────────────────────────────────

# Constraints on specification for CPA:
# 1) The combination of `subject`, `trial`, and `time` must uniquely identify rows in the data
# 2) `time` must have constant sampling rate (i.e., evenly spaced values)
spec_wrong <- make_jlmer_spec(
  weight ~ 1 + Diet, ChickWeight,
  time = "Time"
)
#> ! Grouping column "Time" does not uniquely identify rows in the data.
#> ! Sampling rate for the `time` column "Time" is not constant - may affect interpretability of results.
unique(ChickWeight$Time)
#>  [1]  0  2  4  6  8 10 12 14 16 18 20 21

# Corrected specification for the above
spec_correct <- make_jlmer_spec(
  weight ~ 1 + Diet, subset(ChickWeight, Time <= 20),
  subject = "Chick", time = "Time"
)
spec_correct
#> ── jlmer specification ───────────────────────────────────────── <jlmer_spec> ──
#> Formula: weight ~ 1 + Diet2 + Diet3 + Diet4
#> Predictors:
#>   Diet: Diet2, Diet3, Diet4
#> Groupings:
#>   Subject: Chick
#>   Trial:
#>   Time: Time
#> Data:
#> # A tibble: 533 × 6
#>   weight Diet2 Diet3 Diet4 Chick  Time
#>    <dbl> <dbl> <dbl> <dbl> <ord> <dbl>
#> 1     42     0     0     0 1         0
#> 2     51     0     0     0 1         2
#> 3     59     0     0     0 1         4
#> # ℹ 530 more rows
#> ────────────────────────────────────────────────────────────────────────────────