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MRM chi-square family on d-series.

Source: R/otis_all_analyze.R
morie_otis_analyze_d_chi2.Rd

Yearly trend (d01 Poisson CIs) + Alert x Cause / Housing contingency chi^2 + Cramer's V on d06 / d07.

Usage

morie_otis_analyze_d_chi2(datasets, out_dir = NULL)

Arguments

datasets

Named list with d01, d06, d07 data.frames.

out_dir

Optional output directory.

Value

morie_otis_analysis_result.

Examples

# \donttest{
otis_d01 <- morie_synth_otis("d01", n = 120L, seed = 1L)
otis_d06 <- morie_synth_otis("d06", n = 120L, seed = 1L)
otis_d07 <- morie_synth_otis("d07", n = 120L, seed = 1L)
morie_otis_analyze_d_chi2(list(d01 = otis_d01,
                                 d06 = otis_d06, d07 = otis_d07))
#> OTIS d-series -- yearly death counts + Alert x Cause/Housing chi^2
#> ==================================================================
#>   d01 total deaths                       120
#>   d01 year range                         2018-2024
#>   Year-over-year RR                      1.000 (2024/2018; n=19/19; 95% CI [0.529, 1.889])
#>   d06 (Alert x MedicalCause) Cramer's V  0.2226
#>   d07 (Alert x Housing_Type) Cramer's V  n/a
#> 
#> d-series carries no per-individual alert columns -- the Ruhela alert-complexity dual is structurally impossible. Natural alternatives are: (1) yearly death-count trends, and (2) Cramer's V on d06 / d07 aggregate contingency tables. 
# }