d03 aggregate Ruhela: Indigenous -> custodial deaths

Usage

morie_otis_analyze_d03_ruhela_aggregate(data, out_dir = NULL)

morie_otis_analyze_d03_mrm_aggregate(data, out_dir = NULL)

Arguments

data: d03 data.frame.
out_dir: Optional.

Value

morie_otis_analysis_result.

Examples

# \donttest{
otis_d03 <- morie_synth_otis("d03", n = 120L, seed = 1L)
morie_otis_analyze_d03_ruhela_aggregate(otis_d03)
#> OTIS d03 -- Aggregate RF: Indigenous -> Number of custodial deaths
#> ==================================================================
#>   Source file                            d03_deaths_in_custody_race.csv
#>   Dataset id                             d03
#>   Treatment column                       T_indigenous
#>   Outcome (count)                        Number_CustodialDeaths
#>   Year FE                                Year
#>   Covariate FEs                          none
#>   Cluster group (GEE)                    --
#>   Cells                                  120
#>   Total outcome count                    5183
#>   Overdispersion (Poisson AIC - NB AIC)  1205.9
#> 
#> Aggregate Ruhela formulation -- Poisson + NB IRR for treatment effect on count outcome:
#>   Family   Coefficient            IRR     95% CI          p-value   AIC     Notes
#>   ---------------------------------------------------------------------------------------------
#>   Poisson  factor(T_indigenous)1  1.2801  [1.186, 1.382]  2.29e-10  2335.8  n=120, total_y=5183
#>   NB       factor(T_indigenous)1  1.2762  [0.884, 1.843]  1.94e-01  1129.9  n=120, total_y=5183
#> 
#> Aggregate RF on d03: Indigenous overrepresentation in custodial deaths. Small-sample warning.
#> 
#> IRR > 1 ==> treatment increases the count rate; IRR < 1 ==> treatment decreases it. Concordance between Poisson and NB indicates equidispersion; large gap (Poisson AIC > NB AIC) indicates overdispersion -- trust NB. 
# }