Description Usage Arguments Value See Also Examples
Create BHAI summary table
1 | bhai.prettyTable(pps, pop_norm=FALSE, conf.int=TRUE)
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pps |
The PPS object containing the data. |
pop_norm |
Indicating whether statistics should be computed per 100,000 population, default: TRUE. |
conf.int |
Specifying whether confidence intervals should be computed, default: TRUE. |
A data.frame containing the summarised results.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | data(german_pps_2011_repr)
german_pps_repr = PPS(num_hai_patients = num_hai_patients,
num_hai_patients_by_stratum = num_hai_patients_by_stratum,
num_hai_patients_by_stratum_prior = num_hai_patients_by_stratum_prior,
num_survey_patients = num_survey_patients,
length_of_stay = length_of_stay,
loi_pps = loi_pps,
mccabe_scores_distr = mccabe_scores_distr,
mccabe_life_exp = mccabe_life_exp,
hospital_discharges = hospital_discharges,
population = population,
country="Germany (representative sample)")
german_pps_repr
set.seed(3)
# The following example is run only for illustratory reasons
# Note that you should never run the function with only 10 Monte-Carlo simulations in practice!
result = bhai(german_pps_repr, nsim=10)
bhai.prettyTable(result)
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