UIS Drug Treatment Study — UIS • prLogistic

Data from the University of Massachusetts AIDS Research Unit (UMARU) Impact Study, a 5-year study comparing two residential treatment programmes for drug abuse.

Usage

UIS

Format

A data frame with 575 rows and 7 variables:

ID: Patient identifier.
Age: Age at enrolment (years, centred).
DrugUse: History of intravenous drug use: factor with levels "Short" (<= 3 years), "Long" (> 3 years).
race: Race: factor with levels "White", "Other".
trt: Treatment assignment: factor with levels "Short" (3-month), "Long" (6-month).
site: Treatment site: factor with levels "A", "B".
drugFree: Drug-free at 6 months: factor with levels "No", "Yes". Binary outcome.

Source

Hosmer, D. W. & Lemeshow, S. (2000). Applied Logistic Regression, 2nd ed. Wiley, New York.

Examples

data(UIS)
prop.table(table(UIS$drugFree))
#> 
#>        No       Yes 
#> 0.7443478 0.2556522 

fit <- glm(as.integer(drugFree == "Yes") ~ trt + Age + DrugUse + race + site,
           family = binomial, data = UIS)
prLogisticDelta(fit, standardisation = "conditional")
#> 
#> Prevalence Ratio Estimation via Logistic Regression
#> ----------------------------------------------------
#>   Model        : glm 
#>   Method       : delta 
#>   Standardis.  : conditional 
#>   Conf. level  : 95% 
#> ----------------------------------------------------
#> 
#>             Estimate   2.5%  97.5%
#> trtLong       1.4233 1.0489 1.9314
#> Age           0.6239 0.4376 0.8896
#> DrugUseLong   1.7785 1.3150 2.4055
#> raceOther     1.2665 0.9006 1.7811
#> siteB         1.2215 0.8798 1.6960
#>