Data from a randomised clinical trial comparing two oral antifungal treatments (itraconazole vs terbinafine) for toenail dermatophyte infection. Patients were measured at up to 7 visits over 18 months.
Format
A data frame with 1908 rows and 5 variables:
- ID
Patient identifier. There are 294 patients.
- Response
Presence of moderate or severe onycholysis (nail separation): factor with levels
"Not moderate/severe","Moderate/severe". Binary outcome.- Treatment
Antifungal treatment: factor with levels
"Itraconazole","Terbinafine".- Month
Time since randomisation (months, continuous).
- Visit
Visit number (1 to 7, integer).
Source
De Backer, M. et al. (1998). Twelve weeks of continuous oral therapy for toenail onychomycosis caused by dermatophytes. Journal of the American Academy of Dermatology, 38, S57-S63.
Details
The dataset illustrates a longitudinal binary outcome with dropout (not all patients have 7 visits). GEE with an unstructured or exchangeable correlation is commonly used.
Examples
data(Toenail)
table(Toenail$Response, Toenail$Treatment)
#>
#> Itraconazole Terbinafine
#> Not moderate/severe 723 777
#> Moderate/severe 214 194
# \donttest{
library(geepack)
Toenail$resp_bin <- as.integer(Toenail$Response == "Moderate/severe")
fit_gee <- geeglm(resp_bin ~ Treatment + Month,
family = binomial, id = ID,
corstr = "exchangeable", data = Toenail)
prLogisticGEE(fit_gee)
#>
#> Prevalence Ratio Estimation via Logistic Regression
#> ----------------------------------------------------
#> Model : geeglm
#> Method : delta
#> Standardis. : marginal
#> Conf. level : 95%
#> ----------------------------------------------------
#>
#> Estimate 2.5% 97.5%
#> TreatmentTerbinafine 1.0299 0.6949 1.5264
#> Month 0.8723 0.8458 0.8996
#>
# }