Questionnaires from 63 participants were not collected at the urological departments before surgery because of logistic failures.
To account for an approximately 3% dropout by technical or logistic failures of the 3D-RX-system, a total of 250 patients have to be included for each fracture type.
27 Once the best distribution was chosen, a log-logistic accelerated failure time-to-event model with gamma frailty was obtained.
In a hierarchical logistic model, heart failure (odds ratio, 3.06, 95% confidence interval, 1.89-4.95) and less-frequent angina (odds ratio for monthly angina [versus daily/weekly], 1.69; 95% confidence interval, 1.12-2.56) were associated with greater odds of under-recognition.
To identify baseline predictors of treatment failure, logistic regression analysis was performed, with the outcome being treatment failure and the independent variables at randomization being diabetes duration, HbA1c, and oDI in addition to age, sex, race/ethnicity, and BMI.
In an adjusted multiple logistic regression model, failure to clear HCV was associated with black race, injection drug use, higher nadir CD4+ T-cell counts, and lower platelets (Supplemental Table 1).
In logistic regression models, failure to achieve maximum recorded visual acuity of 6/7.5 in right eyes with self refraction was associated with greater absolute value of myopia/hyperopia (P<0.001), greater astigmatism (P=0.001), and not having previously worn spectacles (P=0.002), but not age or sex.
The results of the logistic regression for reinduction failure occurring at the first and later salvage attempts are displayed in Table 3. Salvage attempt number, duration of previous remission, and NCI risk category at diagnosis were all significant predictors in both univariable and multivariable analyses (Table 3).
Multivariable analyses were carried out using logistic regression for growth failure and linear regression for weight and length gains.
Another possible limitation is the failure of logistic regression analysis to take into account the intra-patient variability [ 51- 54].
