Risk factor analyses for nosocomial infections (NIs) are complex. First, due to competing events for NI, the association between risk factors of NI as measured using hazard rates may not coincide with the association using cumulative probability (risk). Second, patients from the same intensive care unit (ICU) who share the same environmental exposure are likely to be more similar with regard to risk factors predisposing to a NI than patients from different ICUs. We aimed to develop an analytical approach to account for both features and to use it to evaluate associations between patient- and ICU-level characteristics with both rates of NI and competing risks and with the cumulative probability of infection. Methods: We considered a multi-center data base of 159 intensive care units containing 10,9216 admissions (71,0221 admission-days) from the Spanish HELICS-ENVIN ICU network. We analysed the data using two models: an etiologic model (rate-based) and a predictive model (risk-based). In both models, random effects (shared frailties) are introduced to assess heterogeneity. Death and discharge without NI are treated as competing events for NI. Results: There was a large heterogeneity across ICUs in NI hazard rates which remained after accounting for multilevel risk factors, meaning that there are remaining unobserved ICU-specific factors which influence NI occurrence. Heterogeneity across ICUs in terms of cumulative probability of NI was even more pronounced. Several risk factors had markedly different associations in the rate-based and risk-based models. For some the associations differed in magnitude. For example high Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were associated with modest increases in the rate of NB, but large increases in the risk. Others differed in sign, for example respiratory versus cardiovascular diagnostic categories were associated with reduced rate of NB, but an increased risk. Conclusions: A combination of competing risks and multilevel models is required to understand direct and indirect risk factors for NI and distinguish patient-level from ICU-level factors.