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Nontuberculous mycobacteria (NTM) are potential respiratory pathogens in cystic fibrosis (CF). To assess the species-specific prevalence and risk factors for acquisition, we conducted a prospective, cross-sectional study of the prevalence of NTM and clinical features of patients at 21 U.S. centers. Almost 10% of patients with CF who were 10 years or older were included (n = 986). The overall prevalence of NTM in sputum was 13.0% (range by center, 7-24%). Mycobacterium avium complex (72%) and Mycobacterium abscessus (16%) were the most common species. When compared with patients with CF without NTM, culture-positive subjects were older (26 vs. 22 years, p < 0.001), had a higher FEV1 (60 vs. 54%, p < 0.01), higher frequency of Staphylococcus aureus (43 vs. 31%, p < 0.01), and lower frequency of Pseudomonas aeruginosa (71 vs. 82%, p < 0.01). Molecular typing revealed that almost all patients within each center had unique NTM strains. In summary, NTM are common in patients with CF, but neither person-to-person nor nosocomial acquisition explained the high prevalence. Older age was the most significant predictor for isolation of NTM. The clinical significance of NTM in CF is incompletely defined, but patients with these organisms should be monitored with repeat cultures.

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Summary.  A class of Shewhart‐type distribution‐free control charts is considered. A key advantage of these charts is that the in‐control run length distribution is the same for all continuous process distributions. Exact expressions for the run length distribution and the average run length (ARL) are derived and properties of the charts are studied via evaluations of the run length distribution probabilities and the ARL. Tables are provided for implementation for some typical ARL values and false alarm rates. The charts proposed are preferable from a robustness point of view, have attractive ARL properties and would be particularly useful in situations where one uses a classical Shewhart  X‐chart. A numerical illustration is given.

Traditional statistical process control for variables data often involves the use of a separate mean and a standard deviation chart. Several proposals have been published recently, where a single (combination) chart that is simpler and may have performance advantages, is used. The assumption of normality is crucial for the validity of these charts. In this article, a single distribution‐free Shewhart‐type chart is proposed for monitoring the location and the scale parameters of a continuous distribution when both of these parameters are unknown. The plotting statistic combines two popular nonparametric test statistics: the Wilcoxon rank sum test for location and the Ansari–Bradley test for scale. Being nonparametric, all in‐control properties of the proposed chart remain the same and known for all continuous distributions. Control limits are tabulated for implementation in practice. The in‐control and the out‐of‐control performance properties of the chart are investigated in simulation studies in terms of the mean, the standard deviation, the median, and some percentiles of the run length distribution. The influence of the reference sample size is examined. A numerical example is given for illustration. Summary and conclusions are offered. Copyright © 2011 John Wiley & Sons, Ltd.