Nonparametric inference for competing risks current status data with continuous, discrete or grouped observation times

New methods and theory have recently been developed to nonparametrically estimate cumulative incidence functions for competing risks survival data subject to current status censoring. In particular, the limiting distribution of the nonparametric maximum likelihood estimator and a simplified naive estimator have been established under certain smoothness conditions. In this paper, we establish the large-sample behaviour of these estimators in two additional models, namely when the observation time distribution has discrete support and when the observation times are grouped. These asymptotic results are applied to the construction of confidence intervals in the three different models. The methods are illustrated on two datasets regarding the cumulative incidence of different types of menopause from a cross-sectional sample of women in the United States and subtype-specific HIV infection from a sero-prevalence study in injecting drug users in Thailan

Nonparametric inference for competing risks current status data with continuous, discrete or grouped observation times

New methods and theory have recently been developed to nonparametrically estimate cumulative incidence functions for competing risks survival data subject to current status censoring. In particular, the limiting distribution of the nonparametric maximum likelihood estimator and a simplified "naive estimator" have been established under certain smoothness conditions. In this paper, we establish the large-sample behavior of these estimators in two additional models, namely when the observation time distribution has discrete support and when the observation times are grouped. These asymptotic results are applied to the construction of confidence intervals in the three different models. The methods are illustrated on two data sets regarding the cumulative incidence of (i) different types of menopause from a cross-sectional sample of women in the United States and (ii) subtype-specific HIV infection from a sero-prevalence study in injecting drug users in Thailand.Comment: 16 pages, 3 figure

Nonparametric inference for competing risks current status data with continuous, discrete or grouped observation times

New methods and theory have recently been developed to nonparametrically estimate cumulative incidence functions for competing risks survival data subject to current status censoring. In particular, the limiting distribution of the nonparametric maximum likelihood estimator and a simplified naive estimator have been established under certain smoothness conditions. In this paper, we establish the large-sample behaviour of these estimators in two additional models, namely when the observation time distribution has discrete support and when the observation times are grouped. These asymptotic results are applied to the construction of confidence intervals in the three different models. The methods are illustrated on two datasets regarding the cumulative incidence of different types of menopause from a cross-sectional sample of women in the United States and subtype-specific HIV infection from a sero-prevalence study in injecting drug users in Thailand

Inconsistency of the MLE for the joint distribution of interval censored survival times and continuous marks

This paper considers the nonparametric maximum likelihood estimator (MLE) for the joint distribution function of an interval censored survival time and a continuous mark variable. We provide a new explicit formula for the MLE in this problem. We use this formula and the mark specific cumulative hazard function of Huang and Louis (1998) to obtain the almost sure limit of the MLE. This result leads to necessary and sufficient conditions for consistency of the MLE which imply that the MLE is inconsistent in general. We show that the inconsistency can be repaired by discretizing the marks. Our theoretical results are supported by simulations.Comment: 27 pages, 4 figure

Optimal stimulation settings for CMAP scan registrations

Background: The CMAP (Compound Muscle Action Potential) scan is a non-invasive electrodiagnostic tool, which provides a quick and visual assessment of motor unit potentials as electrophysiological components that together constitute the CMAP. The CMAP scan records the electrical activity of the muscle (CMAP) in response to transcutaneous stimulation of the motor nerve with gradual changes in stimulus intensity. Large MUs, including those that result from collateral reinnervation, appear in the CMAP scan as so-called steps, i.e., clearly visible jumps in CMAP amplitude. The CMAP scan also provides information on nerve excitability. This study aims to evaluate the influence of the stimulation protocol used on the CMAP scan and its quantification. Methods: The stimulus frequency (1, 2 and 3 Hz), duration (0.05, 0.1 and 0.3 ms), or number (300, 500 and 1000 stimuli) in CMAP scans of 23 subjects was systematically varied while the other two parameters were kept constant. Pain was measured by means of a visual analogue scale (VAS). Non-parametric paired tests were used to assess significant differences in excitability and step variables and VAS scores between the different stimulus parameter settings. Results: We found no effect of stimulus frequency on CMAP scan variables or VAS scores. Stimulus duration affected excitability variables significantly, with higher stimulus intensity values for shorter stimulus durations. Step variables showed a clear trend towards increasing values with decreasing stimulus number. Conclusions: A protocol delivering 500 stimuli at a frequency of 2 Hz with a 0.1 ms pulse duration optimized CMAP scan quantification with a minimum of subject discomfort, artefact and duration of the recording. CMAP scan variables were influenced by stimulus duration and number; hence, these need to be standardized in future studies

Sustained data access and tools as key ingredients to strengthening EO capacities : examples from land application perspective + powerpoint

Sustainably managing agriculture and forests is key for development, in particular in Africa, and for facing global challenges such as climate change or food security, but requires reliable information. As Earth Observation (EO) satellite data can contribute to these information needs, more and more institutes integrate this technology into their daily work. Facing ever-growing and evolving EO data sources (e.g. new satellites and sensors) and access technology (both online and via EUMETCast satellite broadcast), their applications require software tools to particularly facilitate (i) the exchange of data between the analysis tools, so users can take advantage of each tool’s strengths, and (ii) the processing and analysis of time series. A first example is the Land Surface Analysis Satellite Application Facility (LSA-SAF), that entered the second part of the Continuous Development and Operations Phase (CDOP-2), under the lead of the Portuguese Institute for Sea and Atmosphere (IPMA), in 2011. VITO, joining the LSA-SAF network for the first time and building on previous experiences (e.g. http://www.metops10.vito.be), aims to contribute by producing and delivering operational, 10-daily vegetation indicators based on MetOp-AVHRR. Furthermore, a software tool is developed to aid exploitation of LSA-SAF products, provisionally called “MSG Toolbox”. A second example is the AGRICAB project, that receives funding from the European Union’s 7th Framework Programme for Research (FP7) and aims to build a comprehensive framework for strengthening capacities in the use of EO for agriculture and forestry management in Africa. This framework starts from sustained access to relevant satellite data (e.g. CBERS-3, DEIMOS) and derived products, such as those from the European Copernicus Global Land service, the 15 year time series of SPOT-VEGETATION (and its transition to PROBA-V) and Meteosat Second Generation (e.g. rainfall estimates). It combines local and EO data with tools and training into applications on crop monitoring, area statistics and yield forecasting, livestock insurance and modelling, forest and fire management, all fitted to the needs of stakeholders in the African focus countries

Kemalettin - (Mimar) [1870-1927]

Taha Toros Arşivi, Dosya No: 134-Mimar Kemalettinİstanbul Kalkınma Ajansı (TR10/14/YEN/0033) İstanbul Development Agency (TR10/14/YEN/0033

Long-term outcomes of slipped capital femoral epiphysis treated with in situ pinning

PURPOSE: Slipped capital femoral epiphysis (SCFE) is the commonest hip disorder in adolescents. In situ pinning is commonly performed, yet lately there has been an increase in procedures with open reduction and internal fixation. These procedures, however, are technically demanding with relatively high complication rates and unknown long-term outcomes. Nevertheless, reports on long-term results of in situ fixation are not equivocal. This study evaluates the possible higher risk of worse outcome after in situ pinning of SCFE. METHODS: All patients treated for SCFE with in situ fixation between 1980 and 2002 in four different hospitals were asked to participate. Patients were divided into three groups, based on severity of the slip. Patients were invited to the outpatient clinic for physical examination and X-rays, and to fill out the questionnaires HOOS, EQ5D, and SF36. ANOVA and chi-squared tests were used to analyze differences between groups. RESULTS: Sixty-one patients with 78 slips filled out the questionnaires. Patients with severe slips had worse scores on HOOS, EQ5D, and SF36. 75 % of patients with severe slips had severe osteoarthritis, compared to 2 % of mild and 11 % of moderate slips. CONCLUSION: Hips with mild and moderate SCFE generally had good functional and radiological outcome at a mean follow-up of 18 years, and for these hips there seems to be no indication for open procedures. However, severe slips have a significantly worse outcome, and open reduction and internal fixation could therefore be considered

Karagöz tetkikleri

Taha Toros Arşivi, Dosya No: 176-Karagöz Sanatkarlarıİstanbul Kalkınma Ajansı (TR10/14/YEN/0033) İstanbul Development Agency (TR10/14/YEN/0033