High-throughput data analysis in behavior genetics

In recent years, a growing need has arisen in different fields for the development of computational systems for automated analysis of large amounts of data (high-throughput). Dealing with nonstandard noise structure and outliers, that could have been detected and corrected in manual analysis, must now be built into the system with the aid of robust methods. We discuss such problems and present insights and solutions in the context of behavior genetics, where data consists of a time series of locations of a mouse in a circular arena. In order to estimate the location, velocity and acceleration of the mouse, and identify stops, we use a nonstandard mix of robust and resistant methods: LOWESS and repeated running median. In addition, we argue that protection against small deviations from experimental protocols can be handled automatically using statistical methods. In our case, it is of biological interest to measure a rodent's distance from the arena's wall, but this measure is corrupted if the arena is not a perfect circle, as required in the protocol. The problem is addressed by estimating robustly the actual boundary of the arena and its center using a nonparametric regression quantile of the behavioral data, with the aid of a fast algorithm developed for that purpose.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS304 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective

A call center is a service network in which agents provide telephone-based services. Customers that seek these services are delayed in tele-queues. This paper summarizes an analysis of a unique record of call center operations. The data comprise a complete operational history of a small banking call center, call by call, over a full year. Taking the perspective of queueing theory, we decompose the service process into three fundamental components: arrivals, customer abandonment behavior and service durations. Each component involves different basic mathematical structures and requires a different style of statistical analysis. Some of the key empirical results are sketched, along with descriptions of the varied techniques required. Several statistical techniques are developed for analysis of the basic components. One of these is a test that a point process is a Poisson process. Another involves estimation of the mean function in a nonparametric regression with lognormal errors. A new graphical technique is introduced for nonparametric hazard rate estimation with censored data. Models are developed and implemented for forecasting of Poisson arrival rates. We then survey how the characteristics deduced from the statistical analyses form the building blocks for theoretically interesting and practically useful mathematical models for call center operations. Key Words: call centers, queueing theory, lognormal distribution, inhomogeneous Poisson process, censored data, human patience, prediction of Poisson rates, Khintchine-Pollaczek formula, service times, arrival rate, abandonment rate, multiserver queues.

Statistical Analysis of a Telephone Call Center

A call center is a service network in which agents provide telephone-based services. Customers who seek these services are delayed in tele-queues. This article summarizes an analysis of a unique record of call center operations. The data comprise a complete operational history of a small banking call center, call by call, over a full year. Taking the perspective of queueing theory, we decompose the service process into three fundamental components: arrivals, customer patience, and service durations. Each component involves different basic mathematical structures and requires a different style of statistical analysis. Some of the key empirical results are sketched, along with descriptions of the varied techniques required. Several statistical techniques are developed for analysis of the basic components. One of these techniques is a test that a point process is a Poisson process. Another involves estimation of the mean function in a nonparametric regression with lognormal errors. A new graphical technique is introduced for nonparametric hazard rate estimation with censored data. Models are developed and implemented for forecasting of Poisson arrival rates. Finally, the article surveys how the characteristics deduced from the statistical analyses form the building blocks for theoretically interesting and practically useful mathematical models for call center operations

Head-to-head trial of pegunigalsidase alfa versus agalsidase beta in patients with Fabry disease and deteriorating renal function: results from the 2-year randomised phase III BALANCE study

BACKGROUND: Pegunigalsidase alfa is a PEGylated α-galactosidase A enzyme replacement therapy. BALANCE (NCT02795676) assessed non-inferiority of pegunigalsidase alfa versus agalsidase beta in adults with Fabry disease with an annualised estimated glomerular filtration rate (eGFR) slope more negative than -2 mL/min/1.73 m2/year who had received agalsidase beta for ≥1 year. METHODS: Patients were randomly assigned 2:1 to receive 1 mg/kg pegunigalsidase alfa or agalsidase beta every 2 weeks for 2 years. The primary efficacy analysis assessed non-inferiority based on median annualised eGFR slope differences between treatment arms. RESULTS: Seventy-seven patients received either pegunigalsidase alfa (n=52) or agalsidase beta (n=25). At baseline, mean (range) age was 44 (18-60) years, 47 (61%) patients were male, median eGFR was 74.5 mL/min/1.73 m2 and median (range) eGFR slope was -7.3 (-30.5, 6.3) mL/min/1.73 m2/year. At 2 years, the difference between median eGFR slopes was -0.36 mL/min/1.73 m2/year, meeting the prespecified non-inferiority margin. Minimal changes were observed in lyso-Gb3 concentrations in both treatment arms at 2 years. Proportions of patients experiencing treatment-related adverse events and mild or moderate infusion-related reactions were similar in both groups, yet exposure-adjusted rates were 3.6-fold and 7.8-fold higher, respectively, with agalsidase beta than pegunigalsidase alfa. At the end of the study, neutralising antibodies were detected in 7 out of 47 (15%) pegunigalsidase alfa-treated patients and 6 out of 23 (26%) agalsidase beta-treated patients. There were no deaths. CONCLUSIONS: Based on rate of eGFR decline over 2 years, pegunigalsidase alfa was non-inferior to agalsidase beta. Pegunigalsidase alfa had lower rates of treatment-emergent adverse events and mild or moderate infusion-related reactions. TRIAL REGISTRATION NUMBER: NCT02795676

An Edgeworth expansion for the m out of n bootstrapped median

It is well known that the ordinary bootstrap distribution of the median is consistent. We show that for bootstrap samples of size m, an Edgeworth expansion holds with reminder term . With extrapolation this gives a best possible rate estimate of the distribution.Bootstrap m out of n bootstrap Median Edgeworth expansion

Statistical Analysis of a Telephone Call Center: A Queueing-Science Perspective

A call center is a service network in which agents provide telephone-based services. Customers that seek these services are delayed in tele-queues. This paper summarizes an analysis of a unique record of call center operations. The data comprise a complete operational history of a small banking call center, call by call, over a full year. Taking the perspective of queueing theory, we decompose the service process into three fundamental components: arrivals, customer patience, and service durations. Each component involves different basic mathematical structures and requires a different style of statistical analysis. Some of the key empirical results are sketched, along with descriptions of the varied techniques required. Several statistical techniques are developed for analysis of the basic components. One of these is a test that a point process is a Poisson process. Another involves estimation of the mean function in a nonparametric regression with lognormal errors. A new graphical technique is introduced for nonparametric hazard rate estimation with censored data. Models are developed and implemented for forecasting of Poisson arrival rates. We then survey how the characteristics deduced from the statistical analyses form the building blocks for theoretically interesting and practically useful mathematical models for call center operations